Congratulations to the enterprise AI company that just raised another nine-figure round to solve a problem software is supposed to solve by itself: getting humans to use the product.

You know the one. Won’t name it. Don’t have to. You’ve read the press release — “autonomous,” “agentic,” “category-defining” in paragraph one, and then, a few paragraphs down, where the money is actually going: hiring an army of engineers to sit inside customer offices and manually make the “autonomous” thing behave.

Nothing says “we’ve built the future of work” quite like raising half a billion dollars to hire more people to do the work.

The business model, decoded

Here’s how it works, in case the deck was too artfully vague:

1. Sell the customer an “AI platform.”
2. Discover the platform doesn’t actually do the thing on its own.
3. Send in the forward deployed engineers: sharp young people with CS degrees who now spend six months hand-building the workflow the website implied already existed.
4. Bill the customer for “software.”
5. Book it as ARR.
6. Raise a bigger round because “ARR go up.”
7. Repeat, forever, with an increasingly large and increasingly expensive engineering org standing between the product and the promise it made.

This is not a flywheel. This is a payroll with a pitch deck.

And the industry has stopped even pretending otherwise — it’s fundraising on it, loudly.

pledged valued at $10 billion, with another $4 billion from ,, , and . The vehicle, DeployCo, has been with more than $4 billion in investment.

Meanwhile, job postings for “forward deployed engineer” are up somewhere between 800% and 1,000% year over year. Lightcast data reported by from January to August 2026. data carried by put listings up more than 800% from January to September 2025, and data from 643 in April 2025 to 5,330 in April 2026. Total comp is pushing past $300,000 in the U.S. list at $280,000 to $320,000 base pay and OpenAI at $185,000 to $300,000 base, plus equity. Fortune reported some Anthropic roles reaching $400,000 in total compensation.

Somewhere, a VC is calling this “operating leverage” with a completely straight face.

It is not operating leverage. It’s a staffing agency that learned to say “agentic.”

The tell

Ask the one question the pitch deck conveniently never answers: “If you pulled the embedded engineer out tomorrow, does the customer still get what they paid for?”

If the honest answer is “well, no, but the ARR is real” — that’s not product-market fit. That’s people-market fit, and people-market fit has a brutally unglamorous ceiling: You can only hire humans so fast, and you can never hire them cheap enough to earn a software multiple. Every new logo doesn’t get more profitable to serve. It gets another headcount request.

Two companies, same $20 million ARR. One needs 10 engineers to keep the lights on. The other needs 100. Both slides say, “AI software company.” The difference shows up in gross margin, cost to onboard the next customer, and whether that cost falls as the company scales.

The bill always comes due

Here’s the thing about people-market fit: it feels great right up until someone asks the unfashionable questions: What does it actually cost, fully loaded, to onboard the next customer? Does that number go down as the company scales, or does it just grow the org chart? What happens to gross margin if the first year growth slows and the headcount can’t hide behind hypergrowth anymore?

Companies funding their FDE armies with fresh nine-figure rounds are betting nobody asks these questions until after the round closes and the confetti is swept up. That’s a fine bet in a hype cycle. It’s a terrible one in a market that’s about to start reading the fine print.

Because eventually, someone always reads the fine print. A CFO builds a cost-per-deployment model. A CIO benchmarks time-to-value against three vendors instead of trusting one demo. An investor finally does the unglamorous work of separating software ARR from human-powered ARR on the same balance sheet.

The distinction buyers and investors can test is on the numbers. Software ARR should get cheaper to deliver as it scales. Human-powered ARR does not. OpenAI guaranteed the private-equity backers of its deployment vehicle an annual 17.5% return over five years, which is a different structure from a growth thesis.Âą

So no, your AI isn’t autonomous. But your business model might be — autonomously transferring the cost of a services company onto a software valuation, for as long as the music plays.

Enjoy the round. Hope the org chart was worth it.

, the co-founder and CEO of , is an entrepreneur and product leader with more than 20 years of experience across cybersecurity and AI. He has built three generative AI companies, including one that reached unicorn status. Gurtu is known for turning advanced AI into scalable, real-world platforms, and previously contributed to successful exits, including acquisitions by , and , and a public company, . He holds a master’s degree from the and CISSP certification.

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How would you handle a junior employee questioning the way you’ve always done something? Might you roll your eyes and dismiss their comments as naivety? Or would you indulge their curiosity?

As AI has made knowledge accessible on a scale never seen before, companies are becoming leaner and operating faster. What once took a large team months to do can now be done by a handful of people in a few days.

It is undeniable that autonomous systems are changing the way we work. In the small and dynamic teams of the future, choosing the right humans to direct your AI systems will become make or break for a company.

As a six-time founder, I’ve learned the best workplaces are the ones where questioning things is the norm. Here’s how to build a team that questions orders as much as it obeys them.

AI by design

“AI by design” doesn’t only mean building the right autonomous systems. It’s also about creating autonomous humans. You need to trust the human in the loop as much as you do the technology. The team around you ultimately shapes the company in ways you can’t control. So surrounding yourself with people you trust to make decisions when you’re not in the room is critical to success.

