Every board is asking how the company is leveraging AI. At first they just wanted to make sure the company was using AI, but now they want to know:

• What are you doing that actually adds value for customers?

• What are the best use-cases for internal work?

• Are you moving faster and/or more efficiently yet?

Brex’s The CFO Guide to AI Strategy is a great resource for CFOs to see where other finance teams are finding the best AI use-cases right now. I have implemented most of this myself…

Download the Guide

The Highest Paid Person

Many people assume the CEO, CFO, and other executives are the highest paid people at the company. A benefit of being in finance is you get to peek at everyone’s compensation, which sometimes comes with questioning your career choices.

There are two components of an employee’s total compensation:

1. Cash - base salary + bonus

2. Equity - stock options, RSUs, etc

For private companies (particularly those without an active secondary market), the highest cash-basis earners are almost never the exec team. If they are the highest paid, then something is probably wrong at the company (like flat revenue growth).

Who’s getting the most cash?

It should almost always be your sales reps. How many reps are earning more than the exec team is usually a function of company size and how many sales reps you have.

Top 10 Paid Employees (cash-basis) at ~$250M ARR Mid-Growth Company

I recently spoke with a CFO at a mid-size software company with decent revenue growth. Below were their top 10 highest paid folks:

Notice anything? It’s mostly sales folks…Other than the CRO (who owns sales), no other exec was in the top 5 (but they are doing OK too :)

How Much Does the Top Sales Rep Typically Make?

Below is survey data from RepVue on how much the top earner makes in a year (base, commissions, bonus, etc)

Most of these top-earning sales reps would be the highest paid people at their companies (with the obvious exception of the public ones).

Are we paying sales reps too much?

As painful as it might be to approve those 6-figure commission checks, you can’t conclude that just because a sales rep (or a few) are making a ton of money that the commission plan is broken.

All else being equal, I would love to hire great sales reps and pay them half as much and still close the same number of deals. Efficiency goes way up, right?!?!

Nah. That wouldn’t actually happen…

Your best sales reps are highly paid, but also they create the most sales efficiency. The reps you should be worried about are the mediocre ones. They are the expensive ones.

Example: Top Rep vs Mediocre Rep

The below compares two enterprise reps with the same OTE and quota. Except one rep closes $1M in ARR (or 77% attainment) while the other rep closes $5M (or 385% attainment). The “Top Rep” gets massive accelerator commission rates (20%) on everything over $1.3M in bookings while the “Mediocre Rep” earns just 11.5% commission rates on everything he closes.

CEO: Whoa…We are paying “Top Rep” too much! He is getting 20% commission rates and made over $1M.

Me: If you compare Top Rep’s cost to ARR, he is only 74% the cost of Mediocre Rep…He is our highest ROI Rep.

But even the above scenario doesn’t capture the true value difference based on my experience… Because the best reps usually:

1. Discount less - so gross margins are better on their deals

2. Qualify accounts better - so churn is lower on their deals

3. Set better expectations - Fewer concessions and less CSM work

Not saying they are perfect at all of these, but the mediocre/poor reps are usually more desperate and less experienced in all of these areas. If you haven’t, build a report to look at average discounting % by rep. It’s usually interesting…

How Much is Too Much?

While top-performing reps are more efficient, CROs and CFOs need to figure out the best balance - pushing higher revenue while improving GTM efficiency. If all your sales reps are crushing quota, then your comp plans aren’t aggressive enough.

If you average the attainment numbers of all the companies from the RepVue chart then you get an average of ~60% of reps hitting quota. Ie only 60% of sales reps are at least getting their OTE while the remaining 40% are not.

There are a few different thoughts on what attainment targets should look like:

• Dave Kellogg says 80% of reps at 80%+ attainment

• Others say 80% of reps at 100%

• Team-wide quota at 75%

• And many other versions of the above

Too high, not aggressive enough. Too low and the best reps will leave and a sales death spiral will happen. So if your top 10 earners are all sales reps then you may have a problem (not aggressive enough).

Two things are always true for growing companies:

1. Quotas are increasing

2. Territories are shrinking

What About Total Compensation?

Total theoretical compensation is almost always the highest for the executive team (CEO, CFO, CRO, COO, GC, CMO, etc) because of the size of their equity grants.

The top sales rep from my example above (making $870K) has VERY little equity. Like 0.005% of fully diluted. Maybe he will make $100K - $200K if things go really well with his equity.

The executives have 100x+ that…

If the company is public or has a decent exit, then the exec equity will be worth a lot more than the difference in cash-basis compensation. But…for most companies the “decent exit” is a BIG if.

Below is Fastly’s pay mix for its executives (CEO vs other execs). Only 11% of compensation is cash (salary and bonus)…The rest is tied to equity that is either service-based or performance-based.

Below is the pay of 5 public company CFOs and their relative cash versus equity mix.

Why I Love When Sales Reps Make a Ton of Money

And here is why every CFO, CEO, and any other exec should be cheering when their top sales reps are making a lot of money.

$1M incremental ARR booked at accelerator commission rates is $200K in commissions to the sales rep. But it also represents $100K in additional equity value for the CFO (assuming 1% ownership and a 10x revenue multiple)…And I am, theoretically, getting this much richer every time a deal is closed (assuming there is, or will be, a market for my shares).

We want sales reps worried about commissions, while execs worry about enterprise value.

Final Thoughts

Yes, sometimes I get jealous when I approve 6-figure commission checks but then I remember that hopefully means things are working well. And that my equity value is growing.

Occasionally an easy whale deal will fall into a sales rep’s lap, but the consistent top performers work REALLY hard and are 100% worth the massive commission payouts.

Footnotes:

• Check out The CFO Guide to AI Strategy and figure out how your team should be leveraging AI to get the most ROI

• Subscribe and share with your friends

Subscribe now

*Disclaimer: Informational and educational purposes only. Not tax, legal, or investments advice. The author may own positions in companies discussed. Do your own research.

In the age of AI, finance teams need to move fast while staying in control.

Brex is the intelligent finance platform that gives you the AI-native workflows to move fast (handling receipts, memos, transaction monitoring, policy enforcement, etc) while staying in control and eliminating manual busy work.

Join companies like Anthropic and Zoom that are moving faster because of Brex.

Learn More

The IPO window seems mostly closed except for the very best AI companies. Also, there are several public tech companies that IPO’d during the ZIRP era that in retrospect should never have gone public (AI accelerated some of their downfalls)…

This means that M&A has become an even more important source of liquidity and “soft landing” for companies.

One such public company is BigCommerce (recently changed name to Commerce.com):

• Stock is down 97% since the IPO

• Basically zero revenue growth

• Barely profitable (3% NTM FCF margins and near breakeven GAAP profitable)

What is a company like this worth?

Not much…BigCommerce trades at a 0.6x NTM revenue multiple, which is the lowest of any public software company that I track. Shopify, its closest public competitor, trades at 11.5x.

During peak software stupidity (2021), BigCommerce traded at 13.5x while Shopify traded at 37x. Relatively, BigCommerce has fallen A LOT more …

A Prediction with a Meme

As I was looking at BigCommerce and thinking “these guys definitely shouldn’t be a standalone public company anymore”, I posted the below meme.

Narrator: Bending Spoons (the serial SaaS acquirer) is creepily watching BigCommerce as a potential acquisition target

I have no idea if Bending Spoons is looking at BigCommerce (although at least a couple senior Bending Spoons folks liked the Tweet :). But…I do think it could be a decent acquisition for someone. For the right acquirer, they could probably pay up to 2x the current valuation and do well.

If you are not familiar with Bending Spoons’ game….they are a serial acquirer of digital/SaaS businesses and they IPO’d in July.

They buy struggling businesses and “transform” them into cash flow machines by cutting costs, maintaining/improving product, and usually raising product prices (by a lot sometimes).

Below are some recent Bending Spoons acquisitions:

Their business sounds a lot like private equity, but with one important difference - they never plan to sell (and never have) any of the businesses that they acquire. They don’t buy with the plan to sell in 3-5 years for 3x the purchase price like PE. They get their returns by turning acquisitions into cash cows that pay for themselves (rather than relying on a future exit)

It’s not just something cheap that they are looking for. Bending Spoons wants a product that is sticky

There are two good ways to look at this from a numbers perspective:

1. RPO (Remaining Performance Obligations)

RPO represents all contracted revenue that hasn’t been recognized. It’s different than deferred revenue (which is on the balance sheet) because it also includes unbilled but contracted amounts.

BigCommerce has $201M of locked in revenue, which is crazy compared to their current $220M enterprise value….They basically have locked in future revenue equal to the company’s valuation! *note - the actual amount might be lower because customers go bankrupt or some other extreme circumstances but GAAP requires RPO to be a pretty sure thing.

Some of this future revenue is already reflected in cash because it was paid upfront though. To calculate total contracted unbilled revenue you need to subtract deferred revenue from RPO.

Since there is only $70M in deferred revenue, there is $131M of contractual billings that an acquirer would be able to invoice and collect. Pretty good relative to their valuation!

2. NRR and GRR

PE companies and acquirers like Bending Spoons will spend a lot of time here. It usually won’t be too high otherwise the company will likely be too expensive, but if it’s too low then Bending Spoons would be concerned if the unit economics break and they can’t turn it into a cash machine.

The software business model is built on high NRR and GRR (although most public companies don’t report GRR so we rely on NRR)…

During the 2021 days, BigCommerce had 118% NRR and has dropped to ~95% over the last couple of years. But at least it looks steady! And slightly improving.

It’s not the most straightforward acquisition target for Bending Spoons, but I can definitely see a path for someone to make some money acquiring them.

BigCommerce Rejects Acquisition

A public company (Rezolve AI) actually tried to acquire BigCommerce earlier this year. Rezolve is an AI ecommerce platform so the interest made sense, but their bid apparently did not make sense to the BigCommerce board.

Rezolve’s acquisition attempt is actually pretty funny….

First Acquisition Attempt - Feb 2026

• Strategy: Rezolve went to BigCommerce’s board (non-hostile)

• Price: Rezolve offered 1 share for 1 BigCommerce share. The problem was Rezolve’s stock traded at $2.15 vs BigCommerce’s $3.02…a 29% discount to BigCommerce’s then-current price.

• BigCommerce Board: Rejected the offer asking why shareholders would want an acquisition at a huge discount to current prices.

What’s funny is how Rezolve responded and what they did next:

Rezolve’s Response to Rejection

Rezolve didn’t hold back in their response to BigCommerce’s rejection.

My favorite line: ”Your board rejected a gift”….lol

Rezolve argued that BigCommerce is a “zombie stock” and that the “thinly traded screen price” (stock price) was fake because the volume was so low.

Rezolve went on to say that one Wall Street analyst valued their stock at $11 (4x what they were trading at) so BigCommerce was actually getting a really good deal 🤣. You don’t see that argument every day….

Side Note: My dad recently told me he strongly believes that the OnlyCFO Newsletter is worth $1,000,000,000 so I plan to use that valuation as acquisition currency to build my finance empire.

Second Acquisition Attempt - April 2026

Since BigCommerce rejected their acquisition offer, Rezolve decided to take the offer directly to the shareholders this time (getting hostile!). They wrote an open letter to the shareholders.

But…the offer price changed :)

Rezolve’s new offer: 1 Rezolve share for 2 BigCommerce shares (deal was cut in half and represented a ~50% discount to BigCommerce’s current stock price lol)

Daniel (Rezolve CEO) refers to his bid as a “rescue” 🤣

Rejection and Adopting a “Poison Pill”

You won’t be surprised to hear that BigCommerce also rejected the new offer.

But Rezolve’s aggressiveness prompted BigCommerce to adopt a “Poison Pill” to deter any hostile takeovers. This is common once hostile takeover attempts begin.

What is a “poison pill”?

It’s a defense that makes it much more expensive for someone to acquire a company without the board’s approval.

Here is how BigCommerce’s poison pill works:

1. New Right: Every shareholder gets a new right attached to their shares. The right allows BigCommerce shareholders to pay $13 for $26 worth of BigCommerce stock but only if certain triggers occur (see below)

2. 10% Threshold: Once a person/group acquires 10% ownership (20% for certain passive investors) then the new right is triggered.

3. Exclusion: The right is triggered for everyone except the acquirer (their right is voided). So everyone buys up a lot of stock at a discount and dilutes the potential acquirer.

In theory, an acquirer could just trigger the poison pill dilution and keep buying shares to acquire the company but that would be really expensive with a lot of unknowns. So no one actually does that.

What the hostile acquirer would do next is start a “proxy fight” to get shareholders to elect directors who support their offer and waive the poison pill. Rezolve kind of threatened a proxy fight but doesn’t seem to have actually pursued it, but they told shareholders to vote against the current board members that were up for election.

Why “Classified Boards” Matter

BigCommerce has a “classified board”, which means that there are different classes of directors that serve in staggered terms so that only a minority of directors are up for re-election in any given year.

If Rezolve attempted to continue with the hostile takeover, BigCommerce’s classified board would have also slowed them down because it would take a while for them to get board control.

What’s Next? Does Rezolve give up?

Last month, BigCommerce reported disappointing quarterly results and Rezolve made a press release that basically said “I told you so”. Rezolve didn’t provide a new acquisition offer but they suggested it would be even lower than before if they did…

BigCommerce’s stock fell ~38% over the next three days after their quarterly results. Maybe Rezolve was right?!?! Was the stock mispriced…?

If you track the two companies’ stock prices since the original offer (1:1 share exchange), Rezolve is up only 3% (guess the Wall Street analyst was just early :) while BigCommerce is down 15%. So far, good decision by BigCommerce…

When Will BigCommerce Sell?

I don’t know a ton about BigCommerce other than their financials seem pretty broken and it would likely be more valuable if they weren’t a standalone public company (acquired by Rezolve, Bending Spoons, etc)

But obviously price matters for current equity holders.

It’s hard to see a deal like this getting done for a price below their current stock price. So acquirers will need to either:

1. Wait for the stock price to continue to collapse (but how much further can it fall?)

2. Be willing to pay a 30%+ premium from today’s price

Based on BigCommerce’s performance and continued weak outlook, I wouldn’t be surprised if something happens soon. Seems unlikely the acquirer is Rezolve based on the history though…And it will likely need to be a non-hostile acquirer given the poison pill and classified board.

Maybe someone like Bending Spoons? Maybe…

Footnotes:

• Talk to my friends at Brex for a true AI-native spend platform

• Subscribe and share with your friends

Subscribe now

*Disclaimer: Informational and educational purposes only. Does not constitute investment advice. The author may own positions in companies discussed. Do your own research. Don’t make investment decisions based on anon online characters please

In the age of AI, finance teams need to move fast while staying in control.

Brex is the intelligent finance platform that gives you the AI-native workflows to move fast (handling receipts, memos, transaction monitoring, policy enforcement, etc) while staying in control and eliminating manual busy work.

Join companies like Anthropic and Zoom that are moving faster because of Brex.

Learn More

SaaS is Back Baby!!

Last week felt like a major vibe shift for the SaaS industry. Maybe SaaS isn’t dead after all? The SaaSpocalypse is over and investors just got it wrong…right?

It definitely looks that way based on public software companies’ stock performance last week (and over the past few months). Bessemer’s cloud index is up 55% in 6 months and it’s back to levels not seen since early 2022. SaaS has even outperformed the semiconductor industry over the last 6 months 🤯

Or…is this just a “dead cat bounce”?

Not all software companies are the same…

The SaaSpocalypse was never going to be evenly distributed. Investors treated all SaaS names like AI was going to send them all to zero by tomorrow and now we are doing the same thing on the way up (like they will all be fine).

I have gone through lots of SaaS renewals in 2026 so I put together the 10 biggest reasons why I have said “I am churning” this year. The companies that grow despite these threats (or even turn these threats into advantages) will be just fine.

10 Threats to SaaS Companies

1. Increasing AI Spend Squeezes the SaaS Budget

Every CFO is dealing with the same thing: If AI spend increases (which it probably has), then something else in the budget needs to decrease. Only exception is if you are accelerating revenue by a lot….then maybe you can have both.

AI may indeed reduce headcount, but you better believe that every CFO is pushing on existing SaaS spend as well.

Boards/investors won’t have much patience for higher spend because of AI but no change in revenue growth and/or efficiency…

2. The Value I Get From Claude Broke My Brain On ROI

You want me to pay 2x what we pay for Claude for your little workflow tool?

This makes everyone question how much they are paying for all their tools. It certainly has made me push hard on pricing (both new vendors and renewals). My bar for value relative to price has skyrocketed…

Related point below…And is the reason a lot of companies are starting to see huge price deltas. Are you selling to someone that is AI-pilled or an AI-noob?

3. Exponential Growth In Competition

AI has created an explosion in competition. Many of these competitors are new but AI has accelerated their products to get to feature parity really fast.

And there are two big things that can give them an advantage:

1. AI-native built so AI agents often work better with them

2. Built with less capital and more efficiently so they can be more price competitive

And threat #4 (below) has made the increased competition an even bigger problem for the incumbents.

4. Decline In Switching Costs

It’s becoming so much easier to churn. A few years ago I would have hated to churn off most finance tools because it was such a headache to switch vendors. Long implementation, costly consultants, lots of risk in moving, integrations, etc.

It’s so much easier today.

Most of us don’t have the patience for a long implementation anymore so it’s become a priority for vendors (if you have a long implementation you are ngmi).

5. Vendors Keep Expanding Into Each Other

Most of my vendors have massively accelerated and expanded their roadmap because of AI (as they should). This has meant that several of my vendors’ products are starting to overlap.

For example, one of my larger accounting vendors added a tool (for free) that I was previously paying $50K/year as a point solution…Was it as good? No…but it was good enough. Hard to justify $50K when I got something 80% as good for free.

AI is accelerating roadmaps and vendor surface area. The benefit will accrue to the stickier core tools.

6. Vibecoding

The mere threat of vibecoding or doing something natively in Claude is often enough to get your vendor scrambling to get you a “special deal”. I have played this trick a couple of times…

But sometimes it’s more than a threat. I am not on team “vibecode all your internal tools and therefore SaaS valuations are going to zero”. But…building internally can make sense when customization is important for you. The customization possibilities are one of the biggest reasons in my opinion to build internally.

Pro Tip: If you just want better pricing, then start the conversations early (4+ months before renewal). Then the vendor has plenty of time to panic, escalate, get pressure from the board for their high churn, etc so they make “special exceptions” on pricing.

