Post Category → Legal Tech

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. 

Why BigLaw Over-Automates Startup Law

TL;DR: BigLaw’s very high operating costs require it to charge 3-4x of what its typical lawyers actually earn. This makes rates often stratospherically high. While billion-dollar companies that use BigLaw can afford those rates, early-stage startups often cannot. BigLaw is responding at times by hyper-standardizing and hyper-automating early-stage work. This has significant downsides, as companies lose out on flexibility, advocacy, and strategic guidance for very high impact projects, like financings. Much of this standardization ends up favoring VCs over startup teams. Elite lean boutique law firms offer an alternative approach, in which lower overhead allows for lower costs without requiring substantial inflexibility. In the end, this trend toward over-automation is leading many clients and lawyers to balk, and alternative approaches for achieving efficiency (while remaining flexible) are rightfully emerging.

Lawyers are not cheap. Elite lawyers – the kind with very extensive top-tier training, experience, and ability to handle high-stakes complexity – are in fact quite expensive.

Then again, elite human talent of all sorts is quite expensive. Top doctors make over half a million a year. Top software developers can make into the millions, and their “bugs” are much more easily corrected than bugs in contracts; which by design often can’t be “fixed” once they are signed.

I candidly find it amusing when “tech people” criticize elite lawyers for the amounts they earn, given what similarly elite talent in other industries (tech included) makes. If you’re expecting an apology, it’s going to be a while.

That being said, criticizing what people earn is not the same thing as criticizing what firms charge. There are in fact quite a few firms in “BigLaw,” including those who work with startups, where a lawyer charging over $1,000 an hour is in fact earning only a small fraction of that, maybe $200 or $250. “The beast” (the bloated institution) absorbs the rest. That, in my opinion as a leader of an elite lean boutique firm precisely designed to address this problem, is a very valid criticism.

Traditional elite law firms in “BigLaw” have virtually all designed themselves, with minor variances, around a similar high-overhead business model. They charge 3-4x+ what their typical lawyers are actually earning. That overhead pays for extremely posh offices designed to signal “prestige,” armies of non-lawyer staff, lavish events and other programming, as well as a small cadre of equity partners who absorb millions, sometimes tens of millions, in profits every year per partner without doing much of the actual billing.

The fact that BigLaw has entrenched itself in this way of doing legal business makes it very difficult, even impossible, to meaningfully address “efficiency” at an institutional level. It would require sacrificing too many sacred cows with political leverage in the firms’ bureaucracies. Thus when BigLaw does try to do something to become more efficient, or at least appear more efficient, its options are constrained. One option that is always on the table is adopting (often pricey) automation software, because it ostensibly allows charging less without actually having to do human legal work (contextual, flexible, strategic) any more efficiently.

Don’t deliver more efficient lawyers. Instead, make clients use dumbed-down, inflexible, and often quite clunky software. They can talk to professionals only once they can afford $900/hr for an associate and $1400/hr for a partner.

I’ve written about this issue before, such as in Vaporware Technology Won’t Hide Your Firm’s Business Model Problems (on Above the Law). Lean elite boutique law firms are about what I call substractive innovation. Finding efficiency by removing unnecessary (for clients) costs, and re-designing a firm’s operations around that leaner operating model. Yes, this does involve technology, but a particular kind of technology meant to replace unneeded overhead and traditional processes; not to simply layer on new software without otherwise changing much at all about the firm itself.

BigLaw, for the above reasons, is usually incapable of this kind of innovation. It virtually always leans more towards additive so-called “innovation” – buying more and more things that purportedly bring efficiency.

Tying this all together. BigLaw – which in 99.9% of cases works with billion-dollar multinational high-stakes projects for whom charging over $1,000 an hour is not a budget problem – has to charge a lot for its lawyers. 3-4x what those lawyers actually earn. The portion of BigLaw that actually touches early-stage startups – 0.1% of what BigLaw as a whole category really does – faces a problem. Early startups are not billion-dollar multi-national entities.

That’s a big constraint on what BigLaw as it relates to startups can really charge. Startups are constantly balking at what they are charged by BigLaw. The way some of BigLaw is addressing this is by removing their elite lawyers almost entirely from that segment of work. Automation – I would say over automation – combined with what is often called in industry circles “de-skilling” (delegating to lower-level staff).

