"ChatGPT OpenAI may look like a Goliath today as the clear market leader, but there is a non-zero chance of the company failing, especially if there is an AI crash. We already saw this risk during the board control dispute, when questions about AI safety and trust in Sam Altman as CEO led to real value destruction. If Altman had been forced to leave, OpenAI would have followed a very different trajectory, with some arguing the value might have been higher and others believing it would have been much lower, which is something worth thinking carefully about." - Jeremy Au, Host of BRAVE Southeast Asia Tech Podcast


"VCs need to be thoughtful not only about selecting the right teams but also about helping them survive the early stage. Many incubators and accelerators, especially those working with very early startups, spend significant time coaching founders, teaching them how to work together, and connecting them with people who can help." - Jeremy Au, Host of BRAVE Southeast Asia Tech Podcast


"Even though it is well known that older founders have a higher chance of success because they have more experience, more self-awareness, and are less likely to make bad decisions, VCs still tend to invest in younger founders. One explanation discussed in the research is that older entrepreneurs often have more resources and can self-fund their progress, so they do not need to sell as much equity. As a result, VCs may index toward younger founders who need venture capital and where VCs believe they can add more value." - Jeremy Au, Host of BRAVE Southeast Asia Tech Podcast

Jeremy Au discusses how value is created, preserved, and lost in Southeast Asian startups, focusing on governance, control rights, and exit risk. The conversation looks at real founder–investor breakdowns, regulatory shocks, and why weak structure often shows up only when things go wrong. It explains why growth alone is not enough, and how control, trust, and exit planning shape outcomes in emerging markets.

00:14 Investor Regret on Control Rights: Investors reflect on the downside of weak protections and wish they had negotiated stronger control measures earlier.

01:18 Exit Management Is a VC Skill: The discussion shifts to exits, emphasizing that building value and realizing value require different skills and planning.

06:09 Light-Touch Governance and Fraud Risk: How US-style light governance in Indonesia contributed to aggressive growth, weak oversight, and fraud issues.

09:07 Growth Pressure and Revenue Fraud: A direct link is drawn between growth-at-all-costs behavior and manipulation of revenue numbers in emerging markets.

Today we’re talking about exit management, which is a core skill for VC funds. We’ll also touch on regulatory affairs, which connects nicely with our earlier discussion about how startups fight to preserve value over time.

Take the example of BlueCity. This was the world’s first LGBTQ-focused Chinese company to IPO on Nasdaq. They raised about US$85 million. Over time, the company faced significant selling pressure, the stock price declined, and eventually the company was taken private.

This is an interesting case and something for you to think about when we talk about exits and proceeds.

Every VC has to be able to source, select, close, support, and eventually exit an investment. We talked about how VCs issue term sheets, negotiate them into long-form agreements, conduct due diligence, sign legal documents, and eventually wire capital.

When you do that, you’re building trust, setting up board seats, and creating structures intended for a long-term relationship.

That’s where the control discussion comes in.

I mentioned earlier that I received a message from a VC about a founder who has gone silent. Investors in that situation inevitably think, “I wish we had negotiated stronger control rights.”

But the flip side is reputational. If you push too hard on control, does the broader founder market view you as someone who doesn’t trust founders and isn’t founder-friendly, and therefore avoid taking your capital?

This is something VCs think about constantly.

Term sheets generally fall into two buckets: financial terms and control terms.

Financial terms define economics. These include check size, valuation, price per share, employee option pools, liquidation preferences, and anti-dilution clauses.

Control terms define decision-making. These cover board composition, voting rights, information rights, protective provisions, and mechanisms for resolving disputes between founders and investors.

These provisions can protect value, but they can also be a source of significant tension or even destruction for founders if handled poorly.

If you look at the United States, many public companies allow founders to retain control through super-voting shares. Mark Zuckerberg is a classic example. Even with a minority of the economic interest, he retains majority voting control.

The market, rightly or wrongly, seems to believe this allows founders to make long-term decisions without being overly constrained by short-term quarterly reporting pressures.

President Donald Trump has proposed making quarterly reporting optional for public companies. His stated belief is that without quarterly reporting, companies could focus more on long-term value creation rather than being beholden to every investor call.

There are obviously different schools of thought on this.

Short sellers would likely argue the opposite. Firms like Blue Orca and others would argue that transparency is critical so markets can identify overvalued companies and apply short-selling pressure to correct prices.

You also have activist investors who attempt to influence board composition or management decisions in order to push for better leadership or operational changes.

All of these dynamics influence how control and governance work in both public and private markets.