7. New Pricing Model Is Stupid

I have seen a lot of pricing model changes in my vendor renewals this year. Everyone is trying to figure out how to price in an AI usage-based world.

It’s hard. There will be a lot of pricing experimentation.

But…on the buying side, my initial thought when I hear “We have a new pricing model” is “Great, how are you trying to screw me?”

The vendor’s job is to show:

• We are not trying to screw you (this year or next year as you scale)

• Here is how pricing works and why it makes sense (should be easy to understand)

• This is how you can forecast it

Fail at any of these (but especially the first one) then I am looking at alternatives.

8. AI Has Changed What I Value

AI has changed what we value from our software. For instance, UI matters a lot less today. I am logging into my finance tools less every day. I am relying more on AI agents or working directly in Claude to interact with my software tools.

Does your tool play nice with AI agents and Claude/ChatGPT?

I am probably going to churn from any tool that doesn’t have a prebuilt MCP today.

9. Vendor Not Accelerating Product Roadmap

I really don’t like taking demos. But now I tell my team that we need to occasionally take demos (especially before annual renewals) to see what else is out there.

It takes 30-60 minutes and helps us better understand what others are doing with AI. We churned from one legacy vendor after we discovered how much more we could do with a more AI-native one.

In the old world, SaaS renewals felt almost guaranteed because no one wanted to move. But that ARR feels a lot less “recurring” today because at every renewal I am considering other options.

10. AI Reduces Headcount/Seats

Obviously.

Everyone has heard enough about this so the only thing I will add is to make sure you don’t make stupid pricing changes (#7) because you are rushing to get out of the seat business.

Footnotes:

• Talk to my friends at Brex for a true AI-native spend platform

• Subscribe and share with your friends

Subscribe now

*Disclosure: Nothing discussed in this post is financial, tax, or investment advice.

Want to screw up a fundraising round, an acquisition, or an IPO?

Then don’t pay attention to indirect tax (sales tax, VAT, and GST). You will create a big liability that is hard to quantify without a ton of work. Ask me how I know…

It’s why one of the first things I do when starting a new job is 1) make sure we have good sales tax software and 2) a recent sales tax analysis has been performed.

With Numeral, you get both of these. That’s why Supabase, Character AI, and more than 3,000+ businesses have turned to Numeral’s global solution.

Check out Numeral

Joining [Hot Company] as an Advisor

I just signed my agreement to be an advisor at a pre-seed startup. I don’t normally take advisor roles because I stay pretty busy with my normal job, writing this newsletter, and spending time with my family (including my kids’ never-ending sporting events). But I made an exception for this company….

Will it make me rich? Or will it take a lot of my time with no treasure chest at the end of the rainbow?

Statistically, it is definitely the latter…

It’s the same as early-stage investing, but a much more concentrated bet since there is no way I can be an advisor to the same number of companies that early-stage investors bet on. Early-stage investing only works because of the power law…1-2 investments will return the entire fund and make up for the other 20+ losers that go to zero. This is why early-stage VC funds invest in ~20-30 companies.

So why be an advisor?

There are lots of good reasons to be an advisor:

• Smart team that you are excited to work with (most important)

• They are building in an interesting space

• Opportunity to learn new things

• Build your network and connect with new people

• If they are successful, could set the stage for you joining full-time

Unlike a job where money is a driving factor, don’t become an advisor unless you will learn and enjoy it. And maaaybe (if you are lucky) you might make some money.

The company I am advising checks all of these boxes for me, but I also believe it has the potential to be a massive success (incredible founders, tackling a big problem, they have deep expertise with the problem, and they have me as an advisor :).

Since advisor stuff is top-of-mind…there are a few topics I want to cover:

1. How much are advisors paid?

2. Is the dilution from advisors worth it? What do advisors even do?

3. How to structure an advisor agreement?

4. How do I become an advisor?

5. Bonus content: Did a Cursor advisor make $384M in ~4 years?

Subscribe now

Advisor Compensation & Dilution ROI

Hard Truth: 90%+ of advisors are not worth the dilution. Yes, I made up this stat but it’s definitely true based on my experience.

They take too much equity and provide little value. Common reasons include:

• Failure to set proper scope/expectations

• Misaligned compensation for scope

• Wrong person and/or experience

• The people and expertise you need can change quickly at early-stage companies.

Why don’t you just fire them as soon as you realize they aren’t providing value? They are on a vesting schedule so you can stop the dilution bleeding, right?

You would not be wrong for asking that question…but it rarely actually happens. I’ll explain why further below.

How much do advisors get paid?

Let’s start with the difference between an advisor and a consultant because that can create confusion:

• Advisor:

  • Compensation: Usually equity.

  • Role: Review decks, discuss strategy, provide product feedback, make intros, etc. Advisors provide their perspective and feedback on work that is already created.

• Consultant:

  • Compensation: Typically cash. But could be equity for cash-strapped startups.

  • Role: Produce work. Consultants create decks, perform analysis, write code, etc.

Carta has great benchmarks by fundraising stage that generally line up with my experience. But like most benchmarks…the “right” amount of equity for an advisor can vary a lot.

Equity percentages fall (just like employee equity packages) as a company scales because there is less risk and the equity is theoretically worth more. But also, as a company scales, the need for advisors decreases because a lot of the gaps that advisors fill are replaced by full-time hires.

So what is OnlyCFO’s compensation?

I obviously should charge a high premium for my time :), but like I said…you can’t just assume 1% ownership (90th percentile per Carta benchmarks) because I said it’s a pre-seed company.

Why? Two main reasons:

• How hot is the company? Not every pre-seed company is the same. Some have zero traction and unproven founders while others have real traction and a proven team. We have seen examples of this with some AI companies that go and raise $100M+ pre-seed rounds at $1B+ valuations…

• What are the hours and scope? Unlike full-time employees where there is clear scope/expectations (40+ hours per week), the scope and time commitment can vary wildly for advisors. This makes equity benchmarks less insightful for advisors compared to full-time employees.

Advisor Agreements & Scoping

1. What Do Advisors Do?

There are a few reasons a company may hire an advisor. Some reasons are better than others…Below are the main ones:

• GTM advisors - People who have a large distribution in a company’s target audience, deep connections at important prospects, or someone who is an experienced GTM leader for your market/ICP.

• Technical advisors: Help guide, shape, and recruit for the product. These folks often have good connections at partners or prospects.

• Industry experts - Deep industry expertise to help guide the company

• Network - Help recruit, intros to prospects, or intros to investors

• Credibility boost: Looks cool to have a big, credible name as an advisor. Founders won’t admit that they do this, but they do. But this might be the worst reason to hire an advisor. They require the most equity and usually do very little. You might be surprised how little VCs actually care about your list of advisors…

2. Set Expectations and Scope

Often the problem is that companies bring on an advisor without any real expectations or scope of what that advisor will do.

• What are you hiring an advisor for?

• What are the expectations?

  • # of calls per month

  • Some kind of regular output

  • Providing regular network introductions

  • 💡Tip - I don’t like setting specific hour requirements or being too descriptive of exactly what the advisors will do. They are not consultants paid by the hour. But you can/should be clear about general expectations from the relationship.

• What does success look like? What are the targets?

Without proper scoping, you won’t really know how much equity they should be given. Someone doing weekly calls or providing important prospect connections should probably get more equity than someone just doing monthly calls (all else being equal).

3. Defining Advisor Equity Terms

Equity compensation for advisors looks different from equity compensation for employees. Advisors get much more favorable terms:

• Vesting Period: Typically vests over 2 years (or shorter). Advisors are most helpful until the next level of scale is reached when more full-time folks are hired to fill gaps so a shorter vesting period than employees typically have (e.g., four years) usually makes sense.

• Vesting Cliff: Unlike employees who almost always have a 1-year cliff, advisors typically have no cliff or it’s very short (like 3 months) because equity is their only form of compensation.

• Early Exercise Provision: Most advisor grants have an early exercise provision since it can be very beneficial to exercise early and the price is usually very small at early company stages (where most advisors are hired).

• Equity Type: Typically stock options (NSOs since they aren’t employees), but RSAs are sometimes done when the company is very early.

• Single Trigger Acceleration: Advisor shares are often accelerated in a change of control event (single trigger). Company execs often get double trigger acceleration clauses - there is both 1) a change of control and 2) they are fired (without cause). Most other employees (non-execs) rarely get either of these acceleration triggers.

• Post-Termination Exercise Period (PTEP): Often this is 90 days just like employees, but with one important caveat. Advisors are rarely actually terminated, even if they stop providing work, so their PTEP never actually starts so they effectively have until the grant expires (10 years).

  • The advisor is fully vested anyway so the company lets them stay active and the PTEP clock never starts

  • CEO forgets about actually terminating them

  • Company doesn’t want to create conflict

  • Founder is embarrassed to terminate an advisor when they discover they aren’t a fit. Most advisors are well-connected so it’s less friction to just stop talking to them. This is why you want to be REALLY sure you want the advisor first.

Advisors are like barnacles. They grow on your company and every once in a while they need to be scraped off. — Dave Kellogg

When I first got the keys to the cap table I was shocked how many “barnacles” we had. Still vesting, but not doing anything. Monthly/weekly calls stopped a long time ago.

Be generous with advisors, but set vesting terms and equity size relative to the time period you think you will need the advisor. Think carefully before hiring any advisors because terminating them won’t be easy.

How do I become an advisor?

Start with these two questions:

1. “Why would a company want you as an advisor and spend their precious equity to compensate you?”

2. “What can you solve as an advisor (working a few hours a month) that the current team can’t figure out by themselves (especially with AI)?”

A deep network is the most common reason I see for hiring advisors (especially today). Product expertise can also be very important when the early team doesn’t have deep product knowledge in some part of the product (can massively improve roadmap and building the right thing).

A startup isn’t typically searching LinkedIn or opening up a recruiting search to find an advisor. Advisors come through the network of the founder, exec team, VCs/board, etc.

Go network…pro tip: being great at what you do makes it easy to build a strong network

Bonus Content: Did a Cursor Advisor Make $384M?

SpaceX finalized its $60B acquisition of Cursor this month, a 4-year-old company.

If you were lucky enough to get an advisor role with Cursor by the pre-seed round, you might be taking home ~$384M for maybe a few hours of work a month for a few years…

Here is my quick math:

After the $60B acquisition was announced, several people posted DMs from Cursor’s CEO, who was asking for advice while he started Cursor as an MIT student…Alex’s $600M missed advisor payday is inflated because it doesn’t take into account fundraising dilution, and tbh, the 1% is probably high. But could he have gotten 0.5% and made ~$180M? Maybe…

There are VERY very few Cursor-level outcomes in the world.

Final Thoughts

If you are going to hire advisors, then make sure you carefully scope it, set expectations, have a good agreement, and provide an appropriate amount of equity based on all of this.

I look forward to becoming filthy rich from my advisor shares, but in the meantime I am excited to just have some fun and learn with great founders. I will be sharing some of the journey from this company in future posts (and will eventually name them).

Subscribe now

Advisors (and employees) dreaming about Cursor-level outcomes…

Footnotes:

• Get a Free Sales Tax Analysis - talk to my friends (and sponsor) Numeral so you don’t screw up fundraising or an acquisition because of sales tax.

• Here is the FAST agreement for advisors. A lot of companies use this agreement and they just released version 3 last month that has some good updates.

*Disclosure: Nothing discussed in this post is financial, tax, or investment advice.

CFOs are pushing AI adoption in finance but are their teams, processes, and systems actually ready to make it work?

Hear what 250 CFOs said about adopting AI in their departments in Rillion’s 2026 Finance AI Report webinar. See what’s working, where CFOs are finding the best AI use cases, and what still isn’t ready for prime time.

2026 Finance AI Report Webinar

I asked Nate Nasralla, CEO of Fluint, to guest write about how AI has changed (or should be changing) GTM efficiency and how we evaluate sales reps. Nate has spent 20 years in sales and currently spends all of his time helping sales teams adopt and leverage AI. So he knows what he’s talking about…

His concept of “floating highways” is my new favorite analogy for how we should think about real AI adoption.

So, on to Nate’s post…

Floating Highways: How to Rethink GTM Efficiency & Rep Evaluation for the AI Era

I’ve been at 18 customer onsites since the start of the year, and there’s a simple analogy I’ve used at almost all of them to describe what AI x GTM is right now.

Remember The Flintstones? How Fred traveled around?

A pedal car, powered by his feet. Pure leg day, every day baby.

Now, remember The Jetsons? They had hovercars, a fundamentally different technology. But what’d they do with it? They “drove” down floating highways. With stoplights, cross traffic, and lanes. Taking tech that unlocked entirely new planes of travel, and bolted it onto what they already knew: roads.

Most GTM teams today are running on floating highways. Somewhere in-between the early 2020 motion, and, what’s to come.

You can run all the “AI Maturity Assessments” you’d like, but you really only need one question to know whether your org has been building a truly AI-native GTM:

If you killed all your AI contracts and ripped AI out of your GTM tomorrow, what would stop working?

Not “go slower,” or “be less convenient.”

What would break?

To the extent things break and just stop working, you’ve built an AI-native GTM. To the extent it keeps humming along, just slower: you’ve got a floating highway.

Now here’s why I think this question matters: the efficiency metrics you manage are built for one of these two worlds. So if your gauges are measuring the machine that no longer exists, or your GTM team is actively tearing down, then, you’re about to make headcount, comp, and budget decisions based on those readings.

So this write-up has three parts to help frame the shift you’re in the middle of today:

1. Part 1 is an audit. Which gauges on your dashboard were built for the old machine, vs. where GTM efficiency is actually found now?

2. Part 2 is about building the system. Breaking down “compound” metrics into the drivers you can influence, while modeling your GTM in a way that wasn’t possible before. (And if you do this, ripping AI out would break something, like a kill-switch.)

3. Part 3 is about people decisions. Headcount, comp, ramp, eval, etc. How to figure out if your reps are performing, and seeing the RevOps team building the systems behind them as someone who’s equally on the hook for a “quota” of sorts. Which flows downstream from the first two points.

(Part 1) What’s Changing?

Are you tracking MPG on an electric car?

I still drive my 2015 Audi Q5 because it’s a diesel, and gets 35 miles per gallon (better than my wife’s 21 MPG BMW). But, if I go to an Audi dealer and compare it to the e-tron, my Q5’s MPG is irrelevant. The e-tron’s an electric car, it’s an entirely different category.

Similarly, here’s a shortlist of metrics I’d be cautious of using in the coming year:

• Pipeline Coverage: this used to be a proxy for “more pipeline = more revenue.” But generally, mid-funnel conversion rates are the same or declining year-over-year, with more of a buyer’s evaluation pushing further down the funnel, so early-stage pipeline coverage doesn’t carry the same weight.

• Cost per Lead: I don’t know another operator who isn’t shifting their packaging and pricing. We’ve launched two new products in H1 at Fluint, each with a slightly different pricing model and GTM experience (PLG, self-serve with consumption bands for technical RevOps users, vs. core sales-led experience for non-technical buyers).
  
  So my old measures of who a lead is, and my cost to “buy” one more, don’t work for AI-native customers coming in self-serve.

• Activity per Rep: this used to translate to pipeline. But now, activity is cheap and essentially infinite. So channels are saturated, and creating truly qualified opportunities is about a smaller set of targeted activities, born from a rep’s human judgment.

The common theme here is that sales efficiency is now found deeper in the mid-funnel:

AI is compressing the seller’s work (prep, follow-up, CRM fill, etc.), but, it largely hasn’t touched the buyer’s internal process after top-funnel research. A buyer still has to manage all the internal comms, stakeholder drama, and nuances of human approvals, to either expand a bottom-up experiment into an annual commit, or, for a customer to move to a new price and package.

As an example of this, let’s take a company that’s:

• $100M ARR with three core segments.

• Enterprise ($45M ARR, ~$250K ACV, with 20 AEs).

• Mid-Market ($35M ARR, ~$60K ACV, 25 AEs).

• SMB ($20M ARR, ~$12K ACV, 12 AEs).

We’ll call them “Bedrock” software. (My creation with illustrative numbers, but a composite of a few of our customers.) Their FY24-26 shows the evolution of (1) pre-AI, (2) the floating highway transition, and then, (3) refactoring for the AI era.

FY25 looks pretty good here when you focus on the top-funnel metrics, like lead generation and pipeline coverage. But those top-funnel gains don’t translate to a 1:1 revenue efficiency, if you follow the quality of the pipeline down through the middle and bottom-funnel, like Stage 3 conversion rates and sales cycle times.

Which is what their FY26 is correcting, with less focus on topline effort metrics (when effort was scarce and roughly equal to results). And more focus on mid-funnel efficiency, like stage-by-stage conversion.

Revenue comes from a mix of humans and agents, but agents don’t carry a quota.

In the past, you could use a simple Quota-Attained : OTE ratio to say, “2-3X is bad, 5-6X is good.” (OTE = on-target earnings, what you pay a rep in variable and base compensation).

This compares the human cost to carry out a set of sales actions, to the revenue they produced. But now, a growing share of the sales activity is agentic vs. humans alone:

Which means every new dollar is increasingly system-enabled, not just sales-enabled. And the revenue generated by a system vs. sales carry different cost profiles. Now, follow me here:

• You can split out the cost of each pretty quickly (token spend vs. payroll).

• But it’s not so easy to attribute a percentage of a revenue outcome to an agent vs. a human rep. (The first half of the “Quota:OTE” ratio.)

• So, if you’re spending on tokens to drive up the rep’s efficiency, and to take on a greater share of their work, shouldn’t their quota go up? But by how much?

• And if you’re spending legit dollars on those agents’ tokens, don’t you need to know what the agents return? How well do they “attain” their “quota”?

The point we’re getting to here isn’t about capping AI spend (”tokenmaxxing” critiques have lost the plot). It’s more about the same question that marketing raised a decade ago. Attribution:

Which AI dollars trace to specific closed-won revenue, and which are just… waste?

This same concept around attribution needs to migrate further down the mid-funnel.

Where the next lift in efficiency is migrating (see point #1 above), and agent contribution and spend are growing the fastest. And once that “instrumentation” is in place, it’ll change the assumptions you use to drive capacity planning, compensation, and 2027+ budgets.

Which brings us to part 2, building the system, before we get to part 3, people decisions.

(Part 2) Building the System

Model your GTM:

Your FP&A team models the business with a “driver tree.” But GTM never got the same driver-based approach, because deals seem “non-deterministic.” Too many variables, and too much gut feel from sales leaders who need to sit on weekly forecast calls to divine whether Lakers season tickets are enough to swing Deal A our way.