BigLaw is thus heavily incentivized to over-automate Startup Law. As I’ve written before in many contexts, automation in law is not a free lunch. Not even close. It relies on heavy standardization and inflexibility for it to be workable at all. The problem is that a lot of what founders ask lawyers to do in early-stage Startup Law is extremely high-stakes from a financial perspective. Even minor tweaks to language in docs can have 8 to 10+ figure implications. We are not talking about parking tickets or coffee shops.

The extremely myopic way in which pockets of Silicon Valley have over-adopted YC’s Post-Money SAFE is a perfect example of this. Only now are many founders coming to realize how much of an “own goal” it was to let YC pretend their terms were founder friendly and “efficient.” In that article I show how literally adding a single sentence to the Post-Money SAFE can have tens of millions of dollars in improved economics for founders, and yet the vast majority of so-called “efficient” automated startup financing tools to do not allow for this tweak. People are pretending they are saving founders money. What they are really doing is “saving” a few hundred dollars (at most) in legal fees while letting VCs (including YC) take millions from startup teams.

There are countless ways in which over-standardization and over-automation in Startup Law are costing startups and founders enormous amounts of money. Every attempt to create a so-called “standard” term sheet for equity rounds ends up with VC-favorable economic and power terms that simply are in no way, shape, or form a universal “standard.” See also Standardization v. Flexibility in Startup Law.

Because VCs (and accelerators) are “repeat players,” whereas individual founding teams are not, they have the market leverage to heavily bias so-called “standards” in their favor. And the software companies intending to profit from all of this legal hyper-automation are happy to help them in the process. I wrote about the outsized leverage and influence that repeat players have in startup ecosystems, including over many law firms, in Relationships and Power in Startup Ecosystems.

These automated financing software companies – who need law to become hyper-standardized so that they can ever-so-generously step in to charge for the automation – are heavily incentivized to publish biased “data” about so-called “standards.” For example, they’ll build a software tool offering only 2 or 3 ways to do a seed funding, all heavily standardized and therefore inflexible. They’ll market this tool, and then publish data saying things like, “80% of seed deals are Post-Money SAFEs, and so it is a standard.” Actually (if you read the footnotes), 80% of seed deals on your half-baked automated platform are Post-Money SAFEs. Selection bias. That is not the same thing as saying 80% of all seed deals in the country or world are.

These tools are lying with so-called “data” to promote their own wares. For that, who can really blame them? Everyone’s got to make a buck. But let’s please stop pretending that they actually care about what’s best for startups, or their founders and employees. I don’t criticize people for talking their book. I criticize people for pretending to be far more benevolent and selfless than they really are.

Lawyers should be telling startups and their founders whenever they are facing these sorts of issues. They should be telling founders that the Post-Money SAFE is not a universal standard, and that many many deals end up customized, or even with entirely different structures, to make the economics better. They should be negotiating term sheets to better position the governance of their client, instead of letting some VC dictate what “standard” means. Instead, many of them are over-standardizing and over-automating. Why? Because they’re in BigLaw, and that’s what BigLaw does for startups.

Because of its institutional inability to actually do human legal work more efficiently (see above paragraphs), which involves assessing context, negotiating, tweaking, advising, etc., and the fact that Startups cannot pay over $1,000 per hour for extensive advisory, much of BigLaw is choosing to delegate the entirety of early-stage startup law to software. In my opinion, this is an abdication of the responsibility of lawyers to actually advise their clients as to what is best for them. If I were a paranoid BigLaw lawyer, I’d at least worry a little about the malpractice implications of practicing law this way.

On top of the fact that this is not actually in the best interests of startups or their stockholders, many lawyers are themselves starting to balk at the machine-like evolution of BigLaw’s way of operating. Boutique law firms, where the ratio of billed rates to lawyer earnings is more like 2x instead of BigLaw’s 3-4x (dramatic efficiency) are not just about lower rates. In many segments they are emerging as refuges for lawyers who want to step off the assembly line and actually think for their job.

When lawyers are able to charge, say, $500 per hour instead of $1100, they have time to actually negotiate for their clients. On top of this being good for the client (See: Negotiation is Relationship Building), from an intellectual standpoint it’s legitimately more enjoyable. Many ECVC lawyers prefer this way of practice over acting as if every deal before Series B should just be a cookie-cutter template.

