Seed-Stage Startups Should Shrink Their Option Pools

Background reading:

You only get 100% of your cap table to give away (or keep), and the sad fact is founders make all sorts of tactical errors that needlessly give up points to investors and other parties. Sometimes those errors are driven by bad advice offered by misaligned participants in the ecosystem.

One example I’ve written extensively about is the aggressive anti-dilution mechanism built into YC’s default Post-Money SAFE Template. YC portrays its template as a wonderful legal fees-saving “standard” for founders, while staying quiet about its extremely harsh economics that amplify founder dilution. YC is, at the end of the day, a VC that benefits from making founders dilute more. So be skeptical about using their templates without any modification.

The reality is SAFEs are tweaked/modified all the time, and it costs essentially nothing in legal fees to do so. In that above-linked post I offer a very simple – just a few sentences – tweak to eliminate this issue, while preserving the post-money valuation mechanism that provides transparency on how much of the cap table a SAFE is purchasing.

Another issue I wrote about over ten years ago is how founders needlessly reserve too large of an option pool at formation. They’ll just pick a number, like 20% or 10%, and reserve that amount, regardless of what they actually intend to use. They think this costs them nothing, but it’s just not true.

First, most employee new hire equity grants are made based on a % of the fully-diluted capitalization. When you offer them 2% or 3%, the denominator of that percentage includes the reserved but unused pool. It’s simple math that if you reserved too large of a pool, you are needlessly giving them more of the cap table than you otherwise would have. If you had reserved a smaller pool up-front, the 2% or 3% would be of a smaller pie, and then in expanding the pool later (which you can always do), the employee dilutes alongside everyone else.

Second, reserving too large of a pool makes it easier for VCs to argue for a needlessly large pool in your first equity round. As I wrote before:

“The pool you reserve before your first VC financing will set the baseline for negotiating how much of an option pool “top up” VCs make founders absorb.”

If your pool is at 5% going into a funding round and your VCs are negotiating for a 10% or 15% pool post-closing, it’s going to show up as a very large increase. The optics of that increase will help you in negotiation. But if you start with a 10% or 15% pool that you didn’t even need, the increase will look much smaller, which means you basically made the VC’s job easier for zero benefit to yourself.

The above two issues are not new in my writings. Stop reserving too large of a pool at formation, because it ends up giving too much equity to employee/consultant/advisor hires via equity grant calculations, and to VCs via equity round negotiations.

A somewhat newer issue that I want to emphasize here: Post-Money SAFEs make it even more costly to have an artificially large pool, given how their conversion math works. Shrink your pool to as small as possible before your SAFEs convert.

The definition of “Company Capitalization” in the Post-Money SAFE (which is the denominator for purposes of SAFE conversion) includes the pool existing before the equity round, but excludes the pool increase negotiating with your new lead VC(s).

Thus by having a pointlessly large pool at the time of SAFE conversion, you are just handing money to the SAFE holders. Shrink the pool before SAFE conversion to only exactly what you need, and the full pool increase of the equity round will NOT drop the SAFEs conversion price.

I’m not going to show specific examples of the math here. You can use the Open Startup Model (free) if you don’t have your own excel model. Suffice to say based on a few examples I’ve modeled out, you can reduce the amount of dilution your SAFE holders take, in most scenarios, by about 10% or more. Free money.

So the costs of having a pointlessly large equity pool before an equity round continue to mount:

  1. It means you’re giving too much equity to new hires.
  2. It means you’re making the job of your VCs in your equity round easier by front-loading an option pool increase they would otherwise need to argue for themselves.
  3. It means your SAFE holders are getting more shares from their SAFE conversion than is actually necessary.

Stop. Reserving. Stupidly. Large. Option. Pools. The emergence of AI probably means hiring needs, and associated equity pool needs, are going to shrink anyway.

At formation, reserve only what you think you will need for the next 6 months or so. And before you start negotiating an equity round, shrink your pool to cover only what has actually been used. This will save you multiple percentage points on your cap table that could be worth millions in the long-run. Again, free money. Take it.

