附近上门

By 听

In recent years I鈥檝e found myself reflecting on what the startup and venture capital market has become.

Bubbles, deception, spin and outright misrepresentation seem to have become the norm, and even those who steer clear of such practices are inevitably caught in the ripple effects. Either they rely on distorted data, miss out on opportunities, or lose money and credibility. Many times, it is all of the above.

While this problem is not new, it is certainly solvable. Acknowledging it is the first step toward finding a solution, which is why I believe it鈥檚 crucial to bring it to light.

A personal example

I happened to discover online that my portfolio includes two more 鈥渆xits鈥� than I was aware of.

As it turns out, one startup, which faced significant issues and ultimately shut down 鈥� returning 3 cents on the dollar to investors 鈥� had its founder join a well-known company and take a couple of employees along for the ride. Somehow, this is spun as an acquisition or successful 鈥渆xit.鈥�

Another struggling portfolio startup burned its cash, racked up debt and finally 鈥渕erged鈥� into another company 鈥� not through a sale, but simply to preserve the team. The founder, unwilling to let an alternative potential buyer conduct an in-depth team evaluation, handed over the company for free. Investors made nothing, yet the founder proudly counts this as an exit.

The big picture

These examples highlight broader issues in the startup ecosystem, where narratives evolve at each stage 鈥� from founders creatively interpreting metrics to investors selectively reporting them. Data platforms, in turn, reflect these narratives, ultimately shaping market perception and fueling the illusion of success.

In this growing divide, only 鈥渟toryteller鈥� investors, extreme risk-takers, or overly cautious 鈥渟harks鈥� thrive, while more balanced players often lose out or underperform 鈥� at least on paper, which is all the market sees.

I know of funds that boast a sky-high IRR, only for it to later emerge that these figures were calculated by cherry-picking a sample of their most successful projects. This masks the full picture of their portfolio鈥檚 performance.

Similarly, there are startups whose creative metrics 鈥� think of ‘s 鈥� have become a running joke within the industry. Yet some investors still buy into these inflated stories, fostering a dangerous feedback loop that misleads stakeholders and undermines trust across the ecosystem.

The consequences are far-reaching. More people see the industry as undesirable. And ultimately, this makes capital more expensive and hard to get for those who may have a good idea.

Solving the problem

Startups, investors, the media and even regulators 鈥� who often turn a blind eye 鈥� all share the blame. Yet, there are potential solutions.

On public markets, frameworks such as the Global Investment Performance Standards have been introduced to bring transparency and accountability to fund performance.

Is it time to introduce a similar structure for VC reporting?

Perhaps. Transparency in reporting could help create a more trustworthy ecosystem. But let鈥檚 be honest 鈥� this problem is decades old. Remember when sold a dysfunctional to , only for the acquisition to be called a disaster? Well, that was over 25 years ago.

Still, it feels like a conversation worth having, and we must continue to shine a light on questionable practices while pushing for a startup ecosystem built on real value.

As investors, we can genuinely make a difference by conducting proper due diligence and ensuring we don’t fund projects that are smoke and mirrors out of the fear of missing out.

is the founder and managing partner of , a Delaware-based VC fund with more than 20 AI startups in its portfolio and five successful exits. With 20 years of experience in executive roles with financial groups and industrial companies, he has closed more than 250 M&A and private equity deals totaling $24 billion.

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