But now, you can use a lot of data to model the unique properties of your GTM: specific inputs (“behaviors”) that predict that deal, instead of relying on a general rule, “Stage 4 = 80% value.”

“You mean like having our team set up some Gong trackers or something?”

No, I mean a true model that can (1) weight dozens of sales behaviors, (2) retrains itself as your motion changes over time. Which is what you already do in FP&A, but for revenue.

Which you can do for revenue, in two ways:

1. Step one is what you feed the model: it’s about logging all the GTM activity data you have access to, joined to your revenue data.

2. Step two is what the model feeds you: thresholds that signal risk in the pipeline and base. Signals like, “Hey, deals in [ segment ] evaluating [ product X ] close 59% less often when [ title ] isn’t involved by [ stage 3 ].” So Finance doesn’t “peanut butter spread” the same probability across every deal in the same CRM stage.

(This, by the way, is what I spend all day doing with customers at Fluint.)

Break out each segment independently.

I’m not telling you anything you don’t already know or do here. But before we get to part 3, we have to call out that AI delivers efficiency across Enterprise, Mid-market, and SMB segments differently. And we can’t tell an “AI efficiency story” in broad strokes.

For example, at a board-level, let’s say Bedrock’s LTV:CAC ratios looked good after the last year of AI rollouts. CAC drops from $47K to $36K in FY25, so we’d celebrate, “AI efficiency!”

But if we break it out:

The mix just shifted toward SMB as a greater percentage of the customer count, where CAC is structurally lower.

Now, that’s still a pretty high-level example. But the idea is the more granular we go (cost per qualified opp, stage conversions, cycle time, ACV, etc.), the more we’re going to find different takeaways for different segments.

(Part 3) People Decisions (Both Reps and RevOps)

Model the distribution of your reps: how wide is the bell curve, and can you skew it even further?

As a simple thought experiment, say you have only two sellers on your team, and a CFO reaches out to you as a warm referral. Which rep do you intro them to?

• Rep #1: closes 55% of the accounts they work, at $98K ACV

• Rep #2: closes 15% of the accounts they work, at $58K ACV

It’s kind of a no-brainer. Rep #1.

I mean, why wouldn’t you send 100% of referrals their way? Well, eventually, they’ll hit a “productive capacity.” They’ll get tapped out, so adding more accounts to manage drops their close rate and creates diminishing returns.

So instead of pushing your GTM team to “raise the floor” and get underperformers up to quota, first ask: Can we skew the bell curve further to the right? It’s the highest-probability bet.

Similarly, ask: What changes did we make to our GTM process, to drive up our reps’ “productive capacity?” How many more accounts are they working?

I’d much rather lean into the contribution we earn from more variable pay to high-performing reps who’ve cleared their base + benefits, vs. grow off a larger number of average reps.

Ramping new reps is now an infrastructure vs. a talent question.

The old way of ramping a sales hire was a big PDF playbook, updated once annually at SKO.

The new model is a “living” system that rewrites itself based on the GTM data that’s changing every week. More “flywheel” than “process.” Which just couldn’t have existed 18 months ago.

The idea here:

Your top-performing reps at the front of the bell curve (above) often “work in the dark.” They have a gut-feel that drives them to make different decisions, and that judgment isn’t captured anywhere. So when they leave, that knowledge leaves too.

But that judgment is as valuable as any asset capitalized on the balance sheet today.

If this sounds like an operations problem, in my experience, it’s a comp problem, too.

• With AI, now, you can build a model that makes those subjective judgment calls from top performers an explicit dataset.

• That model is constantly trained on your actual GTM motion, not the market average (a general LLM), to guide new hires.

• But first, you need to trace a top rep’s set of behaviors, with them actively contributing training data back into the model.

• To make sure they do that, create a SPIF that gives top reps a payout based on their data added to the model. Which is them helping you build an asset, that’ll appreciate over time.

For example:

Let’s say a high-performer comes off an exec-level customer meeting, and the next step is to loop in the customer’s procurement team. Well:

• Deal #1: the procurement intro comes in at 8:30pm same day, Friday night

• Deal #2: the intro lands the following Wednesday, business hours, at 10am

Those are WILDLY different signals on the level of priority. Which will change how a top rep approaches pricing and negotiation, to hang onto deal value, maximize commitment terms, etc.

The model traces that change in behavior, and feeds direction to a new hire to act similarly. Which moves them closer to the ACV, win rate, etc. of a top hire.

Ultimately, that means you’re funding and grading RevOps and Enablement based on their ability to compound revenue in a system, which should show up in your rep cohort data:

Did the last class of sellers ramp faster and hit a higher level of revenue-per-rep than the cohort before them?

Capacity planning isn’t “linear math” any more.

It’s more like a multivariate equation.

You used to say, well, “We need X ramped reps, with Y quota, to create Z sales capacity…” But based on the above, there’s a whole set of variables changing beneath that.

Like how far the bell curve is skewing, how much the productive capacity per rep is changing, how quickly ramp time is compressing, how far the span of a leader’s control is expanding, etc.

My old board chair, Lee, used to tell me, “Sometimes Nate, you’ve got to sustain the pain to find the gain.” And what he meant was that we deliberately had to understaff to see how far we could push the system.

I’d suggest FY27 planning is a ripe moment for this. With a choice as you add sales capacity:

• What % of sales capacity do we expect to add from new headcount?

• What % do we expect to add from “system leverage”?

• How does that split compare to last year?

I’d expect that split to skew more towards the system than the seller, toward revops and not just reps, as more dollars are used to expand top rep capacity, vs. just seats. (And as I’d come to find out, the regret cycle of an unnecessary hire is longer, and comes with severance…)

What did you change in your rep’s job description? In RevOps’?

Sales Reps:

As an example of what I mean, earlier this year, after we’d rolled out comp plans, we realized that a more technical product mix (which starts self-serve before a sales-led motion), doesn’t lend itself to the typical, “AE sells the logo,” then “CS onboards and retains.”

Instead, we needed to move to a single account-owner structure, with technical enablement. Where Account Directors own the account from first contact through full customer lifecycle.

Which meant cutting our CS org (hard but necessary), and now, judging our ADs (and paying them) based on a combo of new logo activations, upsells, and retention.

Which forced a few “back to basics” questions for us:

• Does the comp plan match the job description?

• Where it doesn’t, what sales behavior do we want to measure?

• And, what “kind of dollar” is worth more? First spend from a new logo? Dollars committed in a multi-year agreement? What will it cost us to get that specific dollar vs. any dollar?

Here, it’s worth noting reps generally optimize for whichever dollar is the path of least resistance. So if the price you pay for each dollar is equal, they’ll figure out a form of “commission arbitrage,” moving toward the segment that’s easiest to get new commission dollars, to exchange them for what feels like a higher payout.

Which you can rebalance with a type of dollar “taxonomy” (net-new / expansion / renewal, by segment) based on the CAC / margin / strategic value to you.

RevOps:

Back to one of the earlier questions we asked: if AI agents are expected to enable an increasing share of revenue, but they don’t carry a quota, how do you measure them?

Or more accurately here, how do you comp their creators?

The RevOps job description is splitting into two directions right now:

• AI: The engineering function responsible for architecting systems that both learn and execute (creating new data to learn from in a loop).

• BI: The reporting and rules functions to dashboard the outcomes, and ensure there’s consistency in operating rhythms across the business.

As an example, Scott Gibbs from Meltwater describes the new RevOps functions they created to enable this. The revenue engineers need upside, and while the comp norms are still being established, the one question I’d have for you is:

• Is the RevOps org on the hook for driving a greater share of the variable revenue outcome?

• If so, to what extent will they share in the upside of a good outcome, with variable comp attached to it? More than last year?

To be clear, I don’t think this looks like a commission plan for RevOps. But it does look like a direct conversation on how their role and compensation are being reorganized.

Slope, not intercept.

The rising tide of AI does not float all boats. So while it’s good to evaluate the efficiency gain AI brings to the revenue org as a whole, I’d suggest a more granular, rep-level look.

It helps to evaluate each rep as a “line, not a dot.”

Buying behavior is changing fast, and a seller’s ability to evolve with it isn’t guaranteed. (In case that wasn’t already obvious.) So, my suggestion is to create a simple line chart of trailing Revenue:OTE on one axis (the “intercept”), with their trajectory over recent quarters on the other (the “slope”).

Then, you can split that grid into quadrants:

• Who were previously the bottom-half performers, that have been accelerating fastest? (Likely a future asset that an annual stack rank may have thought to begin managing out, but, could be among your rising stars.)

• Who were previously the top-half performers, whose performance may be “decaying” over time?

• And collectively, is the median trend line up, or down, midyear? Is the “system” working?

So, where do you go now?

Back to Fred and his pedal car:

The teams still running on floating highways will treat AI as a line item to cap, and they’ll get what they measure: the same motion, just a little faster, with a new expense to explain to the board.

Vs. the teams refactoring for the AI era see it differently. Instead of bolting new tech onto the old roads, they’re building a system where ripping AI out of it would mean breaking the model.

So if you’re somewhere in-between the early 2020 motion and passing the “kill-switch test,” here’s where I’d start this week:

• Check your dash. Was this gauge built for the old machine? Anything measuring topline effort (when effort was scarce and roughly equal to results) goes on the watch list. Move your attention to mid-funnel health, like stage-by-stage conversion.

• Make FY27 planning about the “multivariate” equation. As you add sales capacity, force the question: what % do we expect from new headcount, what % from system leverage, how does that split compare to last year, and what operational changes did we make to drive it?

• Evaluate the revops job description, and sales reps as “lines, not dots.” Plot trailing Revenue:Quota with a quarterly trajectory, find the rising stars, and over-invest in the top quartile of reps. While confirming your revops team is comped and focused on building the system beneath them.

Footnotes:

• Join me and attend Rillion’s 2026 Finance AI Report webinar to learn how other CFOs are implementing AI

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

*Nothing in this article constitutes legal, tax, or investment advice. I am not a lawyer or tax accountant.

Register for Rillion’s 2026 Finance AI Report webinar to hear what 250 CFOs are saying about implementing AI in the “Office of the CFO”.

What’s actually working, where the gaps are, and where things break.

Every finance team is trying to become more AI-native. Hear from AI-forward CFOs who have done it — and learn what worked, what didn’t, and what they’d do differently.

2026 Finance AI Report Webinar

The Most Common Cap Table Issues

A few years ago, I was working with a company that had the worst cap table issues I had ever seen. It was bad… If I was the CFO while these issues happened, I would have changed my name and moved out of the country.

The one positive from this experience, though, is that I learned A LOT about these cap table issues (thanks to some very expensive lawyers), how and what issues can be fixed, and how you might remediate them with your employees.

If you have any ownership over the cap table (CFO, accounting, legal, HR, etc), then please read this post and/or share it with your teams that do. It’s also helpful for regular employees to understand how this stuff works too in case it happens to you.

Mistake #1: Unapproved Grants

An admin error causes grants to not get included on the list that the board of directors approves:

• HR fails to tell finance/legal (or whoever owns the grant list) about promotion grants

• There is a timing cutoff error on new hire grants so a group of new hire grants don’t make it on any approval list

• A founder promises equity but forgets to formalize and communicate with HR.

• Someone forgets to actually add it to the board meeting agenda so the batch of grants never gets approved (everyone just thinks it got approved)

What’s Wrong:

No board approval = no grant.

Offer letters always say something to the effect of “contingent on board approval” with respect to the equity listed in offer letters. This is because typically only the board of directors can approve equity grants.

I have even seen cases where the equity admin thinks the board approved the grant since the board meeting happened, stock option agreements are created, and then sent out and signed by employees….but the board never approved the grant so it still isn’t a legitimate grant. And the employee would have no way of knowing that the company screwed up on the paperwork.

The Fix:

For most equity-related issues, waiting to fix it will only compound the problem.

• How much higher is the 409A fair market value (FMV)? Companies can only grant at (or above) the current FMV so if your company has gotten more valuable, granting the same number of stock options means the employee will be worse off since there is a higher strike price to buy the stock options. This is less of an issue with RSUs.

• Have they exercised an invalid grant? If the issue has gone unfixed for long enough, then some invalid grants may have already been exercised…This makes it much more painful. This is harder to unwind because you have to fix the cap table, refund exercise prices and figure out what to do with any taxes that were paid (AMT, payroll, etc)

• Are they still employees? Now this is where it gets really painful. “Hey John, remember how you exercised $50K worth of stock options last year? Well, funny story….those shares you think you own aren’t real.” Former employees are never as kind to you as the current ones. Also, once someone leaves the company, there are a lot fewer options to remediate the problem.

There are a few imperfect fixes for unapproved grants:

• Re-grant at current FMV. But like I said, if the valuation increased, the employee gets shortchanged. If the 409A decreased then I guess it works out. Slightly bittersweet that the company valuation is decreasing though.

• Top-up grants. Give more options to make the math work. The employee might be happy, but more stock options at a higher price is only good if they expect the price to increase even more than the spread they lost between what the FMV price should have been at versus what they got it at. The company/board is unhappy though because this means more dilution.

• Restricted Stock Awards (RSAs). Can help patch past mistakes, but come with tax consequences that can also create problems for employees that may also need to be solved.

• Cash bonus / settlement: Give some cash to make up for potential tax consequences and/or change in FMV. This is the main fix if they are now an ex-employee that exercised their “options” that don’t actually exist.

• Advisory role workaround for ex-employees. If the employee already left, you can hire them as a contractor/advisor so that you can issue equity to them as a “service provider.” There is some risk here since they should actually be providing some kind of advisory services, which is why this is usually reserved for large grants given to VPs or above.

• Return exercise price. If an employee exercised an invalid grant, then you have to return the exercise price and you also have to decide what you will do about any taxes they paid (AMT or payroll taxes on NSOs). You might also be able to do a W-2c if it was within the past three years, but that is always painful so a settlement payout is often easier.

The only potential “get out of jail free” card is if the invalid grant was issued to an employee that has left and never exercised their stock options. For those, you may have dodged a bullet…

Mistake #2: The Stale 409A Valuation

Private companies must get a new 409A valuation at least every 12 months or following any material business changes (most commonly a financing round).

• Forgot it’s been 12 months since the last 409A was effective and granted equity.

• Financing term sheet is received, but deal isn’t closed. The date the term sheet is received likely invalidates the prior 409A

💡Common mistake: 409As are valid 12 months from the 409A report effective date. Not the 409A report date…. The 409A might be effective on 5/1/25 but your 409A advisor finishes the report on 7/1/25. It expires on 5/1/26 (12 months from effective date)

What’s Wrong:

If a stock option strike price is granted below FMV (regardless of whether its an ISO or NSO), it’s subject to Section 409A, which is a bad thing... There are lots of taxes and penalties for employees if this happens, including losing the ISO status if it was granted as one. It is NOT something you would ever want to do intentionally. It’s a nightmare for both the employee and employer.

The Fix:

Stale 409As are different from unapproved grants. Unapproved grants never actually existed. These grants might exist but they are wrong (and create tax issues). Here is what the fix may look like.

1. Cancel or deem invalid:

   Cancel and “deem invalid” is kind of the same thing, but deeming it invalid is cleaner I think. Basically all stock option plans say that grants must be done at (or above) FMV. So a company can just say the grants didn’t follow the plan so they weren’t properly granted and therefore don’t actually exist. If you “cancel” them then you are kind of saying they were valid, which may mean there should have been tax consequences for below FMV grants.

2. Get a new 409A:

   You probably need to update your 409A. While you may deem the grants invalid under the stale 409A, you still may have a problem with valid exercises that happened under a stale 409A…Exercises have tax consequences depending on the FMV at the time of exercise so if the 409A was stale at the time of exercise then that is a problem for them as well which may require adjustments for tax purposes.

3. Make employees whole:

   Since the grant doesn’t exist the company now has to do one of the make-whole options that I mentioned previously (re-grant at current price, add more options to make up for the increase in FMV, cash bonus/settlement, etc)

Don’t forget to refresh your 409A. The two key times are: 1) at least every 12 months and 2) after a financing. But also understand at what point the 409A goes stale and you must stop any new grant approvals (receiving a financing term sheet, getting an acquisition LOI, etc)

Mistake #3: The Zombie Exercise

This happens at lots of companies… Most stock option agreements have a 3-month post-termination exercise period (“PTEP”). This means that once an employee terminates they have 3 months to exercise their option. Otherwise, the stock option expires.

Here is what usually happens:

1. Someone forgets to enter the termination date into the equity management tool

2. Three-month window never starts in the system

3. Employee checks 6 months later and decides to exercise because it’s still available in the system

💡PTEP vs ISO Status: A lot of people incorrectly believe that stock option PTEPs must be three months or less for stock options to get the favorable ISO status. That’s not true. You can grant stock options with a 6-year PTEP and still have ISO status.

The rule is that stock options just have to be exercised within three months to get ISO status. If someone exercises after 100 days post-termination then the stock options just automatically flip to NSOs.

Having worked at a company that granted long PTEPs, this can be an awesome benefit that employees love, but…it 1) adds a lot of administrative burden and 2) it can add a lot of dilution overhang which obviously means everyone’s slice of the pie shrinks (~50%+ of people don’t exercise stock options when they leave, but if you have a long PTEP then they don’t have to).

What’s Wrong:

If the plan says the option is expired, then it can’t be exercised (regardless of what the system says). The employee thought they owned shares when they exercised, but they legally own nothing.

The company just owes the employee their money back…

The issue may have been caused by a company admin mistake, but the stock option plan is clear, which the employee signed, so the company isn’t typically obligated to do anything (but perhaps legally questionable if the exercise was accepted by the company).

The Fix:

This is different than the first two mistakes because it is kind of the employee’s fault no matter what. They signed an agreement that they only had so much time to exercise options after terminating. An admin mistake doesn’t change that.

Most frequently I just see the company refund their exercise price and undo the “shares” in the system.

But some companies feel bad and try to do something (cash settlement, advisor agreement to regrant shares, etc).

Mistake #4: Waiting to Fix Cap Table Issues

For some issues, it doesn’t matter if you wait to clean them up. Cap table-related issues are not one of those…The longer you wait, the worse (and more expensive) they usually get.

And cap table issues always surface at the most inconvenient moments:

• During M&A diligence because potential acquirers are poking holes in everything.

• During financing diligence when VCs are making sure they understand who owns what.

• During IPO prep while legal is validating ownership before going public

• When an employee asks some questions and someone actually digs into the details.