The nature of job roles is changing. A job description can be totally different from the one advertised by the time you’ve found a candidate, and a six-month roadmap is outdated by the time you’ve finished drawing it up.

The has stated that as AI reshapes the workplace. Hiring for a fixed set of skills won’t move the needle. The people worth investing in are those who are able to learn what comes next.

Hire for curiosity

Curiosity is the best trait you can hire for. When I look at a CV, it’s not just experience or academic credentials that draw me in. I look for what people have built on the side. What have they made on their own initiative?

Hire for curiosity, and you’ll create an environment where people are willing to throw new ideas around and challenge outdated ways of doing things. If your team is worried about saying the wrong thing, they won’t end up saying the right thing either.

In a world where technology is turning everything on its head, the companies that will thrive are the ones with curious people who are able to adapt to change quickly.

Hand over real responsibility

Employees with autonomy operate faster. They make better decisions because company vision is not abstract to people who are given real responsibility to drive it. Being involved in strategic direction stitches an employee into the fabric of the company and keeps them engaged.

Trust your employees to know what isn’t working. Allow people to pursue new ideas and reinvent things. Your employees are likely to spot potential problems before you do when they’re closer to the product. Make sure your team has the autonomy to try to fix them before they take hold.

Boredom is a big business risk

As companies become smaller, employee retention is more important than ever. Losing your best people is costlier when you have fewer of them to begin with.

The effects of a bored employee surface quickly in a small team. Boredom makes talented people a little bit slower, and a lot less likely to try the difficult thing.

The challenge for modern leaders is keeping your team engaged and interested. A bored employee is more likely to be swayed by a flattering recruiter.

Make sure to invest in development, keep your team learning, and always encourage curiosity. Give people autonomy and responsibility from the beginning, and boredom has nowhere to take hold. The mentality of risk and the drive to challenge something outdated is what you need to succeed in the changing work environment.

Dare to be a beginner, and teach your team to do the same. That junior employee questioning how you’ve always done things could be the most valuable person in the room.

is co-founder and CEO of Stockholm-based , an agent-driven, game-based learning platform. He has experience building, exiting and scaling digital companies across 70 countries. Uniplay is his sixth company to date.

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A first venture usually follows a well-worn playbook: a gap in the market, obsessive refinement of concept and pitch, eventual conviction that the solution is as bulletproof as it is revolutionary.

Then, the dreaded phase of product-market fit. Instead of building the future of an entire industry, you find yourself forced to focus on a narrow use case and spend the first invaluable years proving that your idea can make money and scale. The grand vision gets put on pause.

For most founders, this journey is the only one available. After all, investors are betting on someone who has never built a company before, so a small check and a narrow product limit what everyone stands to lose. But some ambitions need total commitment from the start, and having built a company before helps when taking them on.

Lessons from the front line

After selling my first venture, , to for €1.8 billion (about $1.9 billion USD) in 2022, I found myself in a new position — and it wasn’t horizontal on a sun lounger. My co-founder and I had a real war chest of our own, and a brand-new entrepreneurial bug. For the first time in our lives, we had the experience and the resources to undertake something truly world-changing.

Compliance is a gauntlet that any founder will be painfully familiar with. Scaling Tink across Europe, to 700 people operating under a host of regulators, my team and I got used to tearing our hair out over small wording tweaks, reviews that dragged on for months, and perpetual uncertainty that stopped us from iterating fast and boldly. Products were often delayed by months, a slip that meant the world in an industry moving as fast as ours.

A problem with too many heads

Compliance was a problem that could never be solved piecemeal. Every company’s obligations depend on a million different factors, each of which sits in a different part of the business that rarely talks to one another.

Legal tracks regulations; another department oversees how they are implemented. Product teams make their own calls on features, and yet another team opens a case to check whether it was compliant. Policies, standards and regulations belong to other departments entirely, and those are usually the part of a silo a compliance startup builds for — a clear buyer and a budget.

“Solving compliance” was a mission akin to fighting the Hydra: cut off one head and two more grow back. There is no minimum viable product here. Fixing one head changes nothing. What it takes is a maximum viable product from day one.

Why the second time is different

In recent years, we’ve seen a series of inspiring examples of successful founders coming back to take on new problems. Stockholm knows this well: alumni of and have gone on to found and back a long list of new companies, using the credibility from their first successes to try something harder.

The second time around, capital and access both come easier. A successful first exit opens doors to talent, partners and investors that we simply didn’t have with Tink. It is a fantastic opportunity, and one I’m grateful for. You get to bring every lesson from what went well and what went badly, and you start with a real tailwind when people want to work with you and back you.

Money also means you can fund the full build yourself, so no investor asks you to shrink the idea before you’ve tested it.

Maximum viable product

Experience and capital used to get you only so far. Ten years ago, building something this broad would still have needed hundreds of people of various backgrounds, and many years. Language models have changed that. Our team today is 22 strong and growing, and ships at a pace I could only have dreamed of when we first built Tink.

We also feel we’ve grown thicker skin from the bruises of our first 15 years as entrepreneurs.