Legal AI and the Future of Startup Law

It’s been a while since I’ve written on legal tech and startup law, and given recent developments in AI, it feels like an update is in order. For context, I’m a Partner and legal CTO at Optimal, an elite boutique law firm focused on ECVC, M&A, and Tech Transactions for VC-backed startups. We’re about 20 lawyers, company-side focused, and negotiate across from all the top VCs (and lesser ones too) and the usual suspects of Bay Area and NYC-based BigLaw.

Over the past two years I’ve reviewed and/or tested a tremendous number of new AI-based legal tech products that have hit, or will soon hit, the market. The notion that the new generation of LLMs will make a material impact on the legal industry is accurate. The capabilities being released go well beyond the typical automation tools that law firms have been integrating over the past decade or so. Lawyers of all stripes are going to get a lot more productive.

However, what’s also become clear is that (predictably) shysters are coming out of the woodwork, exaggerating where this new tech is going and what can be done with it. For just one example of that, see this X thread. Given what I’ve observed over the years regarding the very short-term memory of the entrepreneurial ecosystem, I am not surprised at all that, thanks to AI, we are going to see the second, third, fourth, and on and on attempts at building the same flawed and untenable business model of some supposed new kind of law firm or legal service provider infused (somehow) so extensively with super-advanced technology that they dominate and transform the industry.

Alas, it’s just not meant to be, even if many of us tech-forward lawyers eagerly await every new tool that makes legal practice faster, smoother, more productive, etc. For those who don’t remember, Atrium was the most visible failed attempt at building the tech-driven startup law firm “of the future.” There are a lot of views out there for explaining why Atrium failed, some (in my opinion) more honest than others. I’ll summarize my views here:

A. It was controlled by a founder (Justin Kan) who, despite being extremely successful and brilliant in his own way, not only didn’t understand the real drivers of the elite legal industry – on the supply or demand side – but had no real interest in learning them. He assumed that his personal brand had enough gravitational pull to cover up impossible economics and a weak value proposition dependent on exaggerated technology capabilities.

B. Kan also assumed that his connections with Y Combinator, which funneled both cash investment and portfolio companies to Atrium, amplified his pull even further.

C. Not nearly discussed enough, Atrium’s organizational structure hid massively problematic ethical conflicts of interest that were a ticking time bomb. Company counsel, what Atrium purported to be, is supposed to help startups negotiate against VCs, serving as an equalizer for entrepreneurs and other common stockholders negotiating super high-stakes contracts and board decisions with financially misaligned elite counterparties. Yet Atrium was funded by the VC community, had VCs on its Board, and used all of those connections to funnel portfolio companies of its investors (including YC) into its client base.

In short, over-confidence and naivete, vaporware technology, and a go-to-market strategy dependent on pretending professional rules around conflicts of interest (for protecting clients) could just be hand-waived out of existence.

I could go on and on about how doomed Atrium was from the start, including how it depended on inexperienced de-skilled (read: no real partner oversight) young lawyers dreaming of VC-like payouts, and how its fixed-fee pricing model itself incentivized rushed work and not properly serving clients. But this post isn’t about Atrium; it’s about the people who are going to be using AI vaporware to try to resurrect it.

The narrative emerging today is something like “Atrium was just too early. Now, with AI, is the right time.” I’m sorry, but it’s really not. Even if the new generation of legal AI is more powerful than what Atrium was building – and it is – nothing coming down the pike of legal AI with the current generation of algorithms is going to be so transformational as to overcome all of the other flaws of the business concept.

At the low end of law, I can certainly see new legal AI creating something like a more dynamic version of LegalZoom, backed by highly de-skilled humans shuffling paper around in the background. But this wouldn’t be that transformational, because legal automation has already been eating up the bottom two quartiles of the legal industry doing work like small business law, simple divorces, estate planning, low-stakes dispute resolution, etc. It’s why the majority of law graduates today, even many from decent schools, can barely earn enough to pay their student loans. Sidenote: I think about half of law schools should just be shut down if they can’t find a way to operate at half the cost or less.

Startups even have their own LegalZoom: Clerky for the very earliest pre-seed stages, when everything can most easily be cookie-cutter. It works great in many (not all) very early-stage contexts, and many lawyers, myself included, integrate with it.