Don’t wait. Make sure your cap table is clean now. If it isn’t, spend the time cleaning up the issues now. It will only get more expensive, the longer you wait. I have seen some big purchase price adjustments in acquisitions because of issues discovered here…

The Cap Table Checklist

Here are the additional checklist items you need to implement so your cap table doesn’t delay/kill a fundraising round, an acquisition, or an IPO. It will also save you lots of money on legal cleanup fees and embarrassment with your board...

1. Board Approvals or Bust: No approval, no grant. Make sure you have a good process for double-checking the grants that should get included (HR, finance, legal, and CEO final review). I use AI now for this…”Claude, compare approved grants from board meeting to pending grant list to new grants in Carta.”

2. Fresh Valuations: Set calendar reminders on month 10 or 11 to email your 409A advisors to kick off the process. And make sure that your finance leader who is in the know about fundraising and M&A knows the rules around 409A valuation timing.

3. Expiration Tracking: Two things I do for this, 1) get a good admin to set a regular cadence for updating the equity admin tool for terms and 2) monthly/quarterly reconcile all terms per HRIS with all terms in the equity tool.

4. Good Equity Admin Tool – this will make your life a lot easier.

5. Monthly/Quarterly Reconciliation – Reconcile the cap table with board minutes and HR records. “We have a new hire from 6 months ago that hasn’t received a grant yet”

6. 83(b) Tracking for Early Exercises / Restricted Stock: Something that always comes up in diligence is if proper 83(b) tracking has been performed. Yes, it’s the employee’s responsibility, but companies should keep a record of the filing too in order to avoid issues with the employee and potential liabilities.

7. Track Early Exercise Terminations: I have also seen companies just forget about folks who early exercised options and then leave before their full vesting period. If the company doesn’t repurchase those shares then they may forfeit their right to repurchase them and then the employee gets to keep the shares even though they didn’t vest.

8. Track Stock Option Pool: I show the remaining pool and 12-month grant forecast to the board every time we get new grants approved. It’s easy to add and keeps everyone aligned on dilution and the remaining pool available.

9. ISO vs NSO Classification: Make sure your admin and equity tool handles ISO/NSO rules correctly. For example, contractors/advisors can’t receive ISOs, large grants can run into ISO limits, and post-termination exercise periods can change the tax treatment. Get this wrong and the company will report and pay the wrong amount of taxes.

10. Rule 701 Tracking: If you don’t track this and apply exemptions when appropriate (like Reg D or 4(a)(2)) then you can accidentally cause a ton of work and broader disclosures of financials…Make sure your legal firm (or someone) is tracking this.

Final Thoughts

A poorly run cap table will cost you lots of money in legal fees, embarrassment with the CEO and board, piss off a lot of employees, and waste a lot of time for many people.

Lawyers can paper some mistakes away (“Section 204” has saved me from a few embarrassments), but a lot of equity mistakes are not easily fixed and cost a lot of money.

Make sure your cap table is clean now before you are in diligence of some kind and it pops up at the worst possible time. These things take time to fix…

Footnotes:

• Join me and attend Rillion’s 2026 Finance AI Report webinar to learn how other CFOs are implementing AI

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

*Nothing in this article constitutes legal, tax, or investment advice. I am not a lawyer or tax accountant. The above article is based on my personal experience and actions that I have seen performed. Consult with your legal team on what to do based on your circumstances…

Sales tax is coming to California (January 1, 2027)! This is bad news for all of us tech folks…

• A high tax rate between 7.25 and 10%+ (depending on jurisdiction)

• Your CA-based customers now get hit with sales tax

• CA-based companies have a big increase to all their software spend

More than 3,000 businesses use Numeral to get sales tax right. Mess up sales tax and you will end up with a huge liability. Get a free sales tax analysis 👇

Get Free Tax Analysis

SpaceX Stock Price Tanks

SpaceX IPO’d last month at a $1.7 trillion valuation ($135/share) and briefly touched $3 trillion ($226/share) a few days later on June 16th, which was the same day they announced their $60 billion acquisition of Cursor.

SpaceX stock has been falling ever since…down 50% in the past 45 days.

Guess who is cheering as SpaceX stock price crashes?

Cursor investors and employees…

Wait…but Cursor is being acquired by them. Why would they be happy?

Because the deal hasn’t officially closed yet (expected this quarter) and based on the deal terms, Cursor is benefiting as the stock price falls.

Why SpaceX’s $60B Acquisition of Cursor Is Getting A Lot More Expensive

April 2026: SpaceX’s Call Option to Buy Cursor:

A lot of the diligence and pricing was done prior to the acquisition being announced in June because SpaceX signed a call option agreement for the exclusive right to buy Cursor for $60B if they decide to move forward.

A call option agreement like this is pretty unusual. The option gave SpaceX time to complete its IPO and evaluate the acquisition before making its final decision.

The option wasn’t free for SpaceX. There was essentially a $10B breakup fee if SpaceX called it off…

June 16, 2026: Exercising the Call Option:

On June 16th, SpaceX announced the exercise of the option and entered into a definitive merger agreement with Cursor. At this point, a lot of the acquisition work was already done as part of the call option agreement.

But the deal doesn’t “close” when you enter into a definitive merger agreement. SpaceX said that they expect the deal to close in Q3’26 (so in the next couple of months). The primary reason for the gap between definitive merger agreement and close is the antitrust stuff (like HSR).

Buyer vs Seller Risk

The acquisition price wasn’t $60B in a suitcase full of cash. It was $60 billion of SpaceX stock.

But $60B of stock as of when? This point matters a lot…

There are two primary ways stock deals can be structured:

1. Fixed Exchange Ratio - The number of buyer shares is fixed, so the dollar value rises or falls with the buyer’s stock price. (Risk is on the seller)

2. Floating Exchange Ratio - The dollar value is fixed, so the number of buyer shares rises or falls with the buyer’s stock price. (Risk is on the buyer)

Fixed is by far the most common deal structure. In fact, floating exchange ratios make the most sense when the buyer is public with an actively traded stock.

Also, when floating exchange ratios are used, they rarely come without a “collar.” A collar limits how much the exchange ratio can adjust when the buyer’s stock price moves up or down. Without a collar, if the buyer’s stock price crashes, the buyer could have to create an unlimited amount of dilution to settle the acquisition.

SpaceX agreed to buy Cursor for $60B using an uncollared floating exchange ratio based on the volume-weighted average closing stock price of the seven days prior to the deal closing.

Remember, the deal was announced in June, but it isn’t expected to close until sometime this quarter (hopefully). While Cursor knows that they will be getting $60B worth of SpaceX stock at closing, SpaceX still doesn’t know how much dilution the acquisition will create for them…

Date TBD: Settling $60 Billion Acquisition Price

I actually got the transcripts from SpaceX’s recent board meeting…

• Elon: Buying Cursor for $60B is a good bet. It will accelerate our AI vision.

• Board: It’s a lot of money, but I guess a small % of your market cap

• Elon: Exactly! This $80B acquisition will be the most important $100B we have ever spent.

• Board: Wait…I thought it was $60B?

• Elon: Look, if we don’t spend $125B buying Cursor then we will lose in AI

*Obviously the above is fictional, but it’s what I imagine everyone is thinking during SpaceX’s collapsing stock price.

SpaceX’s stock price has fallen by ~52% since the deal was announced at SpaceX’s peak valuation. So the floating exchange ratio for the $60B of stock is now 2x more expensive from a dilution standpoint since the deal was announced. And probably feels like they are now paying ~$125B for Cursor…

The acquisition still hasn’t closed yet so maybe the stock could recover a bit but it could also keep falling…

Here is the potential vicious cycle that can happen:

1. SpaceX stock price drops (for whatever reason)

2. SpaceX effectively pays more to acquire Cursor (more dilution)

3. Stock market drops (has been happening right now) so investors believe Cursor might be worth less than $60B

4. SpaceX stock price drops further because it is locked into overpaying for Cursor (or there is a huge breakup fee) so the valuation is dinged again

5. SpaceX pays even more to acquire Cursor as stock price falls

6. Repeat…

A floating exchange ratio creates buyer risk that could spin out of control.

Elon Hates It; Cursor Loves It

Elon and the SpaceX team hate that the stock price is falling for obvious reasons…but all else being equal, Cursor equity holders are silently cheering.

Why?

If nothing material has changed at SpaceX, then it is still the same company with grand ambitions to be “more valuable than Earth”. But Cursor would rather receive more shares at today’s much lower valuation. If the deal were priced today, Cursor would receive roughly twice as many shares as it would have at SpaceX’s June 16 peak.

Cursor folks are just praying that it doesn’t recover before the acquisition closes…

Fixed cash/exchange ratios are the most common, but as you can see below, if your stock price increases, then the fixed ratio works against you. If Google acquired Wiz in a similar structure as SpaceX<>Cursor, then they would have effectively paid $16B less because Google’s stock price rose 93% between announcement and the deal closing (so they would have had to issue almost half the number of shares than at the announcement date).

Buy Low. Sell High

Companies want to buy low and sell high with their own stock:

• Use equity (e.g. employee equity and acquisitions) when the stock price is overvalued

• Use cash when the stock price is undervalued

This applies when issuing stock-based comp to employees, performing buybacks, and buying companies. But that is hard to time right, especially when you have a floating exchange ratio and a volatile post-IPO stock…

So as long as nothing really changes with SpaceX’s business and its stock price remains deflated through the close, Cursor investors and employees are really happy since they would get a much better price with more room for upside.

Footnotes:

• Get a Free Sales Tax Analysis - Sales tax on software is coming to California so use my friends (and sponsors :) from Numeral to get ready.

• Want to sponsor? shoot an email to onlycfo@onlycfo.io

Subscribe now

*Nothing in this post should be considered tax, legal, or investment advice. Educational purposes only. Consult an investment and/or tax advisor.

Subscribe now

Domo has been one of the worst performing software companies in the public markets for a long time. They have one of the lowest revenue multiples driven by zero revenue growth, breakeven FCF margins, and a long history of burning a lot of money.

Domo has been contemplating a sale for a while given their broken economics, growing debt, and dwindling cash balance. They hired a banker earlier this year to formally find an acquirer. When they tripped their debt covenant last quarter the lender put a clock on them getting acquired. The lenders basically said, “Sign a purchase agreement by July 31st and close by November. Or else…”

Well, this week Domo finally convinced someone to acquire them (at least part of them). Progress Software, a public company, has agreed to pay $400M for Domo’s assets.

Unusual Acquisition

Domo is selling basically all of their assets (software, customers, IP, etc) in a $400M asset sale. Not a typical equity sale.

Why structure it this way?

Domo is essentially creating a SPAC-style holding company that will have ~$246M of cash (after repaying debt and transaction expenses) that they can use to buy companies with.

But also, there are some attractive tax benefits by structuring it this way…

Losing Money Was Actually Domo’s Plan All Along!

One of my all-time favorite tweets comes from investor Cathie Wood (CEO of ARK Invest) where she basically says, “due to our bad stock trading we have lots of losses that can offset capital gains for many years!”

Tax loss harvesting can be part of a legit strategy, but it is a very funny thing to talk about when her funds were down so hard relative to the market.

Maybe losing lots of money was part of Domo’s grand plan?

Because it’s an asset sale, Domo will retain their net operating losses (NOLs). Domo expects to close the deal with ~$900M+ in NOLs that can offset future taxable income (if they ever have any). They currently have ~$1.3B in NOLs, but some of those will be used to offset gains from selling assets in this transaction.

So now Domo has a decent pile of cash (~$246M) and a public company shell to go acquire a company (similar to a SPAC).

The difference with a SPAC is that Domo will have a pretty massive NOL asset. In theory, they can go buy a profitable business and offset profits for a really long time.

What is $900M of NOLs worth?

Hint: Not $900M

That represents the total losses that can offset future profits.

With a 21% federal corporate tax rate, it is at most $189M (assuming a $900M NOL).

Domo also has state-level NOLs. Their state NOLs are a bit higher than federal NOLs with an implied average tax rate of ~5%. If we assume they have $1B of state NOLs after the transaction, then they potentially have up to $50M of tax savings.

There are two potential problems with the theoretical tax asset that Domo’s shell company owns:

1. Certain NOL rules, if triggered, could partially or completely eliminate NOLs (more on this below)

2. This one is important…the company must actually generate profits for it to matter.

NOL Expirations:

There are two types of NOLs that companies must track because when and how they can be used are very different:

• Pre-2018: NOLs generated before 2018 expire after 20 years

• Post-2017: NOLs generated after 2017 never expire, but can only offset 80% of income each year.

NOL Limitations (Section 382):

Section 382 establishes thresholds that can significantly limit NOLs. Domo’s structure is supposed to help preserve them.

• Trigger? One or more 5% shareholders collectively increase their ownership by more than 50 percentage points over their lowest ownership levels during the prior 3 years. (remember these thresholds because it’s important to something else they implemented)

• Limitation? If the trigger is met, then the amount of NOLs that can offset income each year is significantly limited. If another company bought control of Domo’s shell company (assumed value is $246M) then that company could only use $9.3M of its NOLs each year ($246M * 3.77%). In other words, it would take 97 years to use their NOLs. A lot of Domo’s NOLs were built pre-2018 so those will eventually expire and the remaining NOLs can eventually be used but the present value of them wouldn’t be worth nearly as much.

Cooking Up a “Poison Pill”

Domo announced a “Tax Benefits Preservation Plan” at the same time the asset sale was announced.

The purpose? To make sure no one blows up their NOLs and severely limits their usability.

What is it? It’s a type of “Poison Pill” that essentially stops investors from obtaining more than 4.9% of the shell company’s stock. This poison pill is a right given to every shareholder to purchase Domo stock worth $35 for $17.50. Everyone gets that right except the investor crossing 4.9%. So everyone benefits except them. In practice, once this is implemented, no investor would acquire 5% because they would essentially just be transferring money to all other shareholders. The board can grant an exemption to the poison pill, though.

While the poison pill was written up to protect NOLs (valid reason), it has the side benefit of preventing someone from buying it for the cash and/or public company shell.

What’s Next For “Domo”?

Domo is losing its name and will change its ticker on the stock exchange since all Domo branding is now owned by someone else.

Domo stock jumped 25% on the acquisition news…

Wait…the company is just a shell holding cash and valuable NOLs. Why isn’t it trading at least at the cash per share of $4.84?

It is currently 18% below the expected cash per share (not even considering NOL potential).

It’s common for a transaction like this to trade below cash per share:

• Management risk: Stockholders are relying on someone who burned through $1B of cash to build a bloated business that never made money so why should they expect them to be able to buy a business and run it well?

• Actual cash per share is just an estimate and could change by the time of closing because of purchase price adjustments, transaction expenses, tax stuff, etc

• Still public: Domo’s shell will still be public and will have operating costs of a shell company (legal, tax, management fees, etc) and will have expenses to try and find a company to buy.

• Deal risk that it never actually closes. Risk here seems pretty small.

I don’t know what the Domo shell will buy, but it will have to be pretty small…What can you buy with $246M of cash on the balance sheet? The obvious answer is a broken company like Domo…so if you want something good (growing and/or profitable) it will have to be pretty small. Good chance they take on some debt to buy something bigger, but even so, they still won’t be able to buy something really worthy of the public markets right now with the leverage that a lender would give them.

And remember, they will still be operating as a public company with all the costs that go along with it, which is difficult for a very small company to absorb.

The deal won’t close for another few months, but in the meantime Josh James (Domo CEO) and the board will be on the hunt for what to do with the cash. Become the next MicroStrategy and go all-in on Bitcoin? Buy broken AI businesses and scale them (version of Bending Spoons)? Build data centers? Or just burn more cash and drive the stock price further down?

Goodbye Domo….And I look forward to writing about whatever the shell company does next :)

Footnotes:

• Want to sponsor? shoot an email to onlycfo@onlycfo.io

• Subscribe for more fun and share with your friends

Subscribe now

*Nothing in this post should be considered tax, legal, or investment advice. Educational purposes only. Consult an investment and/or tax advisor.

Subscribe now

Last week, Trump Media (public company that owns Truth Social) announced “Truth API”, which will give customers access to the 10 most “influential” Truth Social accounts in milliseconds, which is faster than everyone else will get the posts.

• The Price? reportedly as high as $100,000 per month…

• The Target Customers? Hedge funds, banks and big trading firms that are dealing with billions of dollars

• The Pitch? Simple…Trump posts crazy stuff that moves markets in major ways so if these firms can get the posts faster, their automated trading algorithms can buy/sell faster (which matters a lot). Also, if they don’t buy it then they are going to be behind other traders (which will cost them lots of money).

Trump’s post (aka “Truth”) about pausing tariffs last year would probably have paid back the $1.2M annual price tag by 100x+ in just a couple of hours for many of these trading firms…

At 1:18 pm on April 9, 2025, Trump posted about a tariff pause and the stock market immediately jumped by ~7-9%. The Nasdaq finished the day 12.2% higher and the S&P 500 9.5% higher.

Imagine being a trading firm not paying to get this info slightly sooner and missing out on one of the largest single-day gains in history.

Obviously, this wouldn’t be for normal retail traders because most investors can’t act on the news (buy/sell) fast enough for the timing difference to matter. But the shops that have spent millions of dollars to automate trades based on the speed of information have to buy this…there is almost no choice.

I am not a lawyer, but apparently there is nothing illegal about this… It is not insider trading, and apparently the President is exempt from the conflict of interest laws that would have prohibited other government officials from doing the same thing.

Does it pass my general ethics sniff test? obviously not…

Unprecedented Levels of Grift

Truth Social isn’t the first social media app to sell faster access to posts, but…

• Insane price: $100,000 per month for faster access to the top 10 Truth Social accounts (really everyone just cares about the one that actually moves markets on a regular basis). This is ~100,000%+ higher than what would normally be charged by any other similar service on a per-post basis.

• It’s for posts from the President of the U.S.: Many of Trump’s posts move markets in major ways and he posts them first on Truth Social.

• Trump owns 41% of Truth Social: More frequent (and market-moving) posting by the president on Truth Social can make him a lot richer because more people will be pushed to buy these $100,000 subscriptions. Because of this financial relationship, Trump obviously financially benefits whenever he posts market-moving things…

And even crazier is that this “Truth API” will probably make up the majority of the company’s revenue by next quarter.

Trump Media only generated $871K in Q1, or $290K a month. What?!? lol. It would just take three customers at the $100K price tag for it to become the majority of its revenue.