We also talked about startup failure across different stages. Most startups fail early, but even at Series A, Series B, and Series C, you still see thirty to forty percent of companies failing at each stage.

This is important to remember because many people assume that once a company reaches a later stage, it becomes a safe bet. That’s simply not true.

There is still a significant amount of risk even when you join what appears to be a strong or well-funded company.

Take OpenAI as an example. If you joined OpenAI today, it would look like a Goliath. It’s clearly a market leader.

But many people also acknowledge that if there were an AI crash, OpenAI could find itself in a very difficult position. There is a non-zero probability of even a company like OpenAI failing.

We’ve already seen how governance issues can destroy value. During the board dispute involving Sam Altman, there was massive uncertainty about leadership, trust, and AI safety. That conflict alone created substantial value risk.

If Sam Altman had been forced to permanently leave, OpenAI would be on a very different trajectory. Some would argue the value might be higher, others that it would be far lower.

We also discussed how startups can succeed or fail depending on timing. Many startups are simply ahead of their time.

Jibo is a good example. It pioneered social robotics between 2013 and 2018 and ultimately failed. But today, social robotics is coming back as hardware becomes cheaper, sensors improve, and AI models become more capable.

So how do we define failure from a VC perspective?

Failure means that as an investor, you don’t get back more money than you put in. If you didn’t invest in that startup, you could have put your money into gold, the Nasdaq, or an index fund.

This is an economic definition of failure, not a personal one.

Startup failures are often messy. They can be litigious, emotional, and public. People sue each other, blame each other, and fight over narratives.

Media coverage rarely captures the full picture. You might get a few hundred words in an article, which inevitably simplifies complex situations and assigns blame to individuals.

It often takes years to truly understand what went wrong.

We talked about six common failure patterns that VCs think about.

One is bad co-founder dynamics. Even with a good idea, bad co-founders can destroy a company. This is where boards may need to act as a tiebreaker.

Another is false starts, where startups prematurely scale before achieving true product-market fit.

There are also false positives, where early traction looks promising but turns out to be misleading.

Speed traps are another issue. Companies are pushed to grow aggressively and end up creating fraud, bad incentives, or toxic cultures.

Builder.ai is an example. While OpenAI raised enormous amounts of capital and built real revenue, Builder.ai, an Indian AI startup, faced governance failures and fraudulent revenue reporting under pressure.

There’s also bad macro luck. Crypto winter over the past two years wiped out many companies, even strong ones. Now crypto is back, and people are wondering whether AI will face a similar cycle.

Founders today face difficult decisions. Should they conserve cash in anticipation of a downturn, or spend aggressively to defend market position?

We also discussed cascading miracles. Legendary companies are built through a series of interdependent bets. When they succeed, they produce outsized outcomes. When they fail, the collapse can be equally dramatic.

This constant risk of failure drives VCs to actively try to create value and improve the odds of success.

VC funds approach this differently depending on portfolio size. Funds investing in fifteen to twenty companies can spend more time on boards and coaching.

Funds investing in forty or more companies can’t sit on every board, so they operate in batches.

This is why you see accelerators and platforms like Y Combinator, Antler, and Entrepreneur First running structured programs that coach founders in groups.

We also talked about idea vetting. Some ideas are simply too theoretical.

For example, data-driven dating didn’t work, but photo-driven dating through Tinder did. Later, Bumble differentiated by putting women in control of initiating conversations.

From a theoretical standpoint, it’s not always obvious which model will win. That’s why VCs spend so much time working with founders to avoid false positives and premature scaling.

We revisited speed traps, bad macro luck, and cascading miracles as recurring patterns across industries — not just crypto or AI, but also biotech, broadband, and even railroads.

Capital flows in cycles, and timing matters enormously.

Ultimately, the fear of failure and the knowledge that eighty to ninety percent of a VC portfolio may fail pushes VCs to focus intensely on value creation.

What exactly are you promising founders? Are you helping with fundraising, hiring, coaching, governance, or board management?

Your differentiation as a VC fund depends on where and how you add value relative to others.

There is quantitative evidence that angels and top-tier VC funds can meaningfully improve startup outcomes, especially for less experienced founders.

Interestingly, top-tier VCs don’t seem to add much incremental value when working with top-tier founders, because those founders already have strong networks and capabilities.

One explanation discussed in the research is founder age. Older founders tend to have higher success rates due to experience and self-awareness, but they also tend to have more personal resources and are better able to self-fund. As a result, they may need venture capital less and are less willing to sell large equity stakes.

This may partly explain why VCs continue to index toward younger founders, where both capital and value-add matter more.