But unlike automation tools, we (VC-backed startup lawyers) play at the elite end of law, where the stakes are much higher, and the context on the ground is far more variable and complex.

The new LLM-based generation of legal AI tools are going to make elite lawyers much more productive. We already see it happening within our own firm, and it’s influencing hiring decisions, particularly on the junior side. They will make drafting, document review, research, and other lawyer work meaningfully more productive to the point of probably shrinking the footprint of elite firms, concentrating earnings further toward the top as the real “mandarins” of elite law don’t need nearly as much on-the-ground junior labor to serve clients.

But the notion that this new technology eliminates the need for those legal mandarins – the people who not only have the years of technical training, but also the personal understanding of the client and the mix of IQ/EQ to apply legal + strategic insight to unique dynamic human contexts, is preposterous.

There is simply no way to use AI (with presently attainable capabilities) to de-skill this top end of the industry such that a new organizational structure full of lower-paid “legal technicians” can actually deliver what clients want, at a quality level that doesn’t touch malpractice. This generation of AI will, as it plays out, be the equivalent of armies of tireless and supernaturally fast paralegals and junior lawyers, at a tiny fraction of what the human equivalent would cost.

Super valuable. But as anyone who has actually worked in legal (or the military) knows, even the largest and fastest infantry can be useless (even dangerous) without sufficiently smart hands-on strategic leadership. Interesting theoretical discussions on new AI algorithms point out that even if AI isn’t really “reasoning” in an abstract sense (it’s not), many lower-end white-collar workers aren’t either. I actually agree with that, even if some find it insulting (sorry).

But the elite lawyers in high-end law firms? They’re being paid to actually reason in complex high-stakes ways that no present AI breakthroughs anywhere on the horizon, in university or corporate research labs and certainly not in the market, can supplant. That being said, their work is also embedded in workflows that include numerous mundane (boring) tasks they’d gladly outsource to a diligent and reliable tool. This is why literally every single elite law firm is working on integrating AI right now.

Hardly luddites, they understand this tech is going to make their partnerships much more profitable, while improving efficiency for clients. It’s also going to make it a lot harder for junior lawyers to enter elite ranks. Such is life in the race against the machines, or perhaps better said: against the mandarins using machines.

The shysters that will be peddling AI to create pretend startup law firms and alternative legal services will be taking one of a few (predictable) strategies:

They will exaggerate the extent to which elite legal work is or can be standardized, because their unit economics can’t work without hyper standardization.

See Standardization and Flexibility in Startup Law. VC-backed tech companies going after 9, 10, and larger-figure opportunities are not coffee shops. They all operate in different competitive contexts, with different investors, different growth expectations, different team cultures, and all sorts of other contextual dynamics that influence their approach to legal and Board issues. This is why even at the earliest stages Founders CEOs talk to human lawyers.

You see this play out with other automation tools that have tried (and failed) to hyper-standardize startup law: see Carta. They know their technology breaks down beyond a small level of parameters, and so they try to get clients (Founder CEOs) to believe that narrow set of parameters is all they need. But the ROI – millions – for actually negotiating contracts (flexibility) is often so high that only the most foolish entrepreneurs trust their key decisions to an automation tool.

They will de-skill their rosters in order to create margins (potentially) attractive to investors, while covering up the (significant) drop in quality.

The most expensive people at any law firm are the Partners, just as the most expensive people at a hospital are the top doctors, all for good reason. They are the ultimate quality control in a service where low quality is extremely expensive, even dangerous.

Elite law firms are built, funded, and run by a hybrid form of capital – elite Partners. They provide the financial capital, but also the extremely nuanced technical knowledge required to train and run the operation: professional human capital.

If you just layer investors, like VCs, onto this model you are not going to have a competitive advantage in the industry. Too many mouths to feed, and not enough margin. So entrants, like Atrium, rely on de-skilling – eliminating real (highly skilled) Partners, and trying to convince clients this doesn’t result in a drop in quality.