You know the setbacks are coming, and you know that a venture is never a one-man sprint but a team marathon. None of that guarantees success. But it’s a good place to start if you want to stand your ground and build your biggest vision yet.

is the CEO and co-founder of , the Stockholm-based AI-native compliance company that came out of stealth in September 2026. He previously co-founded the open banking platform in 2012 and led it as CEO through its growth to a multimarket operation with around 700 employees before its €1.8 billion acquisition by in 2022.

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You have likely never heard of . You should have.

Over the past decade, Tosin and his team built into the operating system for more than 6 million Nigerian businesses, , or .

As a Nigerian American, I’ve witnessed my father make trips to Western Union to send money back home for decades, and I experienced Nigeria’s fee-laden payment system when visiting the country. Moniepoint is transforming that system.

Moniepoint is not alone. , , , , Ěý1 — these are companies most Americans have never heard of, despite them being worth several tens or hundreds of billions, following the trail blazed by , and .

These are super apps that bundle banking, commerce, ride-hailing and bill pay into one trusted application. The idea never took hold in the U.S. for one reason: trust is cheap here. With , a specialist app inherits the credibility of the financial system. Where trust is cheap, there is no need for a super app.

Build trust first

In emerging markets, trust is the whole problem. Four conditions tend to precede a super app: High mobile penetration, which makes distribution cheap; weak incumbent competition; poor existing financial services; and the condition most investors screen past, a financial crisis severe enough to strip incumbents of legitimacy. These populations are not merely underbanked. They were harmed, and the institutions that harmed them still hold the market.

Brazil froze roughly 80% of bank deposits and financial investments for 18 months in 1990 in an effort to break hyperinflation. The banking consolidation that followed left five banks and . That was the void Nubank was born into.

Kazakhstan went through it twice: savings erased by inflation in the thousands of percent when the ruble zone collapsed in 1993, then a 2007–09 banking crisis in which the country’s largest bank, BTA, holding roughly a quarter of the system’s assets, Kaspi grew into that void.

Southeast Asia’s 1997 crisis was harsher still. Indonesia closed 16 banks in a single announcement, the %. Two decades later which enabled Sea to build and into that gap.

Kaspi also answers the objection I hear most from American investors, which is that these markets are too small to produce large exits. Kazakhstan has only 20 million people, and according to company , around 14 million — nearly 70% of its population — use Kaspi. The . It earns . Depth of spend, not population, sets the ceiling.

Compare Nubank to . Nubank has 14x the customers, to , about 7x the revenue and a market capitalization more than 6x larger. Nubank . A technology applied in an overlooked market with a large unaddressed pain point can build a bigger and more defensible company than the same technology applied in a rich one.

Screen for the four conditions and a few markets stand out as places where the next super app could emerge:

• Bangladesh: , with the government now promising to pay 7.5 million savers whose money is gone.
• Egypt: Repeated devaluations of the pound between 2016 and 2024, shrinking savings held at banks the state itself owns.
• Vietnam: after its owner was arrested in a $24 billion fraud.
• Pakistan: , then government-built rails and a national ID that makes onboarding nearly costless.

One boundary condition: The crisis must be severe enough to delegitimize incumbents but contained enough that the currency and payment rails still work.

The first generation of super apps created enormous value for the investors who backed them early. In 2001, the South African media company paid roughly $34 million for a 46.5% stake in Tencent, and . ’s investment in Nubank’s $2 million seed round, combined with its lead Series A investment, was worth $7 billion at the company’s IPO.

The second generation is scaling now. The third will be built on stablecoins and AI technologies, in Abidjan, Buenos Aires, Karachi and Lagos, by founders like Tosin Eniolorunda who will play an increasingly important role in the growth of emerging market economies.

Ěý is co-founder and managing partner of , where he oversees the firm’s investing strategy, governance and compliance, with a focus on fintech and enterprise technology. Since co-founding 645 Ventures in 2014, he has invested in and partnered with companies including , , , , and . Previously, he was an investor at , where he invested in 19 companies and had nine exits representing more than $9 billion in exit value.

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In 2021, putting AI on a slide could get you funded. Small and mid-sized businesses were eager to be early adopters, and they bought fast. I watched companies secure customers, raise money, then struggle to keep anyone using their products. Retention fell off a cliff.

Many of those products were generic: They did what traditional software already did, with AI fairy dust sprinkled on top. Others saved a bit of time on something nobody’s job depended on. A 20% improvement on a noncritical task makes for a nice demo and a dead renewal.

There were never easy AI wins, even if there was easy money going around. The market is now correcting for that. Companies delivering meaningful value are growing faster than anything I have seen in enterprise software. For investors, the question is which of these companies can keep their customers — and whether the coming IPOs will expose the difference.

What makes an AI business defensible today

Before my co-founder and I wrote a single line of code, we interviewed more than 900 mechanical engineers, from juniors to VPs. We asked where their hours went and which of those hours they would pay to get back. Those 900 conversations shaped how I think about building an AI business.

First: the improvement has to justify the investment. Saving 10% on an occasional task will rarely change how a company operates. Reducing a business-critical process from weeks to minutes, or saving serious money, will.