The elite boutique law ecosystem (of which Optimal is a part) is thus emerging as a win-win countertrend to BigLaw’s tendency to over-automate and over-standardize. Many elite lawyers are tired of half-baked over-technologized (air quotes) “efficiency” that isn’t really efficient at all because of what the client loses. In moving to boutiques, lawyers get to drop their rates substantially without actually earning less. Clients get to pay substantially lower rates, while getting an actual elite human professional to help them navigate complexities and protect themselves; which many prefer over clicking a few buttons on software without ever being told what their options really were.

To summarize: the traditional cost structures of BigLaw require charging 3-4x+ of what their typical lawyers actually earn. This makes their rates, including for startups, extraordinarily high. Above $1,000 per hour in many cases. Sometimes $2,000+ per hour. Startup clients, who do not fit the billion-dollar mold of BigLaw’s average client, obviously cannot afford stratospheric legal bills. BigLaw is responding by accepting hyper-standardization and hyper-automation for its earliest stage work. Clients spend more and more time interacting with junior professionals and software that operate only in very narrow, inflexible lanes; depriving clients of real advocacy or negotiation on high-stakes issues. As a result of all this, inexperienced startup teams are increasingly pushed into these myopic inflexible fundraising approaches that are costing them enormous amounts of money and governance leverage.

There are ways to avoid this problem. The one I’m obviously an advocate for is to move a lot of this legal work to leaner elite boutiques. Some of the top boutiques in ECVC can deliver real legal horse power, especially in earlier-stage deals (pre-unicorn), at half the rates of BigLaw.

There’s another option: if you absolutely are going to use BigLaw, let them charge you for what the work really takes. Why pay BigLaw at all if you’re not using the real legal talent it is designed to house? If you’re raising a $75 million equity round, yeah, you’re going to pay a few hundred thousand dollars in legal fees with BigLaw if you let them actually do their job. As a percentage of the actual raise, it’s really not that much (under 1%). The alternative – over-automation and over-standardization – will be far worse.

If that doesn’t work for a $5 million or $15 million round, then again I suggest looking into elite boutiques. Their lower rates, but still elite rosters, will produce lower legal bills without compromising on the quality of the actual advisory you’re getting. See How Much Seed Rounds Cost – Lowering Fees and Expenses Safely to understand why boutique law is an increasingly popular option among top startup teams for earlier financing rounds. Boutiques are not doing pre-seed deals all day. We have clients closing Series A, B, C, even later, and exiting at 8-9-figure valuations. As I often say, the B in BigLaw is for billions. There’s a lot that happens before billions.

Straw-man prevention disclaimer – Let me be very clear here. I am not just a Partner at Optimal. I am also its Chief Technology Officer. I work with a lot of legal tech startups. I love legal tech, and I even like targeted, thoughtful automation. I’m particularly interested in upcoming ways to integrate AI to enhance lawyers’ productivity.

Some people with very loud microphones like to pretend that the legal profession is full of nothing but luddites who want to milk the entire world for fully bespoke, terribly inefficient work product. In startup ecosystems, this attitude is most often peddled by (i) VCs who want your lawyers to shut up, because when lawyers shut up VCs get what they want, and (ii) software automation tools; because they want you to use their inflexible software instead of an actual human.

What I am advocating for here is a more balanced perspective on when automation really is in the best interests of legal clients, and really is streamlining things, relative to when it is hiding all sorts of biases and costs because the real driver isn’t what’s best for the client but some extraneous factor like institutional constraints. I’m a big fan of automating basic option grants, which no serious professional wants to waste their time on anyway. But raising millions or tens of millions of dollars, and setting permanent power & governance terms that will influence huge segments of the modern economy? Hold the F up.

As I wrote here, the “values” of the legal industry and the software industry are very different, and both serve a very important purpose in the economy. In legal, it’s expertise, context, flexibility, negotiation, leverage, compromise, trusted advocacy. It’s about having a perspective, and pushing for it, while the other side does the same.

There can be no single answer or “standard” in this value structure, because the decision-makers and process for setting it are suspect, as conflicts of interest and subjectivity abound. Companies are different. Investors are different. Goals, industries, values all vary organically across institutions and contexts. It’s contextual “truth” arrived at via a decentralized adversarial process, as opposed to a centralized proprietary one. This concept is not entirely alien to many engineers.