Remember, this company has a $2.7 billion enterprise value (once nearly $10 billion)…off of basically no revenue. Nearly the entire valuation is tied to the President of the U.S. and this new product is doubling down on that. There is a limited amount of time (2.5 years) to milk Trump’s presidential status and they are shamelessly going for it.

Is “Truth API” ARR (recurring revenue)?

Well, it’s a monthly/annual subscription that is probably expected to renew for at least a couple of years. But unless Trump gets a 3rd presidential term 🤣…basically everyone will churn in about 2.5 years.

Funny enough though…I think a lot of software companies are in a similar position (ie revenue is no longer very durable) but they don’t have as clear of a churn date.

Definitive churn in 2.5 years breaks the objective of “ARR”. ARR was magical because of its durability. The business model looks much different if “ARR” only lasts a couple of years. LTV metrics will look amazing for 2.5 years…until a wall of churn hits.

Rationally, then, investors would only value this incremental revenue potential based on the temporary FCF increase from it for the next couple of years. But…that would assume whoever owns Trump Media is “rational”.

*Some reports say they are offering discounted prices of $60K per month if customers commit to at least 3 years. I wonder why…🤔. Oh yeah…the only reason people will buy the subscription will no longer matter in 2.5 years.

What Counts as Insider Trading?

Insider trading occurs when three things happen:

1. The trader has material, nonpublic information about a security.

2. The trader buys or sells securities while aware of it.

3. The information was obtained or disclosed through a breach of a fiduciary duty, confidentiality obligation, or similar duty of trust.

Paying for faster access to information is not necessarily insider trading. For example, Bloomberg Terminals, which cost a lot of money, provide a speed advantage, but that doesn’t trip insider trading rules. People are just paying for a faster connection.

Ok, What About Regulation FD?

Regulation FD (“fair disclosure”) is 26 years old and basically says companies must simultaneously disclose information to the public. Meant to protect retail investors from companies sharing material information with analysts in advance of everyone else.

But Reg FD doesn’t apply here because:

• The information Trump is posting about is not about Trump Media.
  Reg FD governs disclosures of material nonpublic information about that company. Trump’s posts about tariffs, wars, interest rates or foreign policy may move many securities, etc

• The API accelerates delivery of published posts but does not provide unpublished information.
  The API feed will deliver posts faster than ordinary push notifications. If the post is already publicly posted and the API just transmits it faster, there is no nonpublic information to regulate.

TLDR: the laws did not contemplate this insane situation… or at least assumed lawmakers would never need to make something like this illegal.

Takeaway: Be Honest and Ethical

I don’t know all the facts on this Truth Social API subscription, but it certainly looks very ethically questionable based on the facts we have (even if not illegal) - creates information asymmetry with retail investors and creates a crazy financial incentive for the U.S. president.

My reminder for business leaders: perform the front-page newspaper ethics test:

Would you be comfortable with your decision if SEC lawyers, your board, your mom, etc. knew about it?

Whether it’s questionable ARR definitions, manipulating timing of customer churn to look better in fundraising, not being honest about potential product incidents in due diligence, etc….

Do a front-page newspaper test and make sure your decisions will pass it.

Footnotes:

• Free month-end close checklist tool: Ditch Excel or expensive tools. Check out this close tool I helped design. Join the waitlist!

• Want to sponsor? shoot an email to onlycfo@onlycfo.io

*Nothing in this post should be considered tax, legal, or investment advice. Educational purposes only. Consult an investment and/or tax advisor.

1. Every parent of an eligible child should open up an account (it’s free). Even if a child does not qualify for the free $1,000 government contribution, there are still meaningful benefits for all other children under 18.

2. Every company should likely create a “Trump Account contribution program”

If you are a CFO, then read below and figure out how to start getting it set up. If you are not in charge of benefits, then send this article to your HR team and/or CFO and tell them they need to implement it :)

Share

*Put your politics aside and get over it being called a “Trump Account”. The program has huge tax benefits and can significantly help your kids. Every U.S. citizen and company based in the U.S. needs to understand this.

Who Benefits From Trump Accounts?

These accounts are early childhood savings vehicles to help kids learn about the value of investing and save for retirement.

• Who? Anyone <18 years old with a social security number (after 18 typical traditional IRA restrictions apply).

• Amount? Total of $5,000 per year (including employer contributions) can be contributed to each child’s account.

• Investments? Limited to low-cost mutual funds and ETFs that track broad indexes mostly composed of U.S. companies.

• Withdrawals? Prohibited until the year the child turns 18 years old and then IRA rules apply (10% additional tax on early distributions with limited exemptions like first-time home purchase, education expenses, etc)

• Free $1,000? Qualifying U.S. citizen born between 2025 and 2028 can receive $1,000 from the government (does not count toward the $5,000 per year limit)

• Taxes? All gains, interest, dividends, etc are tax-deferred (only taxed when withdrawn).

Why Employers Need to Offer It

All the above benefits are great, but one of the biggest potential benefits comes from your employer.

There are three things a company can add some of this benefit (all companies should probably at least do #1 and #2):

1. Enable after-tax payroll deduction which just helps employees automatically invest part of their regular payroll into Trump Accounts. This wouldn’t impact the employer $2,500 limit but would count toward the total $5,000 limit. No tax advantages, but potentially adds a tiny bit of convenience for employees if it helps streamline deposits and limit tracking.

2. Enable employees to contribute pre-tax dollars up to $2,500 to a dependent’s Trump Account. This would reduce their taxable income and save taxes.

3. The company can contribute up to $2,500 per employee which is tax-deductible to the employer and tax-free to the employee.

💡 Note: The combined limit of #2 and #3 is $2,500 per employee (not per child). For example, if the company contributes $1,000, the employee can contribute only another $1,500 through pre-tax salary reduction. The employee could then contribute another $2,500 with after-tax dollars (#1) to reach the child’s overall $5,000 annual limit.

Obviously #3 (company contributions) can add a lot of new expenses for a company, but simply adding the plan and allowing employees to contribute pre-tax dollars (#2) saves employees on their marginal federal income-tax rate.

Pre-Tax Contributions Example

Let’s say I have a household income of $150K and I am in the 22% marginal federal income-tax bracket (I am married filing jointly). If my employer offers this benefit then I can reduce my taxable income up to $2,500 per year and give those dollars to my children’s retirement.

Instead of giving the IRS $550/year (22% * $2,500) you can contribute more to your children’s retirement or you can just save that amount in taxes if you plan to contribute $5K either way. Based on compounding returns in the U.S. stock market (assuming a reasonable 8% growth per year), those tax savings will grow to nearly $0.6M (or about $100K in today’s dollars if inflation adjusted) by the time the child is 60.

So instead of giving the IRS $9,900 over the first 18 years of your kid’s life ($550 * 18 years) there will be an additional ~$600K benefit by age 60 because of the pre-tax contribution benefit.

*If you use the 10.5% annual return that the Trump Account website uses then the tax saving alone would grow to $1.9M while each child’s account would grow to $18M by the time they are 60. Very generous assumption, but still…power of compounding is incredible.

Obviously if your employer is willing to just fund employees’ children’s Trump Accounts then that is even better for employees, but many companies won’t want to pay an additional $2,500/employee so this option is a major advantage for employees versus those that do nothing.

Process & Cost to Companies?

CFO: We are trying to cut costs so we can’t add more employee benefits like this

Wrong. Companies can add the program for just a little incremental cost that still has a large tax advantage for the employee.

The Department of Labor confirmed last month that Trump Accounts should not be subject to ERISA. That’s a big deal. Company 401(k)s, for example, are subject to ERISA and have a lot more additional documentation, reporting, audits, internal communications, etc.

Below are the main requirements to get it set up:

So maybe a couple thousand dollars to create the written plan and amend your existing cafeteria plan. And then your benefits provider will charge an additional small per participant fee.

Fairly immaterial cost for a material potential benefit.

Other Important Notes

• Tax-deferred vs Tax-Free: These accounts are retirement savings vehicles (IRAs) so eventually kids will pay taxes on gains on withdrawals at their tax rate at the time of withdrawal

• Money belongs to kid: The money is the property of the kid when it goes into the account. Parents can’t redirect money to another child like a 529 plan

• Money is locked until the year the child turns 18: There is no hardship exemption or any way to access the money before the kid turns 18. Don’t contribute if you think you will need the money before then

• Employees need to set up the accounts themselves: Employees have to set up their kids’ accounts and then provide that info to the company in order to participate in the program. Setup is really easy though…

• Need to track contribution limits: Someone who changes jobs or receives contributions from multiple employers must ensure total contributions do not exceed the $2,500 annual per-employee limit.

• Employers Have Contribution Options: Examples include, $1,500 funded for a new baby or adoption, employer match up to $1,000, flat dollar contribution per year, etc.

Final Thoughts

A company with a Trump Account Contribution program is a significant benefit for employees. And it will be a big negative in recruiting if you don’t have one.

I have heard many people (and even some companies) say they won’t sign up because Trump’s name is attached to it… Let me be clear, that is stupid. It’s a great benefit that will hopefully teach kids the value of investing while also giving some great tax advantages.

It’s also pretty cool that Grandma, Grandpa, or a friend can easily contribute to a child’s retirement account (scan a QR code and send money).

Set up accounts for your child and tell your company that they should set up the program as well!

Footnotes:

• Sponsors: Email me at onlycfo@onlycfo.io for sponsorship opportunities.

• Subscribe and tell your friends

Subscribe now

*Nothing in this post should be considered tax, legal, or investment advice. Educational purposes only. Consult an investment and/or tax advisor.

This will have a pretty massive impact on a lot of tech companies.

1. Vendor Spend: If your HQ is in California, then chances are you are paying 0% in sales tax on all your software/AI spend. But starting next year, most software/AI spend will be at least 7.25% higher than you were expecting.

2. Company Invoices: Starting next year, your invoices to California customers (tech companies sell to a significant number of CA headquartered companies) will be at least 7.25% higher.

That’s a significant price increase for both you and your customers!

Does this apply to all software? And…AI token spend?

The change applies to “prewritten computer software” (ie SaaS) transferred electronically or accessed remotely. But it excludes several categories, including “custom computer software” and “digital infrastructure”. The bill defines “digital infrastructure” as certain cloud-based services that let users create, deploy, scale, or run their own software (eg AWS, Azure, etc).

You will want to confirm the category your SKUs fall into. Especially as we get more definitions from California.

This will capture your Claude/ChatGPT/etc spend that is currently at 0% if you are in California. So your fastest growing (and maybe your largest) vendor spend is getting at least 7.25% more expensive next year. Ouch

FP&A Team Takeaway:

Budgeting: Make sure to add these additional costs to your budgets. This might be a material surprise cost in 2027. Pro tip: keep reading for how you might be able to reduce this sales tax liability.

Churn Impact: You also need to consider if/how this will impact your customer churn forecasts. This additional expense may be the breaking point for some of your customers.

What I am doing: Create a list of all your customers that will be impacted. Make sure to communicate the change with sales and customer success. And then consider the impact of any planned price increases next year. Maybe you want to keep prices more flat for those customers next year so it decreases churn?

Accounting Team Takeaway:

Collecting Sales Tax: If you have any decent sales tax software then you shouldn’t have to do anything with one important caveat…. I know some companies that don’t turn on states that don’t collect sales tax so they don’t have to pay additional software and filing fees. Make sure California is turned on if you have nexus there!

Do I have Nexus? Build a good nexus tracking process. I was once at a company that only updated it quarterly and then we sent out a ~$250K invoice that shouldn’t have included sales tax but didn’t because we hadn’t refreshed our nexus yet. We ended up eating about $18K in sales tax because we didn’t want to go back to the customer once we discovered it. More on this below.

What You Should Know About Sales Tax

Do I have nexus?

Nexus: level of connection between a business and a taxing jurisdiction that triggers a sales tax collection obligation.

There are two ways a company can establish nexus:

1. Physical presence. Typically gets triggered when you hire an employee in the state or local jurisdiction. Contractors and large amounts of inventory can also trigger it.

2. Economic nexus. Triggered when a certain $ level of sales and/or number of transactions to customers in the state. Below is a great visual for these different thresholds

California’s economic nexus threshold is $500K of sales in the current or prior calendar year, with no transaction-count threshold. So if you are a software company then you will trip this quickly.

Sales vs Use Tax

There are two primary types of indirect taxes in the U.S. Both are taxes on the same thing, but differ on who is responsible for paying it:

• Sales Tax: Collected by and responsibility of the seller because of their nexus in the state.

• Use Tax: Responsibility of the customer. Seller doesn’t have nexus (or at least didn’t charge sales tax) but the goods/services are subject to sales/use tax.

Idea is you can’t circumvent the tax by using out-of-state sellers to avoid the tax.

So in theory, the customer should be paying the tax either way so it should be included in total expense forecasting.

Where is Software Taxable?

Today, there are over 20 states in the United States that tax software. Many countries also tax software and digital goods from the very first sale. States and jurisdictions are continually changing their stance (like California) so it’s important to stay up-to-date.

Below is a map of states that tax software (with California starting in 2027)

The Dirty Secret of Many Software Companies

Most tech companies put their California HQ address on all their software purchases. It’s true that they are HQ in California but a significant amount of usage happens outside of California (particularly remote companies). It was also very convenient since they paid $0 in sales taxes in California.

But now California is taxing software, we are going to see many companies update their contracts with vendors…

Companies are going to reach out to their vendors to update their address or they will provide a “multiple points of use” (MPU) certification which states that usage happens in multiple places so it shouldn’t all be taxed at one address (this shifts sales tax responsibility to the buyer).

What About International Sales?

Companies are selling internationally a lot sooner today. Other countries have other indirect taxes that are paid by the customer like the value-added tax (VAT) or Goods and Services Tax (GST).

170+ countries have a value-added tax (VAT) regime with more than 80 applying VAT to digital goods and services transactions.

To determine whether VAT applies on a sale of your product or service, there are three main factors to understand:

1. Your customer’s location

2. The taxability of your product in that country

3. Your customer’s VAT registration status.

Final Thoughts

California now taxing software will be a big deal for a lot of companies. Plan accordingly.

If you don’t have a good process for sales/use tax, then you could end up with a huge liability that can derail fundraising discussions, a potential acquisition, or an IPO.

When the seller has nexus, it is generally their responsibility to collect and pay sales tax. Going back to your customers 2 years later and asking for sales tax is very painful. Ask me how I know…

Don’t wait to figure out sales tax. It will be much more painful later.

Footnotes:

• Email me at onlycfo@onlycfo.io for sponsorship opportunities.

• Subscribe and tell your friends

Subscribe now

*Nothing in this post should be considered tax, legal, or investment advice. Educational purposes only. Consult a sales tax advisor.

AI agents in finance are really powerful when they have the right context, controls, and operating environment.

I (OnlyCFO) have been working closely with Brex for over 2 years, and what they’ve built for agentic finance (AF) is incredible. With Brex, agents handle all the tedious stuff, like expense reports, policy enforcement, and month-end close, so your team doesn’t have to. Check out Brex AF!

Check out Brex AF

OnlyCFO’s Valuation

Headline: The OnlyCFO newsletter hits 39,000 subscribers and raises $20 million at a $100 million valuation!

While the above isn’t real (it’s probably worth a lot more 🤣), we see these types of headlines all the time.

• What does “valuation” even mean?

• How do private valuations differ from public companies?

• How can fundraising announcements be deceiving?

What Does “Valuation” Mean?

In public markets, “valuation” usually means one of two things:

1. Market cap

2. Enterprise value

1. Market Cap

When people say “valuation” they could be referring to a few things, so first you need to understand some terms and definitions:

Market Capitalization (aka market cap): is the total value of a publicly traded company’s outstanding shares.

Market Cap = stock price * number of shares outstanding

SpaceX Market Cap

Stock price is straightforward. It’s the price listed on the stock market. SpaceX closed on June 25th at $153.

Outstanding shares is a bit more complicated. Outstanding shares are only disclosed quarterly (on 10Q/10Ks) unless there is a material event that requires additional disclosure. Additional shares from an IPO are disclosed in an S-1 and the exercise of the greenshoe is disclosed in a subsequent 8-K, but things like employee exercises and immaterial changes only get updated quarterly.

2. Enterprise Value

Enterprise value (EV): is more comprehensive than market cap. EV includes the market cap of a company but also adds debt and subtracts cash. EV is used for operating valuation multiples like EV/Revenue and EV/EBITDA because it accounts for capital structure.

EV = Market Cap + Debt - Cash

To continue the SpaceX example, their EV would be lower than their market cap, which is common, because they are in a positive net cash position (cash > debt)

Wait….Why would debt make your company more valuable and cash makes you less valuable? That seems like a mistake, right?

Enterprise value is a financing calculation. It represents the amount someone would theoretically pay to acquire the company. An acquirer would have to pay those who own equity (represented by market cap) plus everyone who has loaned it money (lenders). Once you acquire the company though you get the company’s cash so you can use that to pay off the debt. That’s why you add debt and subtract cash.

Example: Imagine two companies with a market cap of $1B. Company #1 has $1B of cash and Company #2 has $0 of cash. The company with $1B of cash is valued just on their cash level. Someone could theoretically buy it for free. since they get their $1B of cash after they acquire it. While the company with $0 of cash has built something worth $1B so you will have to pay $1B for it.

In reality though, acquiring a public company outright will almost always be higher than the current EV because there will be a large premium paid to be able to acquire all the shares.

Valuations Can Rise While Stock Prices Fall

A company’s “valuation” can increase while shareholders actually lose money. This happens when your slice of the pie shrinks faster than the total pie grows. In other words, dilution eats away stock returns faster than the valuation increases.

Zoom is a good example of this…

Zoom’s stock price is flat since May 2019 (shortly after the IPO). But during that time the market cap went from $18.9B to $24B over that period of time (a 26% increase)

Wait…so why is the stock price flat if the market cap is up?!?

Dilution.

Valuation increased slower than dilution increased which was a huge drag on stock price. If it wasn’t for dilution, Zoom’s stock price would be 26% higher.

What Does a Falling EV Mean When Market Cap Increases?

Zoom’s cash position has changed materially since the IPO. Immediately following the IPO, Zoom had $0.7B and as of April 30, 2026, Zoom had $7.7B in cash and investments….

So while the market cap went from $19B to $24B (26% increase), the enterprise value actually decreased because of its net cash position today versus 7 years ago.

$24B market cap - $7.7B of cash + $0 of debt = $16.3B EV

So it is actually cheaper to acquire Zoom today than 7 years ago. While the market cap increased, the underlying business is deemed to be worth less today by investors. EV shows this by taking out the cash and debt that the business has.