Second: domain expertise. Frontier models are becoming infrastructure. Access to a good LLM is available to almost anyone with an API. The commercial opportunity lies in understanding an industry well enough to solve problems that generic tools cannot.

Third: proprietary context. In terms of engineering examples, every company that builds physical products has accumulated decades of engineering knowledge. Much of it remains buried in old drawings or locked away in the heads of experienced employees. That knowledge is absent from a foundation model’s training data. An AI product that cannot access it will struggle to become essential for the business. The advantage grows as the product becomes embedded in the customer’s workflows and replacing it becomes costly.

What this means for funding and IPOs

The upcoming AI IPOs will put these business models under much greater scrutiny. Public investors will examine net revenue retention and gross margins, assessing whether rapid growth is able to translate into a sustainable business. They will also want to know whether each deployment becomes cheaper to support as the company grows. The standards they establish will influence what private investors expect from earlier-stage AI companies.

I can already see the change in my own fundraising conversations. A few years ago, $1 million in ARR was a milestone. In the AI era, a new product can reach $1 million in ARR in about a year, and shut down a year later. Now ARR alone no longer tells investors enough.

What investors keep asking about is expansion. They want to know whether customers are increasing their spending after the initial deployment. Expansion is the closest thing we have to proof that a product has changed how an organization works: customers have experienced its value and committed more of their own budget to it.

Over the next 12 to 24 months, I expect capital to keep flowing to companies that combine deep industry expertise with significant improvements in business-critical work and access to customers’ proprietary knowledge. They may grow through hands-on deployment rather than viral self-service, but they can expand inside accounts that trust them.

Companies whose products are thin layers over someone else’s model, with impressive customer lists and retention charts nobody wants to show, will find their next funding round much harder than the last one. I would rather grow fast and steady for five years than spectacularly for five quarters.

is the founder and CEO of , the first AI for mechanical engineering — a large mechanical model for physical product design. He conducted AI and mechanical engineering research at as a Fulbright postdoctoral fellow and became the youngest Ph.D. graduate in the history of the Farid has built a community of more than 60,000 engineers and supports underserved youth through his nonprofit initiative.

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For founders raising venture capital, the instinct is often to get the money, as much and as quickly as possible. And it’s no secret that fundraising can be grueling, especially after dozens of pitches, follow-ups and rejections. It can almost feel as though a term sheet is the validation and that the hardest part is finally over. But founders also have to pay attention to far more than the size of the check or the valuation attached to it.

They should be asking a much bigger question: Who exactly am I allowing onto my cap table and to own a piece of my company?

Venture capital isn’t a loan. Investors receive ownership in the company in exchange for the money they put in. As startups mature, some investors may ultimately gain board seats and significant influence over decisions ranging from fundraising and acquisitions to leadership changes.

As an early-stage investor, I always advise entrepreneurs to recognize that you’re not simply raising money, you’re also deciding who will sit at the table you’re building.

That means the goal shouldn’t be assembling a cap table filled with whoever was willing to invest. The strongest cap tables are intentionally constructed around investors who bring different forms of value.

Here’s what founders should look for in their investors.

Investors who can open doors you can’t

Every founder has heard that investors should bring more than money. The phrase has become such a fundraising cliché that it can lose its meaning. If I were a founder building a venture-backed company, I would ask myself of every potential investor: What can they materially help this company accomplish over the next 18 to 24 months?

For a fintech founder, the answer might be introductions to banks, regulators, payment companies or potential enterprise customers. A healthcare investor might provide access to hospital systems, insurers, or executives who understand lengthy procurement cycles. An investor in consumer products may understand distribution, retail partnerships, or customer acquisition.

Founders have to seek out strategic investors: People or institutions with industry expertise, relationships and resources that can help founders solve problems capital alone cannot.

This becomes particularly important when something goes wrong.

When growth stalls, a key hire leaves or a partnership disappears, the investor who can introduce five potential customers on Monday is significantly more useful than one whose primary contribution was wiring money six months earlier.

Founders therefore shouldn’t simply ask investors about their portfolio. They should conduct the due diligence in the same way that investors diligence them. Ask what their platform support typically entails. Talk to portfolio founders. Find out whether the investor was useful when the company struggled.

Reputation and access should be proven, not promised.

Investors who understand your exact stage

A billion-dollar growth investor may have an impressive résumé. That doesn’t necessarily mean they understand how to help a company with six employees, an unfinished product, and nine months of runway. Startup problems change dramatically by stage.

For example, at pre-seed, founders may still be validating the market and searching for product-market fit. At seed, the challenge might become hiring, repeatability and proving customers will consistently pay. By Series A, investors may expect evidence that the company can scale what is already working. That makes stage-specific investors particularly valuable.

Investors who repeatedly work with companies at the same point in their development have seen the movie before. They know what metrics the next round of investors will examine, which mistakes frequently derail companies, and what milestones founders should prioritize before returning to market. They also have something founders won’t necessarily find in a database: current fundraising intelligence.