In software, it’s broadly about standardizing, automating, universalizing, cutting costs and centralizing data. It’s about scale and speed, reducing “friction.” In this worldview, customization and “verification” via independent review is seen as inefficient and pointless. But is it always? When the stakes are really high?

Analogies about making private startup equity operate like “frictionless” liquid public markets are spectacularly flawed. In the latter, the transactions are impacting small percentages of the company’s capitalization, and rarely altering their fundamental governance. What happens in a startup’s earliest days sets the stage for the company’s entire growth. The present dollar value may be small, but the derivative long-term impact is massive. Post-IPO, very little of what’s being negotiated fundamentally changes anything.

Nowhere am I saying here that the legal industry’s values should take full precedence over those of the software industry. Again, I’m a big fan of productivity tools in legal. We just need to avoid myopia in letting the software industry’s values (automation, standardization) steamroll over legal’s as it relates to high-stakes legal work simply because clients think (wrongly) that they have to use BigLaw, and BigLaw can’t make its actual lawyers cheaper. Automation and standardization can be good. Automating and standardizing everything, because we won’t consider alternative possibilities for achieving efficiency, most certainly is not.

The Open Startup Pro-Forma Capitalization Model

TL;DR: In the earliest stages of a startup, paying for a proprietary cap table tool, or simply dealing with the hassle of a 3rd-party intermediary software layer for modeling your capitalization, is not really necessary. We’re publishing the Open Startup Model, an Excel-based “open source” cap table and pro-forma that startups and their lawyers or other experienced advisors (if they don’t already have their own tools) can use for free. It’s based on the pro-forma structure we’ve used for hundreds of deals, and is flexible, editable and auditable.

Background reading:

In the beginning, there was Microsoft Excel, and it was good (enough).

For decades, startup cap tables and pro-forma financing models were maintained on Excel. It wasn’t perfect (nothing is), but it worked well enough. Then as the ecosystem matured, we saw the emergence of specialized cap table software, like Carta (pricier incumbent) and Pulley (leaner alternative). These tools make a lot of sense at moderate (not low) levels of cap table complexity – based on our experience at Optimal, typically around Series A or post-Seed.

But somewhere along the way some founders got the impression that these tools might be needed as early as the incorporation of the company, when there are only a handful of people on the cap table. The argument, certainly made by the cap table software vendors themselves, is that Excel is too clunky, and too error-prone. There is also a land grab dynamic here, in that it isn’t necessarily profitable for these tools to have tons of very small companies on them, but they have to build super early-stage offerings to prevent their competitors from owning the pipeline. There’s no simple way for the tools to agree to leave young companies alone, so we get these silly value-destroying attempts to onboard everyone.

All of this is, candidly, nonsense. I’ve seen seed-stage companies spending thousands of dollars a year and getting absolutely nothing extra of value that they couldn’t get from a basic excel spreadsheet maintained by someone moderately competent.

What makes old-school Microsoft Excel a still-used tool in startup finance is its flexibility, auditability, simplicity, and affordability (free, essentially). It’s really only once you’ve crossed about 20 cap table stakeholders that in our experience, as counsel to hundreds of VC-backed companies, a third-party tool starts to make sense. Before then, I often see more mistakes when founders try to use an inflexible outside tool than when they simply collaborate with a sharp outside advisor to keep things clean and simple on a spreadsheet.

That being said, one thing that has happened is the complexity of seed funding instruments has grown over time. See the Seed Round Template Library and Seed Round Educational Articles.

In the really early days, before the entire seed ecosystem even existed, most financing was in equity rounds. But as the SaaS revolution got started, financings both shrunk in size and exploded in volume, with equity rounds no longer making sense in many cases. So we got seed-stage convertible notes. Then we got notes with pre-money valuation caps, discounts, or both. Then you got pre-money SAFEs. Then you got post-money SAFEs, and various flavors of them. Then you got post-money convertible notes. Time-based discounts and caps. Milestone-based caps. Don’t forget friends & family SAFEs, which are slightly different. Oh, and let’s not forget seed equity v. NVCA equity. Even within these categories there are various nuances and flavors.

