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:

1990sLong 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.

2013Then 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 postmoney, 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.

2018In 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.

*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. 

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.