Forward-looking business intelligence can complement that firsthand perspective. A platform like combines data on past financings with predictions and insights designed to surface company momentum and likely future developments. Investors actively evaluating companies at a particular stage can add another layer of qualitative context: what the market is rewarding right now, how expectations are shifting, and which milestones founders should prioritize before their next raise.

The best investor isn’t necessarily the person with the biggest fund. Sometimes it is the person who knows exactly what your company needs to look like 12 months from now.

At least one investor you can tell the truth

The most overlooked investor may also be the most important: someone the founder actually trusts.

Startups inevitably encounter moments when things go wrong. Revenue misses projections. Co-founders disagree. Executives quit. Products fail. Fundraising takes longer than expected. In those moments, founders need someone they can call before they have the polished explanation prepared. Which is why founders should have at least one investor who “gets” them, not simply their market or business model, but how they operate as a person.

That relationship can be especially consequential for founders navigating rooms where few investors share their background or experiences. A trusted investor can help interpret dynamics, prepare for difficult conversations, and provide candid advice without making every mistake feel like an indictment of the founder’s ability to lead.

Founders should pay attention to how investors behave during fundraising because those interactions offer clues about what the relationship could become. Do they listen? Do they respect your judgment? Can they disagree without becoming dismissive? Do portfolio founders call them when things are going badly, or only when there is good news to report?

Capital can help build a company. The wrong capital can make building it substantially harder.

Before closing a round, founders should look beyond valuation and ask whether their cap table has all three forms of support: someone who knows the industry, someone who understands the stage and someone they genuinely trust.

Because the most important decision in fundraising may not be how much money you raise. It may be who you allow to come along for the ride.

is a partner at (Black Ops VC), an early-stage VC firm, and is founder of , a strategic advisory and risk-management framework that teaches CEOs, operators and senior leaders how to read risk accurately, underwrite it honestly, and move forward boldly with confidence.

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The 2026 IPO pipeline is sending a clear signal. Public-market activity is returning selectively, led by companies that used the slower years to build scale and strengthen their financial and operating foundations.

The IPO market peaked in 2021, then slowed as interest rates rose, valuations fell and recession concerns weighed on issuance. market describes 2022 and 2023 as the weakest period since the global financial crisis. Activity improved in 2024 and stabilized further in 2025, but many companies stayed private longer, raised additional private capital, built scale and waited for stronger public-market conditions.

ÂÜŔňĘÓƵ , which tracks venture-backed offerings, also shows a sharp rebound — but one driven disproportionately by the largest listings. In the first half of 2026, 58 venture-backed companies valued at $1 billion or more went public globally, up from 27 during the same period in 2025 and approaching the 69 recorded in all of last year. Collectively, venture-backed startups raised $110.8 billion through IPOs, compared with $12.6 billion a year earlier. Yet $86 billion — nearly 78% of the first-half total — came from alone. The figures point to a reopened market, but one still dominated by exceptional scale rather than a broad-based recovery.

Data from my company, , offers a forward-looking view. Capital-raising projects — new transaction workspaces opened for financing processes — rose 32% globally in the first half of 2026 from a year earlier, while an IPO-related subset rose 33%.

Project kickoffs are not completed offerings, and some processes may be paused, abandoned or redirected. Even so, they can serve as a directional leading indicator because deal teams typically begin organizing diligence materials before a public filing or announcement. On Datasite, which facilitates about 16,000 new deals annually, this activity can precede announced outcomes by about six to nine months.

For founders, late-stage startups and investors tracking exit readiness, the message is not simply to wait for a better market.

The strongest candidates can close their books quickly, produce public-company-quality reporting, explain a credible path to durable growth and profitability, operate with an experienced board and finance team, withstand regulatory and cybersecurity scrutiny, and show that the business can meet quarterly obligations after listing. They are building those capabilities now so they can choose among an IPO, another private round, or a sale when conditions permit.

Prepared companies are finally coming forward

That delay raised the bar for going public. Growth alone was no longer enough. Companies had to show stronger margins, more predictable revenue, cleaner governance, tighter controls and a longer record of operating performance. Public investors continue to scrutinize valuation, growth, profitability and governance, making disciplined preparation a prerequisite rather than a final-stage task.

IPO readiness creates optionality

That preparation creates strategic flexibility. A company positioned to go public can remain private, raise another round, pursue a sale or return to the IPO process when conditions improve. The same work supports each path and allows leaders to act when an opportunity emerges.

Readiness also must keep pace with the business. Acquisitions, expansion into new markets, and changes to the capital structure can alter disclosure obligations, internal controls and regulatory exposure. Companies that reassess those issues as they arise are less likely to face delays when diligence begins.

AI is changing preparation, not diligence judgment

Technology is shortening the administrative work that can otherwise delay readiness. On Datasite, from 14 days to 12 days year over year during the first half of 2026, while median diligence time remained at 181 days.

For an IPO candidate, AI and automation can help classify files, apply redactions, identify missing materials, and keep disclosures current as the business changes. That creates more time for finance, legal and leadership teams to address substantive gaps. It does not compress the judgment-intensive work of testing controls, resolving accounting issues, responding to regulators, or earning investor confidence.