It is not surprising to us at all that the ecosystem has resisted all attempts to hyper-standardize fundraising instruments, notwithstanding the valiant (even if self-interested) attempts by high-profile VCs or software tools to centralize all fundraising terms. This reflects the decentralized reality of the startup ecosystem. Startups are not uniform commodities, nor are their investors. In the latter category, think of bootstrapping, friends and family, angels, super angels, angel syndicates, pre-seed funds, seed funds, family offices, crowdfunding, accelerators, VCs with seed fund arms, strategic investors.

Couple that organic diversity on the investor side with the extremely diverse industries, business models, geographies, team compositions and cultures, risk tolerances, and exit expectations of startup companies. Do we really expect all of these sophisticated business people playing with millions and tens of millions of dollars, gunning for hundreds of millions to billions, to fit into one or two template financing structures because some VC, accelerator, or cap table software says they should? Because of some childish aversion to actually reading a contract and tweaking a few terms?

The only people misguidedly trying to hyper-standardize this complex ecosystem are (i) specific VCs who profit from controlling terms, with their preferred templates, and (ii) specific software companies (often funded by the aforementioned VCs) who want to build some centralized proprietary tool on which all startup financing would at some point become dependent (surely with juicy margins to them as a result). Neither of these types of rent-seeking gatekeepers are looking out for the ecosystem itself, and its diversity of preferences and priorities; certainly not for entrepreneurs. They’re looking out for themselves (for which, as market actors, I don’t fault them).

Many entrepreneurs and startup teams in particular have lost huge amounts of equity and money by being misled into signing inflexible contracts that they thought were “standard,” but really aren’t. The smallest bit of tweaking and negotiation can produce enormous differences in financial outcomes.

Given the diversity of businesses and investors in the startup ecosystem, which inevitably leads to a diversity of funding instruments, flexibility of any viable wide-reaching startup capitalization model is key. That’s why MS Excel still matters, because of how flexible it is. Flexible and transparently auditable in the way that open source code is flexible; and proprietary “no code” tools are not.

Led by a Partner colleague of mine, Jay Buchanan, we’ve published the Open Startup Model. Free, Excel-based, flexibly customizable and auditable, even “forkable” if others want to iterate on it. “Open Source” effectively. It’s based on the same model we’ve used hundreds of times at Optimal, with clients backed by elite VCs like a16z, Sequoia, Accel, Khosla etc. and dozens of “long tail” funds across the world as well. It works from the formation of the company through Series A (or a Series Seed equity round).

Jay will be writing periodically at OpenStartupModel.com, with info on how to take better advantage of it. Just like open source code isn’t intended to be handled by untrained end-users, this model is not intended to be entirely self-serve by founders. We are modeling very high-stakes and complex economics here. Rather, it’s meant to be a potential starting and focal point for various experienced market participants (including lawyers) to work with founders on.

Just as we are big believers in the thoughtful integration of elite legal industry values and lean tech values, we think an “open” startup ecosystem, with its enormous organic diversity of market players, is far healthier and more sustainable than misguided attempts to centralize everything behind a handful of rigid proprietary structures and tools. An open pro-forma model, together with our open-source contract templates that we’ve published here on SHL, is part of that vision.

In that vision, it’s not necessary that dozens of different actors come to agree on some “standard.” These templates and models will look extremely recognizable to all the serious law firms and other key players in the market. That alone saves time if startups or lawyers want to use them, and as institutions get more “reps,” efficiencies follow as institutional knowledge is gained.

We hope everyone – founders, lawyers, investors – will find this helpful, and welcome any feedback on improving it; particularly if “bugs” are found. As a final legal tech tip for lawyers, the ability to redline excel models, much like how you redline contracts, is super important and improves efficiency in reviewing model changes. Litera Compare is our favorite redlining tool for excel files.

As a separate tip for startup founders, if you need a 409A valuation, but don’t want to pay extra for a third-party cap table tool (because Excel is fine for now), Eqvista and Scalar have lean 409A-only (no extra software) offerings.  Some seed-stage companies go this route, combining Excel and a 409A valuation without the extra bells and whistles of the pricier cap table tools, until their cap table has grown more complex (typically post-Series A).

Finally, once you get to the point of needing to onboard to Carta or Pulley (if you’re successful, you will get there eventually), the following may be helpful for saving on their costs.