It’s why EV is used in financial metrics like EV/revenue.

Private Company Valuations

When a private company says something like “OnlyCFO newsletter raised at a $100 million valuation” it’s similar to market cap but inflates valuation in almost all cases.

Headline Valuation = recent price per share * fully diluted shares

This definition looks the same as market cap but the nuances can be significant

• Price per share: This is the price the recent financing was at, but it’s also the terms the recent round was at.

• Fully Diluted Shares: This is outstanding shares + all dilutive securities (unexercised options, available option pool, warrants, etc).

The biggest potential issue is using the recent price per share and applying that to all shares. If a round was done with heavy structure then that creates a lot more value for those shares. Some valuable terms may include:

• Liquidation preferences mean they get paid back some amount before common stockholders get paid anything. 2x liquidation means preferred holders get paid back 2x their investment before anyone else gets anything. That is valuable and would be deceiving then to apply that share price to all shares.

• Participating: They receive their liquidation preference and then also participate in the remaining proceeds as if they had converted to common (double dipping). This is pretty rare to have.

• Seniority: Does the latest round get their liquidation preference first or is it pari passu (equal priority) and gets paid pro-rata?

• Anti-dilution: Protects investors in a future down-round (lower valuation) scenario. They will get more shares if it kicks in.

For example, when you have a liquidation preference then your downside risk is significantly limited.

Liquidation Preference Coverage = Total liquidation preference / ARR

Let’s say VCs invest $500 million into a company at a $30 billion valuation because it has the potential to be a $300 billion company. But the company currently only has $500M of ARR. That is an extremely rich ARR multiple (60x). But…the liquidation preference coverage is just 1x. Most investors will assume that in a worst case scenario the company could sell for 1x its current ARR so they could get their money back while common stockholders would get nothing. That liquidation preference makes the preferred shares a lot more valuable than any of the common shares and the headline valuation of $30 billion a bit misleading.

Final Thoughts

Theoretically, I could have my dad invest $1 at a $2 billion “valuation” and say my most recent valuation is $2 billion.

It’s a fact, but it’s obviously not the truth.

It’s important to understand what people mean when they say “valuation.” And if you are an employee at a private company then you should understand what the structure of that recent valuation is so you understand how real it is and what it means for your employee equity.

Footnotes:

• See how Agentic Finance can transform your finance department (today’s sponsor is Brex).

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

AI agents in finance are really powerful when they have the right context, controls, and operating environment.

I (OnlyCFO) have been working closely with Brex for over 2 years, and what they’ve built for agentic finance (AF) is incredible. With Brex, agents handle all the tedious stuff, like expense reports, policy enforcement, and month-end close, so your team doesn’t have to. Check out Brex AF!

Check out Brex AF

Stock Price Performance

Only 7 out of 75 public software companies have a higher stock price today than 5 years ago (peak of software valuations in 2021). Unless you invested in one of the top 3 performers, you underperformed the broader market…

And the biggest losers were really big losers… The bottom 10 all lost >90% of their value. Domo leads the pack at a 97% loss.

IPO Performance

IPOs can be wild rides given the excitement around them and the extremely low float (ie the number of tradable shares).

SpaceX went public last week and saw its stock price increase by ~70% within a few days (a trillion-dollar increase…). But since that peak SpaceX stock has fallen over 20%.

History says that buying on the IPO day (when publicly traded) is a bad investment. The average software IPO was 5% lower six months after the IPO while the broader market was up over 6% over those same time periods…

Biggest IPO Losers

Figma, for example, had a massive 250% day 1 pop (one of the largest in history). Just six months later though Figma was down 79% while QQQ (tech-heavy market ETF) was up 11%…If you invested in Figma on day 1, then you are worse off than the broader market by 90% (green column)

Biggest Winners

Funny enough, the biggest winner (Palantir) didn’t IPO. They went public via a direct listing. Shares slid on the first day, which is very unusual, and then it turned out to be a major AI winner.

Revenue Multiples

Revenue Multiple = Enterprise Value/Revenue.

And “revenue” is either LTM (last 12 months), NTM (next 12 months), or sometimes ARR (which is something in between LTM and NTM).

If revenue multiples increase, then stock price almost always goes up for software companies (because revenue doesn’t typically fall).

But revenue multiples can fall while stock prices increase. This happens when revenue growth outweighs the decline in revenue multiple, which is exactly what every software company has been fighting to do since the sky-high revenue multiples of 2021. AppFolio, for example, had its revenue multiple cut in half, but its stock price is up by 18%. This is really hard to do!

Top 10 Revenue Multiple Changes

Below are the top 10 increases (or smallest decreases) in revenue multiples from 2021 to today. Only two companies actually increased their revenue multiples since 2021… Palantir is obvious, but JFrog surprised me.

Top 10 Revenue Multiple Rank Change

I like to see the trend in relative revenue multiple ranking. In the table below I ranked all software company revenue multiples in 2021 and compared them to the rankings today.

JFrog had the second highest relative revenue multiple change since 2021 (jumping 47 spots) and it now sits in the top 10.

Bottom 10 Revenue Multiple Rank Changes

The biggest revenue multiple losers generally come from the companies that experienced the weakest revenue durability (see next section).

BILL leads the pack here. It’s really hard to recover when your revenue multiple goes from 56x to 1.6x….Most of these companies have been deemed AI losers which helps explain the massive multiple drops.

Growth Endurance

Growth endurance measures the stickiness of your revenue growth over some period of time (usually measured annually).

Top 10 Best Growth Endurance

Below are the companies with the best revenue growth endurance over the past 5 years.

Top 10 Worst Growth Endurance

C3 tops the charts for worst growth endurance at -55%….I don’t really follow the company at all, but it blows my mind that C3 is trading at a 5x revenue multiple with negative revenue growth. I guess people are still grasping onto hope that it has some AI that will magically make them grow again and be profitable.

The higher multiples for Dropbox and Zoom make sense given how profitable they are (and Zoom’s early investment in Anthropic helps too)

Gross Margins

Should gross margins be increasing or decreasing?

All else being equal, higher gross margins is obviously better. Gross margins represent the ceiling of profitability. So we want gross margins high, right?

Well…the counterargument is that if companies are implementing AI in a meaningful way then gross margins will likely come down (at least near-term) since AI is more expensive to run. If the tradeoff truly is slightly lower gross margins for significantly better revenue growth durability, then I will take that trade every single time. But it’s usually not that simple.

Top 10 Gross Margin Increases

Most of the companies below that saw the largest gross margin increases also saw their growth rates decrease the most. When growth rates decline, companies start to prioritize fixing things like low gross margins. It’s also easier to have better gross margins when revenue growth is slow.

Top 10 Gross Margin Decreases

C3 has seen an absolute disaster of gross margin deterioration (falling 33 percentage points). I know they are an “AI” company, but…that isn’t what explains this…

FCF Margins

The biggest improvements came from some of the very worst starting points back in 2021. SentinelOne increased 96 percentage points because it started at a -86% FCF margin 🤮. It’s now at a 10% FCF margin, which is good progress, but it still isn’t very good if it can’t keep improving FCF margins as growth rates fall.

The most impressive FCF margin improvement is Palantir…It’s the only one that started positive.

One reason why the Rule of 40 can be a misleading metric is because it assumes all companies can eventually trade growth for FCF margins. Many have proven that they are pretty terrible at doing that.

Footnotes:

• See how Agentic Finance can transform your finance department (today’s sponsor is Brex).

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

*nothing in this post is investment, tax, or legal advice

AI agents in finance are really powerful when they have the right context, controls, and operating environment.

I (OnlyCFO) have been working closely with Brex for over 2 years, and what they’ve built for agentic finance (AF) is incredible. With Brex, agents handle all the tedious stuff, like expense reports, policy enforcement, and month-end close, so your team doesn’t have to. Check out Brex AF!

Check out Brex AF

Hot or Not?

In 2026, your company is either hot or it is not. There is a massive number of companies sitting in the “messy middle” that used to be able to have a decent exit. That’s much less true today. It’s now fairly binary. You are either hot and can have a great outcome OR you are not and even if you can get an exit, it won’t be good.

If you want to raise money or have any kind of exit, then you have to figure out how to become hot. Intercom (which rebranded “Fin” last month) went through a crazy journey and emerged a winner.

Was Hot - Unicorn!

What started as “Intercom” previously raised a total of $241M, with its last fundraise at a $1.3B valuation, and was contemplating an IPO in 2020/2021.

Then NOT Hot - Zombiecorn :(

Growth started tanking in late 2021. And then Intercom was deemed an AI loser which hurt growth even more. By late 2023 they were ~$250M of ARR and basically flat growth.

If Intercom was lucky, maaaybe they could have gotten acquired for like $800M (~3x ARR multiple).

Now Fiery Hot - $3.6B Acquisition!

When you are looking death squarely in the face (which in tech company terms is no exit prospects with quickly diminishing possibilities) then you are more likely to make the hard choices.

Intercom had to figure out how to become hot again. Or its fate would be a lonely road to nowhere…

Intercom was reborn as Fin and transformed their business for AI. Revenue accelerated. But the chart below doesn’t show how they reaccelerated….Their new Fin AI agent product is growing 350% and just reached $100M of ARR.

That acceleration gets noticed and is what gets potential strategic acquirers excited.

Salesforce announced yesterday that they were acquiring Fin for $3.6B!

Headline Deal Numbers vs Reality

Headline Number: $3.6B acquisition, which is a 9x ARR multiple (based on their disclosure last month of $400M ARR).

9x ARR multiple is a pretty good multiple today, but that completely undersells the transformation at Fin. Salesforce wasn’t buying Fin for the entire $400M ARR. Fin’s $400M is comprised of $300M legacy SaaS ARR and $100M of Fin (AI agent) ARR. Salesforce wanted the $100M…

Art explains how the acquisition could be viewed as up to a 36x ARR multiple. Now that is a great multiple.

Fin likely got some credit for the other $300M of legacy SaaS ARR, but at a much lower multiple, likely something around a 2–3x multiple. That means the AI agent ARR was probably valued closer to 27–30x ARR. So while the blended headline shows 9x multiple, the reality is that Salesforce was paying up for the AI growth. Salesforce would not have acquired Fin at any price if it wasn’t for the AI agent revenue.

Can I Become Hot?

If you are hoping to raise money or have any kind of exit (M&A or IPO), then you need to prove that you are becoming hot.

Growth rates either need to already be high or they need to be accelerating. It’s the easiest way to prove that you are building something real with AI and have product-market fit. Everything else falls into the “Not Hot” category and is deemed an AI loser.

The list of software zombiecorns is very large…These companies can still have good outcomes if they move fast (like Fin), but most won’t. And to be honest, for many companies it may be too late. They already lost their advantage and were too slow to move.

Deals are Happening

Deals are happening right now, but you MUST be hot to get any sort of decent valuation. Many people see the Fin headline and think they can sell for 9x ARR too because they have close to the same overall growth rate.

Wrong.

Their ~29% YoY growth rate is pretty good, but that is not what got them acquired. It’s the 350% YoY growth rate to $100M ARR from their AI product that did.

If you are at the same growth rate but decelerating, then you will be lucky to get acquired for 1/3rd the amount.

Accelerate or die.

Footnotes:

• See how Agentic Finance can transform your finance department (today’s sponsor is Brex).

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

AI agents in finance are really powerful when they have the right context, controls, and operating environment.

I (OnlyCFO) have been working closely with Brex for over 2 years, and what they’ve built for agentic finance (AF) is incredible. With Brex, agents handle all the tedious stuff, like expense reports, policy enforcement, and month-end close, so your team doesn’t have to. Check out Brex AF!

Check out Brex AF

“Tokenmaxxing” is Dead

AI token spend is quickly becoming one of the largest vendor expenses, only behind salaries and maybe facilities.

So one of the highest ROI activities a CFO can do right now is to evaluate how the company can be more efficient with AI token spend. Not necessarily to cut AI usage, but to be more efficient with it.

I have talked to several engineers, CTOs, and people much smarter than me to develop this list on where to save on AI spend. I am biased but I think every CFO (and other leaders) should understand the ways to reduce AI model costs below.

1. Right Model for the Task

To understand the importance of the “right” AI model, you need to know the cost differences in these models.

If we use Claude as an example (the others are similar), the “smartest” AI model is 5x+ more expensive than the cheapest model. That means companies could be paying up to 5x more than necessary for many tasks.

The meme below summarizes the problem well…

There are LOTS of cases where the latest model is overkill for the task. If you tell Claude to use Opus 4.8 to rename files or update formatting in a board deck, it will.

This is where “model routing” comes in.

Model Routing = For each AI request, it decides which model should handle the task.

Model routing can be as simple as setting up some basic rules that define “IF this task type THEN use this AI model”. Or it can get as complicated as using an actual AI model to determine what AI model should handle the task.

Awesome! So how do I start model routing?

There are two different ways to use an AI model

1. Directly in App (Claude, ChatGPT, etc) - this is how most internal teams are using AI models.

2. Via API Calls - through another platform that sits between the user and the AI model. If you are selling an AI product, then it’s via API calls to the AI models.

Model routing basically only works if done via API calls. But many people (including me) wrongly assumed model routing wasn’t available for internal use, which is where a lot of AI spend occurs. That is not correct.

Company-Level Model Router: At a company level, you can add an “AI gateway” that sits between the AI models and the user. Instead of directly using Claude/ChatGPT, the AI gateway interface is where AI chats happen and it uses API calls. The AI gateway can then run your model router. You just need to build or buy an AI gateway…

Verticalized Model Router: Having a good model router is obviously important because you don’t want hard tasks going to a cheap model and screwing things up. So some model routers are built for types of people (like software developers). Maybe someday we’ll have model routers for every department...

Model Routing Savings Example:

Let’s say you’re spending $100K/month on Claude:

You currently use Opus 4.8 (most expensive model) for everything, but if the company only used the model it actually needed for the task then it could look something like the below:

Opus is rarely needed for every task. So if users shifted to using Sonnet and Haiku when appropriate, the company could save nearly 50% ($576K per year)…

Model routing is getting quite good so the risk of routing to an incapable model can be pretty low if you set it up correctly.

2. Prompt caching:

I am not going to get deep into this because the important thing is for you to simply ask engineering “Are we prompt caching on repetitive tasks?”

If you’re sending the same large context on every API call (a system prompt, a reference document, a knowledge base), then you’re paying full input price every single time. Prompt caching stores that content so repeat calls cost ~90% less on the cached portion.

This is where data visibility becomes so important. If you can track token spend per API call then you can see what is burning a ton of tokens and often the recurring token-heavy tasks can be reduced a lot by caching.

3. AI Cost Visibility & Reporting

AI costs will soon be your largest vendor expense (if not already). As such, it’s important to be able to drill down into the costs and understand the drivers….

A couple of the big unlocks that come from AI spend reporting:

• AI spend by employee by AI model.

  • Are employees using the most expensive model for simple tasks?

  • Help with forecasting AI spend by department

  • Are you allocating AI costs properly? AI spend needs to go to the right departments so department leaders are incentivized to control it.

• AI spend per API call

  • What products/features are driving the highest AI spend?

  • How much does the above vary by customer?

  • How should we forecast gross margins?

4. Batch API

If a task doesn’t need a real-time response, you can use the AI model’s “batch API” and save ~50% on token costs. A lot of stuff doesn’t need to be real-time so figure out where batching is fine because it can save significant money.

We did this exact thing with our ASC 606 agent. Our agent was reviewing every single contract as it was closed-won in SFDC. It reads our revenue policy, compares it to the contract terms, reviews our list of concerns, and then it documents the treatment and notifies us of any issues. We didn’t need this real-time. It was processing lots of contracts every day. So we batched them at the end of each day. And we stacked cost savings with prompt caching (#2 above) as well. We saved over 50% on the costs for this somewhat expensive AI task. And it took <1 hour to do.

5. AI Admin Controls

• Set the default to the middle-tier model (e.g. Sonnet for Claude). If you are not using an internal model router, then at least do this. 90%+ of users will just use the default model. While they usually won’t be using the most expensive model, they will also almost never downgrade to the cheapest model. Just doing this will save you up to 40% (price difference between Opus and Sonnet) across most teams.

• User Spend Limits: Put controls on users so they don’t create something that just blows up AI usage. Uber just limited developers to $1,500/month in token spend after they blew through their full-year AI budget in 4 months…Set a limit, even if it’s high, so nothing completely blows up. Then you can start to lower the spend limit later if you want.

6. Employee Education

Make sure employees understand this stuff. Most employees just don’t know how to be efficient with AI spend yet. Some examples (in addition to everything above):

• New topic = new chat. Each time you prompt in the same chat window, it re-reads the entire chat history. This gets expensive quick (especially if you are on a premium model). I have seen people just default to the same chat window every time they go to AI…

• Be upfront with everything you need in one prompt. Back-and-forth exchanges compound quickly. Every reply re-reads the full history. Give Claude the full context and ask for exactly what you want in one shot.

• Update the AI model in your automations, agents, skills, etc. A lot of scheduled tasks are structured and repetitive (often fine for a cheaper model). Users can define which AI model to use in agents/skills/automations. Test out a lower tier model and see if it works fine. This is like model routing but it’s manual since there is no automatic solution.

• Output token discipline. Output (AI responses) costs 5x input (user prompts). Asking for detailed responses, not capping responses, letting agents narrate every step will all multiply the expensive side of the bill. Telling models to be concise and setting hard output limits is close to free and underrated.

Final Thoughts

Every CIO and CFO I have talked to recently said the same thing about “tokenmaxxing”:

Tokenmaxxing served its purpose. We wanted to push AI adoption as fast as possible and get employees using the tools that would get us ahead.

Now it’s time for us to drive efficiency in that spend and ensure we are creating real ROI.

It’s time to be efficient with AI. Not slow people down necessarily. But be efficient. Start being efficient now before you have to start making harder cuts (like people or setting hard token limits).

The goal is not to cut AI usage, but to be more efficient with it and drive real ROI.

Footnotes:

• Check out Magpie to see the kind of AI visibility and reporting Brex is building and for a deeper look into the complexities of AI cost analysis.

• I cover a lot more AI stuff under my new newsletter (CFOpilot). Subscribe

• Subscribe and share this post with your finance teams. They need to understand this stuff.

Subscribe now

AI agents in finance are really powerful when they have the right context, controls, and operating environment.