The thesis can still fail. A sustained rise in rates or volatility, weaker economic growth, widening gaps between private and public valuations, regulatory or geopolitical shocks, or poor trading by newly listed companies could cause issuers to pause again. The most important test is conversion. If early project activity does not lead to more filings and completed offerings over the next six to nine months, or if new issues fail to hold their valuations after listing, the pipeline will have signaled preparation without a durable reopening.

What to watch next

The mix of issuers: Continued growth in proceeds alongside fewer listings would confirm that public markets remain concentrated among larger, more established companies.

The conversion of early activity: Capital-raising and IPO-related projects will matter most if they translate into filings and completed offerings over the next six to nine months.

Aftermarket performance: Durable valuations and trading performance beyond the first day will show whether investor demand can support a broader reopening.

The current IPO pipeline reflects years of corporate preparation, not simply a better market window. Rising IPO-related project activity offers an early view of possible issuance in 2027, but it is not a forecast of completed offerings. The next stage depends on whether projects convert into filings, listings and durable aftermarket demand. Today’s IPO calendar is the result of decisions made years ago. The next one is already being built.

is chief revenue officer, enterprise, at , an M&A infrastructure platform that helps companies, investors, and advisers find opportunities, manage complex transactions and make better decisions. In this role, he leads global commercial strategy for Datasite’s transaction business in more than 180 countries. Previously, he was chief revenue officer, Americas, for Datasite. He’s also held sales leadership roles at a variety of SaaS companies, including (now part of ) and . He holds a bachelor’s degree in mechanical engineering from , England.

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Related reading:

• Oura Hits Pause On IPO While Anthropic’s Prospectus Reveals The Cost Of Its AI Ambitions

• IPOs Are Holding Up In 2026, But SaaS Debuts Aren’t Happening
• The IPO Window Is Closing. Here Are 8 Startups To Watch.

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Ten years ago, a seed-stage startup needed a product, a team and a pitch deck to raise capital. Today, that’s just the start. Technology and strategy have become inseparable, each fueling the other, and the rules that once defined success have quietly shifted under everyone’s feet.

Last month, my firm reviewed more than 2,500 inbound applications. Here are the key shifts we’re seeing in the startup ecosystem at the seed stage.

Broadening capital strategy

Equity is a powerful tool for building high-growth companies. But it’s no longer the only option. Non-dilutive growth capital is increasingly playing a strategic role for companies with revenue visibility and clear ROI channels.

For example, we recently financed a company with $1 million in growth capital it needed immediately to expand its team and infrastructure. Raising that through equity alone would have likely taken months, with significant time and execution cost along the way.

We’re now writing financing checks like this on a near-weekly basis.

Distribution focused

Leading with a “better” product isn’t enough to propel growth. The breakout companies are investing in building stronger distribution systems — aka what founders refer to as “traction.” Distribution is a critical moat for early-stage startups. Rapid scaling is no longer achieved by launching new products; it’s through distribution loops.

Distribution is something startups can now architect intentionally with social platforms, marketplaces and other ecosystems. One of the most common founder mistakes we see is delaying the distribution strategy until after the product launch. At that stage, the architecture is harder to retrofit. Strong startups design distribution before they scale their product.

For example, some of the fastest-growing startups now design their products around existing ecosystems from day one — building apps that tap into merchant marketplaces, AI tools distributed through or Teams integrations, or fintech products embedded directly into banking and payroll workflows. In many cases, the distribution channel becomes more valuable than the underlying product itself.

One of the most common mistakes we see is founders postponing distribution strategy until after the product is built. By then, the architecture is far harder to retrofit. The strongest startups design distribution into the company before they scale the product itself.

Learning over speed

“Move fast” is often dolled out as the best startup advice. Operating in a fast-paced environment remains a strategic asset, but it is not enough to maintain a competitive advantage.

Everyone is fast. It’s no longer a unique attribute. Instead, learning velocity is becoming the defining advantage in early-stage startups. How quickly can you reduce uncertainty? Competitive edge is achieved not by executing blindly, but by closing knowledge gaps faster than everyone else. Execution without learning equals wasted motion.

The founder focus advantage

Last year, my team reviewed close to 25,000 applications for our investment funds and bespoke accelerators. The ones that stand out are the companies doing the fewest things exceptionally well. The most-fundable companies can describe their business in one tight sentence. They can also defend exactly what they are not doing.

Disciplined constraint is one of the highest-leverage traits in venture-backed companies. When we review applications, this pattern consistently stands out.

When a company is focused, the residuals compound: stronger early retention, faster iteration cycles, cleaner capital deployment. In a capital-selective market, focus compounds faster than ambition.

Based on tens of thousands of applicants, close to 82% of the ones that stayed in business a year later had a strong go-to-market foundation in their deck. GTM is built on agility and learning fast.

AI as infrastructure, not experimentation

There’s no lack of interest in AI. But there is an implementation problem. We’ve seen companies struggle when AI is approached as experimentation rather than architecture. Rather than bolting tools onto already fragmented stacks and workflows, designing intelligent systems should be mapped from the ground up.