What will a drop in quality look like? Rushed (or non-existent) negotiation. Poorly thought-out legal strategy. Technical errors that even the best LLMs just aren’t algorithmically capable of catching, but now without senior expertise to correct them.

Law firms are far lower margin relative to the kinds of tech products funded by VCs. There’s no real magic to trying to create VC-like margins in professional services. It requires getting rid of a lot of the most elite talent, because that’s where the money (rightfully) goes. In healthcare, this can work at the low end (de-skilled), like nurse practitioners using tech to treat sniffles faster and cheaper than GPs. In high-end specialty care, it can be (and has at times been) disastrous.

They will be funded by, and partner with, ecosystem players who profit from a drop in the quality of legal service provided to startups.

This is exactly what happened with Atrium, which relied extensively on pushing so-called “standards” created by Y Combinator, an accelerator and VC, because YC funded Atrium, sat on its board, and pushed a lot of its portfolio companies to use Atrium. Unsurprisingly, those standards were designed to benefit investors financially, which means they cost entrepreneurs significantly, far more (orders of magnitude) than whatever they “saved” in legal fees.

This is fundamentally what so many people in the startup ecosystem misunderstand about the role of company counsel, and some even put in effort toward ensuring entrepreneurs don’t understand it. Startup Law is, at a foundational level, adversarial* and (unavoidably) zero-sum. See: Negotiation is Relationship Building. Many people want to pretend otherwise, but at the end of the day institutional investors and common stockholders see the world differently, have different goals (often), and in an exit the money can only go into one pocket or the other.

One of the most clever things I observed about how Justin Kan structured Atrium is it offered his investors a double value proposition. The first was obvious: we’ll build this supposedly massively disruptive whiz-bang-pow legal tech firm. But the second one was more subtle: send your portfolio companies our way, and we’ll ensure they negotiate the “right” way and sign the “right” contracts – meaning the ones that make more money for and give more power to… those same investors.

A brilliant move, even if profoundly illegal (it flouted rules against conflicts of interest), and ultimately not enough to overcome the bigger business model flaws. Too many smart entrepreneurs – fools can always be tricked – saw through the charade and weren’t willing to bite. I expect the same to happen with the new generation of Atriums that will be attempted in the ecosystem.

Fiction: New LLMs will disrupt the legal industry, paving the way for entirely new organizational structures taking enormous amounts of business from the old guard.

Fact: At the bottom end of the market, new legal AI will incrementally allow existing automation providers to move up-market, perhaps from the 40th percentile to something like the 50th or 60th, but nowhere near the elite firms that are most-often talked about. At the high end, everyone and their mother is working to adopt legal AI into their existing firms. Elite firms will likely be smaller and more profitable, but still very much headed by elite legal mandarins wielding more powerful productivity tech.

Post-script on Healthcare: A brief point about the new generation of AI as it applies to healthcare, perhaps the field most often compared to elite law. From my vantagepoint, I expect AI to be much more impactful in the long-run to healthcare than law, for reasons I will call (i) less competitive subjectivity and (ii) more compartmentalized service.

What I mean by less competitive subjectivity is that in healthcare the goals are more straight-forward – treat/heal the patient, and the playing field is much more standardized: biology. More straightforward goals and (relatively) uniform biological science lend themselves much more towards the implementation of algorithms and high-volume data crunching. In elite law, however, the goals are much more subjective and contextual: there are multiple players, often with their own worldviews and strategic priorities. Further, every company is very different. Different people, industries, business models, etc. EQ and human-oriented “reading the room” play a much bigger role here, and I believe that limits how far technology – in its currently developing iteration – can go in displacing humans as opposed to augmenting their productivity.

By more compartmentalized service, I mean that healthcare breaks down into much more discrete tasks that can be walled off and modularized, outsourced entirely to third-parties and technology, and then re-integrated into the patient’s treatment without a problem. Think blood labs, diagnostic testing, monitoring, pharma, etc. Elite law just doesn’t work that way for a number of reasons – largely having to do with the more contextualized and subjective nature of the work, which amplifies the friction involved in integrating third-parties lacking the full context of the “patient” (the client). This is why in healthcare I expect to see a flourishing of third-party AI-centric services woven into the market, whereas in legal far more of the development will be tools for law firms.