I (OnlyCFO) have been working closely with Brex for over 2 years, and what they’ve built for agentic finance (AF) is incredible. With Brex, agents handle all the tedious stuff, like expense reports, policy enforcement, and month-end close, so your team doesn’t have to. Check out Brex AF!

Check out Brex AF

What is “ARR” in 2026?

There is a lot of deception/fraud in “ARR” numbers being reported today. While ARR isn’t governed by formal accounting standards like revenue, there are common practices that should be followed. If not followed, then you are either trying to deceive investors or you don’t understand basic financial stuff. Both are bad…

Let’s start with what “ARR” stands for.

Traditional ARR = Annual Recurring Revenue

2026 ARR = Annual Run-Rate Revenue

With AI, new pricing models, contractual changes, etc. the first “R” in ARR feels a little misleading so I think most companies should think about it as a run-rate amount, but everyone still simplifies it to “ARR”.

This post outlines my views on ARR in an AI world and how you should approach defining it at your company.

There are three primary questions that need to be answered:

1. What counts as ARR?

2. How do you report ARR?

3. How do you calculate ARR?

1. What Counts as ARR

There should be a strong correlation between the following:

1. Current “ARR”

2. GAAP revenue, billings, and cash collections over the next 12 months

A greater divergence or risk in that correlation increases the odds that you need either 1) an ARR policy change or 2) separate disclosure of that piece of ARR.

*GAAP (or generally accepted accounting principles) contains the rules that govern how revenue must be recognized (and also lots of other accounting rules)

How ARR Should Convert to Billings, Revenue and Cash

Let’s look at a single customer that closed an annual deal on Jan 1st for $1,200. In January there is $1,200 of ARR for that customer. If we billed upfront then we would bill them once for $1,200 and then maybe collect the cash the subsequent month. And then we should recognize $100 per month for the next 12 months.

ARR → Billings → Cash → Revenue

The expectation is that ARR is the baseline of what GAAP revenue should be over the next 12 months. And that should be billed/cash collected for that same amount.

How Being Aggressive on ARR Backfires

• Lose investors’ or prospective investors’ trust, obviously.

• Metrics all look much better than they are. Maybe good for tricking investors for fundraising, but bad for building long-term trust (which you need). Plus once “ARR” growth slows down (and it will), the metrics are going to look much worse than they should since you pulled ARR forward into earlier periods.

• Hiring and spending on inflated metrics. Related to the above. A lot of companies make spending decisions based on ARR-related metrics (new ARR, NRR, GTM efficiency metrics, etc). If those are wrong, then bad decisions will be made.

• If ARR is aggressive then churn will be higher as well. If you are aggressive on what gets counted as ARR then you must realize that the only way off the ARR waterfall is churn… High churn numbers are going to make your business look like it’s not durable (AI product is fake or your product is being commoditized by the AI models).

Spotting ARR Lies

If I want to quickly check for ARR deception, then I will compare their ARR number to a simple GAAP revenue estimate that I perform based on ARR.

It won’t be exact, but if the difference is too large and it isn’t clear why, then that will be a major red flag for me.

There are two primary components of my estimate:

1. Baseline GAAP Revenue: the expected revenue from starting ARR. This is what revenue theoretically should be if there were no changes (no new business, expansion, or churn)

2. New Revenue: revenue derived from new deals

The example below illustrates how I would estimate revenue from ARR and why it may be a red flag:

If a company provided me the above ARR and revenue numbers and gave me no further context, I would be very skeptical.

There are a lot of reasons that my simple forecast might be materially off, but most of them mean that there are lies/fraud/aggressiveness in ARR definitions.

Linearity/Seasonality

This is a valid reason to have a difference, especially if the company is growing crazy fast relative to its base ARR.

Revenue is recognized over time so if 90% of deals are closed in the last quarter, last month in the quarter, or last day in the month then ARR will diverge from a simple ARR forecast. But you could put some basic assumptions in here as well if you have the detail.

Counting Bad Deals

Every company has some bad deals that should have never been booked, but these can get large if the company is super aggressive. And they will show up in the gap between ARR and revenue.

If a customer invoice (“billings”) isn’t paid, then it shows up in one of two ways on the company’s financials

1. Reversal of revenue (e.g. CSM says “don’t pay we made mistakes”)

2. Bad debt expense is recorded (e.g. customer goes out of business)

There are accounting rules that supposedly determine which one should occur based on the scenario, but it can certainly be grey.

So if the company has a lot of #1, then there is going to be a large gap between ARR and revenue. And large revenue reversals likely mean a lot of ARR is fake.

But also…even if ARR lines up with revenue you may have a problem if bad debt expense is massive. It just means the company is burying the problem in expenses because they want revenue to be higher (since investors care more about revenue than some G&A expense)

Cash don’t lie so if ARR isn’t converting to cash then that’s an ARR definition problem.

Gap between ARR Date and Rev Rec Start Date

My general rule is if the time between contract closing and revenue recognition start date is <14 days then it can be ARR on contract close. If >14 days then wait to count the ARR until the revenue recognition start date (which is often the start date of the contract).

I have seen companies start counting ARR immediately when they had a 6-month delay in contract start date because the company wasn’t ready to move forward yet.

That contract will get $0 in revenue, billings, and cash for 6 months…

Ramping Deals

Just count this ARR when the ramp starts. It’s contracted upsells. Why count that upfront before the upsell and related costs kick in? It screws up your metrics.

A lot of companies just average it into ARR (TCV/contracted # of months) but that would recognize too much ARR upfront and not enough at the end of the contract.

Contracted ARR (CARR) vs ARR

This is the “fraud” that many people refer to in regard to ARR at hot new AI companies. They are reporting a very inflated number.

Contracted ARR = future contracted value

If you have a deal that is $50K in year 1 and $150K in year 2, then contracted ARR would be $150K. That is a 3x reality distortion from whatever an investor assumes “ARR” is. And that $100K extra ARR in year 1 won’t convert to revenue or cash.

I think “contracted ARR” can be an interesting data point, but do not mix it with ARR…disclose it completely separately if you want.

“Experimental ARR”

An existing product that has 1+ year contracts is very different than a new product with new technology that is charged month-to-month or on a pure usage basis.

A lot of new AI products have a high churn rate.

Maybe this can get included in the “ARR” bucket, but you should at least report it separately in your ARR waterfall to your board if the characteristics are materially different than the rest of ARR (see reporting section below).

Usage Overages

I only include overages in ARR if I am confident the overages will reoccur for the foreseeable future. Spikes in usage happen and then customers figure out how to control them.

An AI consultant told Axios that one customer accidentally spent $500M in a single month after they forgot to put usage limits in place. That would be…6 billion dollars that Anthropic could have counted as “ARR” 🤣. If $500M is accurate (big if), then certainly the entire thing wasn’t “accidental”. Likely some portion was a min commitment or had a trended growth over the past few months. And then the rest was a one-time spike. That spike certainly won’t reoccur so hopefully Anthropic didn’t book $6B in ARR related to that customer…

Trials/POC

Not ARR. Please don’t count free trials as ARR based on some estimate or contractual amount that the customer has to opt in to at the end of the trial period.

What about paid trials?

This can be somewhat grey in my opinion…If fully paid and you have a history that 90%+ convert then maybe I would be OK with it as long as the ARR amount tied to it is separately disclosed.

Because guess what? You have to be comfortable with the other side of the double-edged sword. Are you willing to add it to ARR and then recognize a high amount of churn soon after?

One-Time Stuff

Not ARR. Duh. Surprising how often people try to sneak some of this stuff into ARR though…

Other Red Flags That Your ARR Definition is Broken

• Lots of debookings. If you have a lot of debookings (i.e. you reduce net new ARR in the current period for prior period booked), then you probably have an ARR definition problem.

• High churn <6 months after deals close. This usually just means the sales leader bullies the CS leader to count it as churn so it doesn’t impact his/her team’s numbers. If lots of stuff is being marked as churn, expected to churn, and/or is not paying then you got a problem.

• Previously reported ARR numbers constantly change. Have seen several times where companies go back and adjust prior ARR numbers and expect me to not notice. They don’t want to count it as churn or debooking in the current period and impact growth rates so they adjust prior period numbers to make it look like the ARR was never recognized.

2. How to Report ARR

How you report ARR is important for decision making and preventing misunderstanding of what ARR is.

My Big Rule: Always define ARR wherever it’s presented. Changes should be infrequent.

In traditional SaaS, we could usually report ARR as one number because the characteristics of all revenue were mostly the same - highly predictable, durable revenue.

But ARR ain’t what it used to be….

• Pricing models are much more complicated: lots of flavors of usage-based pricing (pure usage, hybrid, etc), dealing with overages, etc

• Contractual terms create more variability - pure usage-based billing, min commitments, etc

• Gross margins across products (particularly AI) can vary widely. An 80% SaaS gross margin product obviously has very different unit economics than a 40% AI product.

• High retention is often no longer expected. And this is reinforced by shorter contract durations. Old software was 1+ year contracts (often longer) with fixed pricing… This made using ARR as a starting baseline for next year’s billing/revenue easy.

This increased complexity requires more detail in your ARR waterfall. I have never heard a board member or investor complain about too much ARR detail.

Example: Mostly Seat/Platform Fixed Pricing with Some Usage

You should break out usage-based ARR from contractually fixed so it’s clear how much unpredictability exists in ARR.

The table below breaks out usage-based increases and decreases. You could then further break that out by committed usage vs pure usage-based, by product if gross margins vary wildly, etc.

3. How to Calculate ARR

If you read this far hoping I would tell you exactly how to calculate ARR, you are going to be disappointed.

There are lots of different ARR calculation methodologies that companies may adopt. And often companies will have different calculations depending on the product and how it is priced and contracted. Below are a few common ways.

• MRR * 12

• Last month’s GAAP revenue * 12

• Trailing [X] month average MRR * 12

• TCV/contract length x 12

• Variation of one of the above less [some portion of variable revenue not expected to reoccur]

• Annualized contractual commitments (for usage-based)

I don’t think any of these are necessarily wrong and if you follow the principles I laid out in the previous two steps then you will likely land on a decent ARR calculation.

TLDR: Please Don’t Lie on ARR

If you learned nothing else, then at least do these two things:

1. Clearly define ARR every time you report it

2. Be consistent in your definition

I know there is a lot of pressure to show growth right now, but cheating with your numbers is not the way to do it. Be honest and transparent.

If you want to show the ARR potential with trials, future expected ARR with ramping deals, or something like that….great! Make a separate slide that shows those numbers. But make sure you’re clear with what you are presenting.

Footnotes:

• See how Agentic Finance can transform your finance department (today’s sponsor is Brex).

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

AI agents in finance are really powerful when they have the right context, controls, and operating environment.

I (OnlyCFO) have been working closely with Brex for over 2 years, and what they’ve built for agentic finance (AF) is incredible. With Brex, agents handle all the tedious stuff, like expense reports, policy enforcement, and month-end close, so your team doesn’t have to. Check out Brex AF!

Check out Brex AF

Entrata Files to IPO

Entrata filed their S-1 this past week and folks were surprised that they hadn’t heard of this hot new AI company before. Oh wait, Entrata is property management software…

There has been A LOT of excitement around the hot AI IPOs (SpaceX, OpenAI, Anthropic, etc), but most of us didn’t have Entrata on our list of companies to lead out the massive backlog of software IPOs. We have been constantly told over the last year that software is dead…

But Entrata seems alive and well! Not incredible metrics (particularly compared to all the AI stuff we constantly hear about), but really strong metrics compared to most software companies at their scale.

I know that a lot of software companies will be anxiously watching to see if Entrata will open the IPO floodgates for the hundreds of other “pretty good” private companies hoping to IPO in the near future.

Let’s dig into Entrata…the financials and story are really interesting.

1. Entrata’s Financial & Metrics

2. Estimating Entrata’s Valuation

3. Entrata’s Unique Fundraising History

How Does Entrata’s Financials Stack Up?

Entrata is a great business. They scaled without real venture capital money so they have always been efficient. So like most bootstrapped businesses, their growth rates have been more modest.

*Yellow bars are Entrata

Revenue

Revenue Scale

Revenue scale is important context. I see too many people say we are growing just as fast as X company but they are 10% the revenue scale…

Revenue Growth Rate

Entrata has a good growth rate (21st out of 73 companies). The market has definitely shifted to being more growth-focused again.

The general sentiment is that if growth isn’t strong, durable, and maybe even accelerating, then you are an AI loser. And AI losers have a terminal value of near $0.

Revenue Endurance

Revenue endurance measures how persistent revenue growth rates year-over-year. It is calculated as follows:

Entrata may not have had rocket ship levels of growth, but it has consistently just kept growing revenue at a good rate for a really long time. Entrata has a better growth endurance rate than almost any public software company over the past 5 years…

Profitability

Gross Margins

Entrata has bottom-quartile gross margins. Since they represent the ceiling of profitability, gross margins is a key metric.

While Entrata has lower gross margins, the improvement over the past couple of years has been incredible. From 54% GAAP gross margins in Q1’24 to 63% in Q1’26….

Increasing gross margins that much is hard to do. I believe a lot of it is a higher mix of customers with higher gross margin products, but also from continued product additions.

GAAP Profits

According to Alex Clayton at Meritech, Entrata is the largest software IPO to be GAAP profitable while growing 20%+. Not to diminish that record, but a lot of that is because most software IPOs were growing faster so they were trading profitability for growth (at least that was the idea…)

Regardless, Entrata is very efficient. Especially after considering their lower than average gross margins. Their OpEx is very efficient.

Free Cash Flow Margins

They have to be FCF positive for a long time given their [mostly] bootstrapped history. Entrata’s good (not great) FCF margins.

Rule of 40

The median software company has a Rule of 40 Score of 38. Entrata is just slightly better than that at 40.

Retention

Entrata also has great customer retention metrics:

• GRR: 99% in 2024 and 97% in 2025

• NRR: 117% for 2024 and 2025

Customers just don’t leave Entrata…And that is exactly what every software investor is trying to assess right now. “How durable will revenue growth be over the next 5 to 10 years?”

What Will Entrata’s Valuation Be?

Entrata’s last fundraising in May 2025 valued them at $4.3B. They also did a tender offer a couple of months later at the same price where employees and former employees sold $37M worth of shares.

It’s worth noting the public cloud stocks are down on average by 8% and their closest comp (AppFolio) is down 23% over the same period.

There isn’t going to be irrational exuberance around the Entrata IPO given all investors’ attention being on AI and other IPOs, but MANY folks will be paying close attention to it as a signal for the broader software IPO market.

Below is how I would expect Entrata to price at IPO.

Bootstrapping, Magic Mushrooms, CEO Forced Exit, & PE Takeover

Entrata (property management software) was founded in Utah 23 years ago when vertical software was a lot less sexy than it is today. Being in Utah and in vertical software at the time meant they didn’t follow the traditional VC path.

Two Early Investments (2005-2006)

Despite almost all reporting saying they bootstrapped for 18 years, Entrata did raise a couple of small early rounds (not institutional money though) in the early days.

In 2005 Entrata raised $125K at a $1M valuation. And then not too much longer after that they raised another small round at a $2M valuation (amount unknown but probably around $200K-300K)

Between these two rounds, Entrata was diluted by ~25% (my best guess)

Bateman recently said that the $125K investor/s made a 1,100x return on their investment (probably exited in the next round below). Not bad!

Founder Takes Magic Mushrooms (2018)

Bateman went to some magic mushroom retreat and decided he was done running Entrata. Bateman wanted to keep his equity but was done with the day-to-day. So Entrata hired a new CEO to run things.

1st Institutional Capital (2021):

PE Firm, Silver Lake, led a $507M round in 2021 (the largest private round in Utah history). The valuation was never disclosed, but I have a guess…

The Silver Lake investment was not all primary capital. There was likely a large amount of founder and early investor liquidity. Much of the details were never disclosed, but Bateman has said that he owned ~60% after the Silver Lake investment, which likely means a lot of the $507M bought out those early investors.

Based on some triangulation of the numbers above, I would guess the valuation was ~$1.5B.

CEO Forced to Sell 100% of His Holding Due to Unhinged Email (Early 2022)

Bateman sent a conspiracy-filled, racist email about COVID-19 to the most prominent figures in Utah.

Bateman was kicked off the board and they forced him to sell 100% of his holdings, which was led by Silver Lake. If Silver Lake acquired Bateman’s ~60% shares at the previously estimated round price of ~$1.5B, then he would have walked away with ~$0.9B, but maybe Silver Lake got to buy his shares at a bit of a discount given the circumstances….

After the sales of Bateman’s shares, Silver Lake became the majority shareholder of Entrata.

Blackstone Invests $200M at $4.3B (May 2025)

In May 2025, Blackstone invested $200M at a $4.3B valuation. A big increase in valuation from a few years earlier. The average public cloud company’s stock price fell by ~30% over that same period of time.

Debt and Dividend Recap

Entrata had $200M of debt on the books by 2024, but then in 2025 they refinanced and took on $400M of total debt. They used almost all of that to pay a dividend of $356M….

Entrata got good debt terms on it though.

They only have to pay $1M per quarter with a bullet payment at the end and a rate of 3% + SOFR.

Will Entrata Have A Successful IPO?

I really hope so because maybe that means Entrata will start to open up the IPO window for the hundreds of others waiting for their turn.

The timing is pretty good from both a market perspective (public software is up nearly 40% from the lows last month) and Entrata continues to execute strongly.

While not some sexy AI company, Entrata is a solid business. The big question is what valuation will investors give them when it seems like the only thing folks are excited about are all the potential hot AI IPOs (OpenAI, Anthropic, SpaceX, etc). And investors remain nervous about software, despite the recent bounce in stock prices.

Entrata seems like a great company with a lot going for it. We all just need to be able to answer one question: “How durable is revenue over the next few years?”

Congrats to the Entrata team! I am rooting for you.

Footnotes:

• See how Agentic Finance can transform your finance department (today’s sponsor is Brex).

• I wrote about how to significantly cut your ChatGPT/Claude spend on my new AI-focused newsletter. Check it out and subscribe

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

*nothing in this post should be considered investment, legal, or tax advice

I made plenty of mistakes when expanding internationally. I’ve learned a lot over the years, so I wrote a guide on some of the most important finance considerations:

• General guidelines for how to hire (contractor, EOR, set up an entity)

• Offshore cost benchmarks by country

• Additional employer burden (don’t forget about these!)

I partnered with Deel to pull real cost benchmarks (the kind of data I wish I had when doing this). Download my playbook for expanding internationally.