More than 78% of the founders applying to today are leveraging AI in at least one way in their startup.

The most successful playbook combines execution with operational clarity and emphasizes infrastructure over experimentation. We’ve seen successful implementations that center around two practical paths. The first is validation, with rapid prototypes and identifying market signal opportunities before investing in a full build. The second is system, designing and integrating custom AI agents directly into operating workflows for revenue-generating companies facing operational complexity. Both are required to move AI agents from concept to capability. A disciplined system design often matters more than flashy tooling.

Marketing is the moat

Marketing execution is one of the largest performance gaps we see across early-stage startups. Startups lose when they don’t distribute fast enough once there is something worth selling. Marketing is the propeller for the distribution engine.

Most startups fail at marketing because it is a business function that becomes a founder hustle with support from one junior hire. But breakout growth requires process, cadence and accountability. That’s not achievable without an experienced team and clear plan.

One of the biggest mistakes founders make is treating marketing as something that starts after launch. Founders must create unique strategies, test them and then analyze what works and what doesn’t. From there, they must keep iterating and creating to unlock the most product-market fit and traction.

If we see classic strategies in a pitch deck, it is an auto-reject. And beyond being unique, your strategies must have been tested by your team.

The key is simple: Test ideas early, measure what actually works, refine aggressively and scale the strategies that compound over time.

, a serial technology entrepreneur since age 12, is now a value-driven venture capitalist with a track record of backing more than 1,000 startups across the globe. He is a co-founder and general partner at , one of the world’s most active venture capital firms. Before becoming involved in venture investing, he built and scaled into the world’s largest debate-focused social network and edtech platform, reaching millions of users and serving students across more than 500 school districts, colleges and universities.

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One of the strangest things about the current AI cycle is just how fast the math changes for the people building it. You can be a 20-something founder who feels like you are still in the warm-up phase of your career, yet on paper your equity is already life changing. Or a mid-level engineer who went from holding startup options to staring at a substantial personal balance sheet practically overnight.

The gap between life experience and the sudden reality of managing serious wealth is widening as AI-native companies reach major valuations faster and private company liquidity arrives earlier.

A of more than 3,400 founders and senior leaders across 20 countries found that AI-native startups are reaching billion-dollar valuations in about 3.5 years, roughly half the time it took before generative AI. They are doing it with about half the staff.

We have seen an even more compressed version firsthand. We recently advised founders who went from launching their company to a major liquidity event in less than a year.

When the money outpaces the mindset

For decades, tech wealth followed a more predictable script. Significant personal wealth often accumulated alongside a long career. Equity vested over years, responsibilities grew and additional grants often followed. If everything went right, an acquisition or IPO marked a visible transition into a very different financial reality.

Today, that boundary is much less clear. AI capabilities allow companies to grow at a much faster pace.

A young founder can suddenly face questions that used to come much later in life. What are their long-term personal goals? What should the new capital be used for? What does financial independence mean for someone who may still be figuring out what they want their life to look like?

These are not always questions that can be answered overnight.

Compounding this is the fact that one doesn’t have to wait for an IPO to de-risk. Tender offers and secondary transactions allow founders and employees to turn part of their equity into cash while the company remains private.

Take as an example. While still only 3 years old, the company authorized a $100 million secondary sale for staff at a $6.6 billion valuation. By February 2026, it had at an $11 billion valuation.

For someone inside a company moving at that speed, the sequence can look very different from the traditional startup script. It is a dizzying loop of grants, valuations and a sudden liquidity window. All of this can happen long before an IPO.

Flexibility is the name of the game

A sudden liquidity event can make financial independence a realistic goal. It may make buying a home possible, even while someone is still single or has no idea where they want to live long term. It may allow them to take care of parents or fund another entrepreneurial chapter.

The pace of these cycles can also be contagious. Opportunities seem to be everywhere. At the same time, a founder may still be taking substantial risks with the current venture and have very little idea what life will look like in five years.

When we advise technology executives and founders in this position, we try to leave room for several possible paths while the broader picture is still developing. Some capital may eventually support long-term family security. Some may need to remain available for opportunities or life changes that do not exist today.

A future business endeavour, a career change, a relocation to another country, or other less conventional ideas can change the picture again. Some of these moves can be made today, but others need time to develop.

A company may compress 10 years of growth into three, but people cannot compress 10 years of life into three. Ignoring that gap is where real risk can build.

Valuations and liquidity can move incredibly fast. Decisions about family wellbeing, security, career and the future still move at a human pace. Your financial architecture needs to respect the difference.

is co-CEO of , where he works with founders, senior technology executives and families on wealth strategy, liquidity events and long-term financial planning. Before moving into wealth planning, he spent many years in the technology industry and writes about the intersection of technology, equity and personal wealth.

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An overwhelming majority of early venture-backed startups utilize a standard four-year vesting schedule with a one-year cliff. It seems like the ultimate one-size-fits-all template. Yet almost no one talks about how this default framework routinely causes bitter legal battles over founder equity, wasting hundreds of thousands of dollars on litigation that could have been avoided.