* When I speak of ECVC law as being “adversarial” I mean in the technical sense. It is (obviously) not to suggest overtly hostile intentions or behavior, but to acknowledge openly and honestly that there are numerous zero-sum issues on which entrepreneurs (and their employees) are misaligned with investors, and each constituency is maneuvering in order to gain an advantage. When certain players suggest that it is “no big deal” for lawyers representing companies to have close relationships with the VCs investing in those same companies, I consider that little more than a rhetorical sleight-of-hand to give investors a tremendous negotiating advantage. See Negotiation is Relationship Building. 

Pre-Seed Funding with Post-Money SAFEs: Revisited in 2024

There are few markets that evolve faster than the world of startups, for unsurprising reasons. I figured it was time to revisit some of my writings on seed and pre-seed funding given how much the market has evolved since 2019-2021, when I last wrote about this topic in depth.

First, a brief history:

1990s – Long before the term “pre-seed” was even a thing, before the SaaS revolution made it even conceivable to start building a tech company with only a few hundred thousand dollars (or less), almost all early startup funding occurred as a complex preferred stock round; what now is reserved for Series A and larger seed rounds. It was a very different world from today.

Early 2000s  – Then convertible notes, once reserved mostly for “bridge” rounds in between preferred stock financings, started being used for seed funding; a natural evolution for rounds that were getting smaller and couldn’t justify full equity round negotiation time or costs. It worked relatively well. We also saw in this era the emergence of “series seed” preferred stock templates, a slimmed-down version of the more complex NVCA, that allowed you to raise a seed equity round for about 40-50% less in legal fees. These also got a decent amount of traction.

2013 – Then the Pre-Money SAFE, which is a convertible note without interest or maturity (effectively) was released around 2013. Founders started (candidly) abusing that instrument by raising Pre-Money SAFEs for years and years while obscuring the real economics behind what angel investors were funding. This was do-able because if your second, third, or fourth SAFE round has a pre-money valuation cap, but nothing capping the post–money, your newest investors can’t really know what % of the company their investment is buying without making you model out all the conversion math.

They could, for example, be putting in $1 million at a $49 million pre-money cap, which would suggest a $50 million post-money valuation, but they were in fact getting way less than 2% of the business because numerous unmodeled earlier SAFE rounds were pushing up the post-money. The post-money valuation is what really hardens a startup investor’s ownership percentage.

2018 – In late 2018 Y Combinator released the Post-Money SAFE. It flipped the economics of SAFEs to have a post-money cap, making the % purchased by investors far more transparent and immune to this issue of companies obscuring a deal’s economics. This was a good development, and the Post-Money model of valuation caps has since gained substantial market share.

But there’s one very big problem. The solution YC devised went much further – to the benefit of investors (including themselves) –  than was necessary to let investors know what % of the cap table they are buying on the day they invest. It further promised those investors complete non-dilutability of that percentage until the SAFE converts, including through subsequent SAFE rounds with higher valuation caps. This makes the Post-Money SAFE far harsher economically (to founders) than any other instrument in the history of startup finance.

YC itself has made an enormous amount of money by implementing this new math into the deal it gets with its own accelerator’s startups. I’ve seen YC companies start with giving 7% (the usual deal) to YC, but by the time the SAFE actually converts, after two or three more convertible rounds, the YC % is functionally equivalent to having received 10% or more years earlier. The smartest YC companies get ahead of this issue and raise a seed equity round as soon as they can after exiting the accelerator, cutting off this problem by converting all their SAFEs, but most don’t. It ends up costing them dearly.*

That’s the history.

2024 – Today, pre-seed and seed rounds have evolved such that you very rarely see an equity round that is smaller than $3-5 million. Many companies raise more than $5-10 million as convertibles (SAFEs or Notes) before doing an equity round.

Given the current landscape and investor expectations, we typically advise founders to not swim too hard against the tide, but also not mindlessly drink the overly “standard” Kool-Aid. Yes, templates like the Post-Money SAFE have gained significant market share, but what you don’t hear as much in the (simplified) data is that they are still being negotiated, particularly on the anti-dilution economics issue discussed above.