OnlyCFO's Global Hiring Playbook

A CFO’s Worst Nightmare: “Tokenmaxxing”

Anthropic is awesome. I am going to probably use $300 million of Anthropic this year at Salesforce. Coding. Everything’s going to be cheaper to make. — Marc Benioff (CEO of Salesforce)

AI tokens are becoming the biggest vendor expense on the income statement (if it isn’t already). From basically $0 spend to the largest in just 2 years...If token costs aren’t rapidly becoming your largest vendor expense, then that probably means you are behind in AI adoption.

Everyone is “tokenmaxxing” right now. And everyone seems to be encouraging it. Well, everyone except for maybe the CFO 🤣.

Tokenmaxxing: maximizing AI token consumption as a signal for AI adoption.

The primary goal, which everyone can agree with, is to make sure folks (across departments) are really adopting AI. AI adoption is critical to every tech company’s survival in 2026.

But this AI adoption is creating a very large expense that companies need to make sure is treated properly on their income statement. And leaders need to understand how it impacts the financials, their budgets, and the company’s long-term unit economics…

Share

AI Costs on the P&L

Cost of Revenue & Gross Margins

When AI is embedded in your product, then that portion of the costs is included in COGS. It’s an incremental expense line in COGS.

The COGS lines 1-5 are the same, but now we have a large new one (#6).

1. Professional services

2. Support team

3. DevOps

4. Customer Success Management (diversity in practice)

5. Infrastructure/hosting costs (AWS, Azure, etc)

6. AI token/inference costs

   1. API spend with AI models (Claude, ChatGPT, etc)

   2. Model hosting when you self-host (not calling an API but using AWS, Azure, etc GPU power)

   3. Vector database costs

   4. Orchestration and observability

This new (and large) expense line in COGS is creating much lower gross margins and that requires a shift in how leaders think about long-term unit economics.

While AI gross margins are up a lot in the last couple of years (from 41% in 2024 to 52% expected in 2026), they are still significantly lower than typical software gross margins.

The median public software gross margin is 77%. This is largely because true AI revenue still isn’t a significant portion of their total revenue yet. Gross margins will be materially lower for most of these companies in 12-18 months…

Because of the vastly different economic profile of AI products, it’s important to be able to track the revenue and COGS of all products separately.

I have talked to a lot of companies that have been blending AI token costs in their “hosting” P&L expense line and also can’t segment gross margins by product. Do NOT do this. The extra data is critical for making decisions.

Create a new line just for the AI costs running through COGS. You, the broader exec team, and the board will want to pay close attention to COGS from AI so tell your accounting team to create a separate line for it.

Below are a few new metrics that every company should be tracking:

• AI COGS as a % of AI revenue. How much lower are AI gross margins?

• Gross margins by individual AI product. Do some AI products have worse gross margins?

• AI COGS relative to total revenue. How much is AI degrading overall gross margins? What is the trend?

• Correlation of AI COGS with revenue. Do you have a broken pricing model?

R&D AI Costs

Your “builders” (engineering, product, and design) are typically the people at the company who are burning the most tokens/spend on AI. And they should be spending the most given what they should be building.

The breakdown below shows the costs required to develop an AI product. Costs are pretty consistent across product development stages.

According to a survey performed by Scale (that Jason Lemkin discussed on SaaStr), the average developer spent $1.3K/month (or $16K per year). And many folks think this is too low…

But you can’t have more token costs and not have something else impacted. Either the higher spend has to directly translate into more revenue. Or…it means you have to cut headcount costs.

You have to figure out the ROI math on when the additional token cost per employee is less effective than the headcount that must be cut as a result of the higher token spend.

S&M AI Costs

There are a lot of AI use-cases in sales and marketing, but most of them are not that expensive in tokens from what I have seen.

One S&M AI cost that can be large (and often misclassified) is the incremental POC/trial costs for AI products. The costs associated with these should go to the sales/marketing department. I have seen many companies not track these well, and they end up erroneously in COGS.

These POCs/trials are increasingly common with AI products as customers want to see the value before they commit. Companies need to make sure the costs are not spinning out of control as they add more AI stuff.

G&A AI Costs

Beware of the AI cost dumping ground into G&A. G&A frequently becomes a cost dumping ground (even before AI):

1. Ignorance or bad accountants who don’t know that some of those costs don’t belong in G&A

2. Intentionally pushed to G&A so it makes all the important financial metrics look better

3. Some diversity in practice where some costs go

But company-wide enterprise AI licenses (Claude, ChatGPT, etc) do NOT all belong in G&A…In fact, the amount of AI-related costs sitting in G&A should be smaller than the other buckets (COGS, R&D, and S&M).

Yes, my G&A teams are doing some cool stuff with AI (check out CFOpilot to see what my teams and I are building with AI). But we should not be nearly as token-heavy as what R&D (or usually even S&M) should be spending.

Allocating AI Costs

Performing allocations of certain shared costs is nothing new for most companies. Although many do it wrong (especially private companies)

Example: IT Department Allocation

All company-wide software that is used by everyone (Slack, Zoom, Gmail, etc) is put into the IT department and then at the end of each month, it’s allocated across all the departments based on headcount.

Every department absorbs some of the costs since they all use it. So these costs end up in COGS (allocation to the support team), R&D (allocation to engineers), etc.

Your AI bill should NOT be allocated this way.

Headcount was a good proxy for how seat-based costs should be allocated across the P&L, but that breaks down for consumption-based pricing vendors. Especially when the usage can vary so much across departments and when it is a massive expense (like token spend).

More exact allocations are needed for token costs. The only good approach now is to do direct allocations based on specific department usage. Finance teams need to segment the different types of AI costs by department. Anything else will result in materially incorrect financials and unit economics.

Final Thoughts

Token costs are going to be the largest vendor expense in nearly every leader’s budget by the end of 2026, so it’s important to get the accounting and department budgeting right.

Trade-offs and changes will have to be made. You can’t just add a massive line of expense across the P&L and expect nothing else to change.

But companies can’t make the right decisions if the financial metrics are screwed up because AI costs aren’t properly allocated across the P&L.

Footnotes:

• Download my playbook for expanding internationally (when to use an EOR, set up an entity, compensation benchmarks, and more).

• Subscribe and share the OnlyCFO newsletter with your teams

Subscribe now

📚 Other Interesting Things:

Learn the Numbers

So many leaders and founders today don’t understand the numbers. And that will be a problem as they try to scale…

Forward my newsletter to your teams so they can get smarter on the numbers :)

Anthropic’s Revenue

The impact on all of our P&Ls from “tokenmaxxing” can be clearly seen in the unprecedented revenue growth rates of ChatGPT and Claude. We may never see something like this again…

Deel’s Financial Path

Deel is a company that continues to surprise me with their financial metrics.

But growing as fast (and efficiently) as they have isn’t luck. And they can’t slow down now. Every company is facing an “accelerate or die” moment. Deel is choosing acceleration…

Revenue Growth

• $0 → $100M ARR in 20 months: A record growth rate at the time (before the AI growth madness). “I am sure their ARR definitions are aggressive, right?”

• $100M → $1B ARR in 6 years: One of the fastest companies to hit $1B ARR. “Aren’t they just a payroll company? They can’t be growing this fast!”

And the “SaaSpocalypse” hasn’t slowed Deel down….

Despite the insane growth rates you might see among some private hot AI companies, 50% growth at $1.5B ARR is incredible. At least top-decile.

They are growing faster than every public software company (except for Palantir).

Profitability

After doubting their revenue growth, my next instinct was to assume they are burning cash like there is no tomorrow. “A payroll company probably has terrible margins, right?”

Last I heard, a few months ago, they have ~17% EBITDA margins…which is also best-in-class, especially considering their high growth rate…

Deel’s “Accelerate or Die” Moment

I recently sat down with Deel’s new CFO, Joe Kauffman, to discuss how Deel is accelerating in the age of AI and the importance of capital allocation to succeed today. Deel brought Joe in to be the leader that is able to take Deel public (he has the right experience).

Every single company is facing an “accelerate or die” moment in 2026. Below is how Joe and Deel plan to accelerate and become an AI beneficiary.

#1 Metric: High, Durable Growth

Leading up to an IPO, Deel needs to continue to prove why it’s worthy of the public markets. That is much harder today than a few years ago. Stellar financial metrics alone aren’t enough anymore. Every investor is questioning the terminal value of all technology companies.

If terminal value (TV) is trending to zero, then investors won’t want to touch it. And valuations will tank.

We are seeing this with many public names in the low growth bucket. There is a 5x difference between low growth and high growth company valuations…

CFOs should be thinking, at a minimum, about how to make their businesses AI-defensible. Think about how the core business may be susceptible to disruption, not just what’s right in front of you, but further down the road.

This focus on AI defensibility can be especially hard for public company CFOs, as it may require disrupting themselves in order to re-architect the business to be more defensible. — Joe Kauffman

Revenue growth continues to be the most important financial metric, but there is a lot more emphasis on durable revenue growth in 2026. “Can you keep strong growth rates for a long period of time?”

Whether you want to be acquired or IPO, nothing matters more than proving your revenue is durable in order to have a good valuation.

You Must “Accelerate”

AI can certainly help companies cut a lot of costs. And many CFOs will celebrate and brag about how much money they are saving by slashing software, headcount, etc.

But, if revenue growth falls off a cliff, do those savings matter? No…

When I refer to “accelerate” I am mostly talking about product. And the revenue will follow. The companies that don’t accelerate product in 2026 are going to get run over by the competition. Churn is going to skyrocket and acquisition costs are going to increase.

The most difficult challenge may be finding incremental businesses that are indexed to AI. That way, every time there’s a model improvement or other AI tailwind, you win too.— Joe Kauffman

Deel certainly seems to be accelerating product…And they are doing it in a way that benefits from their existing advantages (payroll system of record).

• Released Akai (last week) - interconnected agents that learn your team’s workflows so they can automate as much as possible.

• Acquired Sastrify (2 weeks ago) - software management and procurement

• Release of token monitoring tool (2 weeks ago) - ties token usage from LLMs to employees to help understand ROI and employee performance

• Deel app for ChatGPT (3 weeks ago) - Deel is now directly in ChatGPT so users can use AI to search and report directly from Deel

And there is probably even more cool stuff Deel is releasing, but the above are the things I am excited to try out.

Besides just their sheer speed of building, they are creating the right stuff that builds upon their moat/advantage - they are becoming the “operating system for work” (people and agents).

Getting Efficient to “Accelerate”

The second step is thinking about productivity gains from AI, and considering how to take those savings and reinvest them in products that drive top-line growth. — Joe Kauffman

Deel has acquired 14 companies since it started 7 years ago. And it continues to release products at a rapid clip. Deel (like everyone else) needs to use AI to become more efficient so they can reinvest some of those savings in the mission of “accelerating”.

Companies need to rebuild for efficiency. Some rebuilding should have likely happened regardless of all the AI progress (high-growth companies build bloat which also slows them down). AI is another strong reason to rethink how everything is done today.

Deel's new Ghostbuster role is one of my favorite org ideas of 2026.

Deel describes the problem as follows:

Over time, multiple layers accumulate, some become outdated, some become friction, and eventually people start optimizing things that probably shouldn’t exist in the first place. — Joe Kauffman

Every single person reading the above that has worked at a growing company knows that this waste can become VERY significant. And it slows everything down. You can’t be slow in 2026.

It’s a perfect time for this type of role because not only can they find regular waste, but they can find ways to rebuild things from an AI-first perspective. $10M in savings as their goal seems aggressive, but likely doable. The role has a 50x ROI based on the salary target if that goal is met.

Companies need to throw away conventional wisdom around org design and span of control because they are less relevant in an AI-first world. Historical headcount benchmarks are pretty meaningless in 2026.

Getting to “Real” Profitability

More and more investors will be looking at GAAP operating income and GAAP net income. CFOs would do well to look at the fully loaded cost per headcount (and fully loaded cost per agent) when considering ROI decisions for their human capital investments. — Joe Kauffman

Investors want to see that you can get to real profitability. And fast. As terminal values get called into question, investors are questioning mid to long-term profitability.

Not “adjusted EBITDA”….but real profitability.

Final Thoughts

Speed in capital allocation is really a consequence of the position you’ve built. The companies that will win are the ones that have built the muscle to move quickly and smartly. — Joe Kauffman

If you are competing with a company like Deel and you lack speed and/or direction, then you are going to get steamrolled.

Build with urgency. Build upon your strengths. Build things that will benefit from and become more valuable as the AI foundational models become more powerful (which they will).

Footnotes:

• Check out Deel (today’s sponsor) and all the cool stuff they are building

• Check out my new newsletter (cfopilot) for all the AI stuff in finance/accounting

• Join 37K other subscribers reading the OnlyCFO newsletter

Subscribe now

For finance leaders, managing international payroll and compliance requires expertise. Our ‘Guide to EOR for Startups’ offers a detailed look at efficient global payroll management & compliance. This guide will help you:

• Manage cross-border payroll easily

• Navigate tax implications across jurisdictions

• Reduce financial risks associated with global growth

Take control of your financial strategy today.

EOR Guide

Rebuilding Finance with AI

AI has dramatically changed how my team operates and we are still early (lots more work to do)…

I built an AI agent that turned a 2-hour task for my accounting team into 5 minutes. And we used this same AI flow across many similar processes (which cut a full day off of the month-end close).

I just launched a separate newsletter (CFOpilot) to write about everything I am learning and building with AI.

*The below post was shared at CFOpilot a few days ago. I got a ton of feedback on how valuable it was, so I wanted to share it here as well.*

My 6-Step Process to Building an Accounting AI Agent

I built our first AI agent to tackle accounting reconciliations (focused on prepaids initially).

Here is the process I ended up with…

An “agent” is essentially the worker that navigates all of these systems and steps to complete a task.

Step 1: The “Skill” Itself

Skill: A self-contained workflow an agent runs. A system prompt that defines what to do. MCP connectors to the systems it needs. A trigger that kicks it off. A config that drives the behavior. You build it once and it runs forever.

Every skill has a SKILL.md file. The skill defines the inputs, workflows, rules, output, edge cases, etc. My prepaid skill is ~200 lines.

You’re not writing a prompt every time you run it. You’re writing it once. And then updating it if/when something changes.

Step 2: The Config File

My config (YAML file) contains:

• Prepaid GL account codes

• Vendor → coding map

• Materiality threshold

• Partial-month convention

• Routing: who gets pinged, in which channel

When something changes, you edit the config (not the skill).

This is one thing I was doing wrong before. I was dumping everything into a prompt (or a skill). Every time something changed, I would have to update the skill and re-do it.

Having a separate config file with the stuff that might change breaks things up so it’s easier to maintain. It’s like why you don’t put your entire model and all the components in one giant tab or make Excel model formulas huge.

Putting everything in one skill file also makes it so you can’t reuse your skill in other recons, entities, etc because it contains the exact detail for one prepaid recon process. To make it scalable/reusable, you separate out those details into the config file. Then you can reuse the skill and just update the config file.

Step 3: MCP Connector to the ERP

MCP (Model Context Protocol): A standard way for an AI agent to plug into your software systems (Deel, NetSuite, Google Drive, etc) so it can read data, do work, and take actions in those systems on your behalf.

A surprisingly large number of companies I talk to still use AI like a simple chatbot.

The biggest unlock comes from giving AI visibility to everything…Only then can AI agents perform meaningful work end-to-end. The primary way to do that is via MCP connectors.

If AI is not connected to all your systems, then it lacks context, so it will require a lot more manual human effort for each handoff and coordination. AI needs to “see” all the context and have the ability to take actions (even if read-only) to be really useful.

My prepaid agent queries my ERP GL directly via the MCP. No CSV exports/imports.

The skill I created reads the config file to know which prepaid accounts to pull. The agent calls the ERP connector and pulls current period activity for those GL accounts.

If you don’t have an MCP connector to your ERP, that’s the first thing to fix.

Step 4: MCP Connector to the Shared Drive

The workpapers don’t live in your ERP. They live in GDrive, Box, SharePoint, etc.

The skill needs to:

• Read last month’s workpaper

• Write the new workpaper to a new file

• Enable the AI agent to create and edit the new prepaid workpaper

An MCP connector for the shared drive handles this.

Step 5: Slack Is the Trigger and the UI

Slack is the UI for my AI agent.

Slash command: I kick off the recon by typing “/prepaid April”. Or I just chat in Claude “I want to kick off the prepaid recon for April” and it will find it.

The agent will find the prior workpaper (location is defined in the config file), copy that workpaper to the current month-end close folder. It will then use that as the starting point for adding new prepaids, adding a new month of amortization, etc. The agent is trained just like a human would be…it brings over Excel formulas just like the prior month so the amortization calculates correctly.

When the agent finishes, it posts a digest with the workpaper, the JE CSV, and a tag for the preparer.

Below is an AI-generated Slack example of what I see (done with AI so you don’t see my actual Slack…)

If the AI agent flags something I need to fix, then I’ll do one of two things:

1. Open up the workpaper and fix the errors/flags (e.g., add the Cloudflare term from the example above). Then I add a ✅ to the Slack thread, which signals to the agent that I am done so it re-reads the files to see if I fixed the flags. It updates the files and posts a follow-up message for the reviewer.

2. If the issue will be repeating, then I will update the skill or config files to automatically fix it going forward.

Step 6: The Human Part

The skill doesn’t auto-post the JE. We still have a human preparer and reviewer.

• Human preparer: Person managing the agent and fixing the flags/errors that come up. They also do a review of the agent’s work.

• Human reviewer: This is the same process that the reviewer has always performed, and is an important control in accounting.

Essentially, we have turned both of these humans into reviewers. The preparer does the first pass and makes sure the agent did everything properly and then the normal reviewer acts as the final control and sign-off.

But we have even changed the reviewer’s process as well…more on that to come in future CFOpilot articles.

In Summary…

What previously took lots of manual steps (copy workpaper to new location, open up ERP, download detail, update workpaper, create JE upload file, etc) is now 90%+ completed by our AI agent.

From ~2 hours of human work to ~5 minutes.

It did take longer the first time I ran the reconciliation, but then the team took it and kept iterating and improving the skill and the config to automate more and more. Eventually, you get some major time savings.

And then repeat that across your other recons and you will shave off days from your month-end close…Smaller accounting teams, faster close, fewer errors, etc

Footnotes:

• Download this EOR guide from Deel. Every company looking to expand internationally should read this.

• If you are in finance/accounting, then check out my new AI newsletter (CFOpilot).

Subscribe to CFOpilot