By the time a founder leaves or gets terminated, the damage is already done, leaving the company stuck with costly “dead weight on the cap table.”

What dead weight actually costs your company

When a co-founder with substantial ownership leaves — voluntarily or involuntarily — they often walk away with a massive, permanent piece of the company.

From a VC’s perspective, and that of the remaining partners, this is pure dead weight. You now have someone holding 15% to 20% of the equity who is no longer providing any value. Of course, contractually it’s theirs, and they’ve usually earned it.

Practically, it can break the company in three distinct ways:

• It kills motivation: The remaining team has to grind for years toward an IPO or acquisition, knowing that a fifth of the exit payout is going to someone sitting on the sidelines.

• It breaks future dilution pools: When you need to bring in new executives or raise a new VC round, your outstanding share count is artificially bloated by a departed founder. Issuing a simple 1% option pool suddenly requires 20% more shares than it otherwise should.
• It creates voting and control nightmares: If a departed founder owns 20%, you need their signature on standard investment documents and major shareholder votes. Even if they didn’t leave under bad circumstances, their risk tolerance and timeline are completely misaligned with the active team.

The shrinking threshold of tolerance

Five to 10 years ago, investors might have tolerated a departed founder holding 5%, 10% or even 20% of the company. Today, that threshold has collapsed. Many VCs will now insist that a former founder hold no more than 2.5% of the cap table.

However, because the standard four-year vesting agreement has no contractual mechanisms to claw back shares, companies start looking for alternative ways to do so when a founder leaves.

Initially, this usually involves pressuring them to give up shares “for the goodwill of the company.” When that fails, they sic investors on them, threaten their professional reputation, and sometimes resort to litigation.

I see this over and over. We frequently see litigation that is nominally about intellectual property or confidentiality, but everyone knows the real goal is simply to get the equity back. These are multi-hundred-thousand-dollar lawsuits that never would have been filed except as a desperate attempt to claw back departing founder equity.

How to fix the problem

The four-year vest, one-year cliff standard is a very lemming-like system in which founders follow the same standard as everyone else.

They often pull the language in equity agreements off automated legal platforms because it’s cheap, fast and requires minimal thought. If we want to fix this problem — and I believe every startup should — the industry needs to converge on a new, more nuanced position built into founding documents from day one.

We can split the proposed solve into two categories:

Fixing control and voting (the easy part)

Founding documents can automatically strip voting power upon departure. It’s simple enough to build in an obligation to hand over a voting proxy to the current CEO the moment a founder leaves, along with a mandatory drag-along clause that requires them to comply with future sales or investment rounds. Alternatively, a class of nonvoting shares can be created for departed founders and other service providers.

Fixing the economics (the hard part)

Four years is too short. It does not match the actual lifetime of a modern startup heading toward an exit. There are structural changes to the standard founder equity and vesting templates that could address this problem:

• Extend and back-weight vesting: Move to a five- or six-year schedule and stop using even distributions. Force back-weighting — such as 5% in year one and 10% in year two — to reward longevity and protect the cap table if someone leaves early.
• Pre-agreed buyouts and forfeiture over time: Agree upfront on a methodology and price for the company to buy back vested shares post-termination, perhaps leaving the departed founder with a permanent floor of 2%. Alternatively, tie the equity to timing: If the company sells three months after a founder leaves, they keep their 20% because they built that value. If it sells four years later, a portion of that equity should automatically forfeit back to the pool.
• Automatic share class conversion: Build a mechanism where a departing founder’s equity automatically converts into a separate class of stock with no voting rights and inferior economic rights.

A watch-out for minority founders

Minority co-founders face the highest risk of litigation aimed at clawing back their equity. They should push for pre-agreed severance, clear definitions of “cause,” and accelerated vesting protections before signing paperwork.

Even if the dominant founder refuses those terms to satisfy institutional investors, having the conversation is a critical de-risking tool. Simply observing how your co-founder reacts to these structural negotiations can provide a lot of intel. Are they hostile and defensive? Are they secretive, claiming “the lawyers said no” without CC’ing you on the emails?

How a co-founder handles the equity conversation at the outset can provide valuable insight into how they will handle conflict when the stakes are much higher.

Protecting the cap table from day one

Right now, the venture ecosystem is still operating within an outdated, broken structure. VCs want clean cap tables, remaining founders want motivated teams, and departing founders want to be fairly compensated for the early risks they took. But the current four-year vest, one-year cliff template satisfies none of them. Instead, all it does is ensure that when a founder relationship ends, companies are left hobbled by dead weight on their cap table.

Startups face high-stake, bespoke risks. Equity structures should reflect that reality. Engaging a lawyer to properly customize and document these relationships at the outset isn’t hard or expensive. What is expensive is spending hundreds of thousands of dollars later on a lawsuit, searching for leverage to claw back equity that should have been protected from the very beginning.

is a partner at and an accomplished startup lawyer and litigator specializing in corporate, transactional, intellectual property and complex commercial matters. He has advised startups on multimillion-dollar financings and acquisitions and represented clients in sophisticated intellectual property and corporate disputes. Siegel is licensed to practice in both California and New York.

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