Many founders are very uncomfortable with promising their SAFE holders anti-dilution for years, given how equity rounds have been pushed further into companies’ growth. Six years after the Post-Money SAFE’s release I still have not heard a logical argument for why if a startup successfully closes $X million as preferred stock, all prior investors get diluted (what normally happens), but if it happens to be a SAFE round (same valuation, same amount raised), no investors get diluted. Why is the paperwork structure of the round relevant to whether investors get diluted?

Many smart founders modify the Post-Money SAFE (lightly) to address the investor-biased anti-dilution issue. I posted a public redline for this years ago, available here, along with other info on the economic implications of making this modification. Changing just a few words in the Post-Money SAFE can, for a company that achieves at least a $100 million exit, amount to millions of dollars in the pockets of common stockholders (founders, employees) instead of VCs or accelerators. Anyone who thinks at least trying to make this change isn’t worth it, out of some fear of “friction” – isn’t (IMO) defending their cap table enough.

Remember that this modification still promises investors the cap table percentage that the post-money valuation cap implies. If they put in $1 million at a $10 million post-money cap they are getting 10% today, effectively. What the “fix” does, however, is ensure that 10% shrinks pro-rata if you do a new SAFE round in 6-12 months with a higher valuation cap. Because that’s what would happen if you’d raised that $1 million as an equity round instead, or as a convertible note or pre-money capped SAFE. This idea of promising non-dilution to SAFE investors was completely novel, unnecessary, and introduced by YC, costing founders a lot of money. 

Of the founders I observe actually trying to fix the Post-Money SAFEs problems, a material number (but not all) have it accepted by their investors. They send a simple markup early in the process, a little discussion happens, and investors either OK it or they don’t. It ultimately comes down to leverage, which no lawyer can change for you.

For founders unable or unwilling to push for this change, other possibilities are:

A. At a minimum understand the anti-dilution issue, and factor it into your modeling of subsequent rounds. View future SAFE dilution as stacked on top of what was previously given to SAFE investors. The earlier SAFE holders are not themselves being diluted, which means you (the founders) are being diluted more. Your valuation caps in future SAFE rounds thus need to be higher to account for the more aggressive founder dilution.

B. We’ve also seen some founders, instead of tweaking the Post-Money SAFE, simply switch back to an old school pre-money formula. I personally find this a bit awkward in the context of investor expectations of 2024, but it certainly happens sometimes.

C. Convert your SAFEs as soon as possible. This is the advice I give to YC founders, and the advice I give to anyone who has raised a substantial amount of money on unnegotiated Post-Money SAFEs. Cut the anti-dilution off as soon as you can by raising a seed equity round, even a small one. See my article Myths and Lies About Seed Equity Rounds to dispel any boogeyman stories you’ve heard about how equity shouldn’t be used until Series A.

Those stories are often driven by investors holding post-money SAFEs, who make way more money staying unconverted and therefore undiluted even as you raise more money and increase in valuation. Investors can be great sources of advice, but they are not your best friends. Cap tables are unavoidably a zero-sum game, and investors’ advice is very often designed to maximize the amount they get. Watch incentives.

Startup finance continues to evolve. Templates are useful as starting points of a negotiation. They’ve dramatically streamlined the earliest stages of funding, as the number of pre-seed and seed funds (and deals) has exploded. But be skeptical of anyone suggesting that those templates are never negotiable. They most certainly (often) are. The tiniest amount of negotiation can save you and your team millions of dollars. Don’t foolishly leave money on the table.

If you’re raising a pre-seed or seed round, feel free to reach out to us. We often do virtual office hours to help founders better understand these granularities as applied to their market context.

Post-script: After you’ve closed on Post-Money SAFEs, shrink your option pool to save on dilution. Having an unnecessarily large option pool before your SAFEs convert is just handing extra equity to your SAFE holders for no good reason.

*YC will not modify their own Post-Money SAFE for their cohort of accelerator companies. The only way to minimize the economic harshness of its terms is to raise a small equity round as soon as possible after YC to convert their SAFE.