VCs Are Writing Nine-Figure Checks to AI Startups Like It’s 2021 Again

You’re scrolling through TechCrunch on a Tuesday morning, coffee in hand, when you see it: another AI startup you’ve never heard of just raised $150 million. Yesterday it was a different company at $200 million. Last week, someone pulled in $300 million. You close the tab, open Twitter, and see founders joking about how seed rounds now have more zeros than Series B rounds did three years ago. Welcome to 2024, where “seed round” has become a term that’s lost all meaning.

I’ve been reviewing AI tools for two years now, and I can tell you this funding frenzy tells us more about investor psychology than it does about which tools actually work. Because here’s what nobody wants to admit: most of these massively-funded companies are building products that don’t exist yet, solving problems that might not be real, for customers who haven’t asked for them.

The Numbers Are Genuinely Wild

We’re not talking about your grandfather’s seed rounds anymore. Companies that haven’t shipped a product are raising what used to be Series C money. I’m seeing “pre-seed” rounds at $50 million. Seed rounds hitting $200 million. These aren’t outliers—this is becoming the norm for anything with “AI” in the pitch deck.

The justification is always the same: compute costs are astronomical, talent is expensive, and you need to move fast before OpenAI or Google eats your lunch. Fair enough. But when I actually test these tools after they launch, I’m often left wondering where all that money went.

What This Means for the Tools You’ll Actually Use

Here’s my concern as someone who tests this stuff daily: massive funding rounds create perverse incentives. When you raise $200 million at seed, you’re not building a tool anymore—you’re building a unicorn-or-bust moonshot. That means:

You’ll chase enterprise contracts instead of making something individuals love. You’ll add features nobody asked for because you need to justify the valuation. You’ll pivot three times before admitting the original idea wasn’t working. And most importantly, you’ll burn through capital trying to be everything to everyone instead of being excellent at one thing.

I’ve tested dozens of AI tools this year. The ones I actually recommend to people? They’re usually built by small teams who raised reasonable amounts of money and focused on solving one problem really well. The overfunded ones tend to be bloated, confusing, and trying to do seventeen things poorly.

The Talent Vacuum

There’s another issue nobody’s talking about: these mega-rounds are creating a talent vacuum. Every competent ML engineer is getting recruited by companies with infinite runway. That’s great for those engineers, but it means the scrappy startups building genuinely useful tools can’t compete on compensation.

I’m watching talented teams struggle to hire while mediocre companies with great fundraising decks are assembling armies of engineers. The correlation between funding and product quality is weaker than ever.

What Actually Works

After testing hundreds of AI tools, I can tell you the best ones share common traits: they solve a specific problem, they work reliably, and they don’t try to be your entire workflow. They’re often built by teams that raised modest amounts and stayed focused.

The $200 million seed rounds? They’re building platforms, ecosystems, and “infrastructure for the AI age.” That might work out. But when I need a tool to actually get something done today, I’m usually reaching for something built by a team of five people who raised $3 million and spent it wisely.

The Reckoning Is Coming

Look, I’m not rooting for failure. I want great AI tools to exist. But this funding environment is unsustainable. When the music stops—and it will—we’re going to see a lot of overfunded companies with nothing to show for it.

The companies that survive won’t be the ones with the biggest seed rounds. They’ll be the ones that built something people actually want to use. As someone who tests these tools every day, I can already tell you which category most of these mega-funded startups fall into.

So next time you see a headline about another $150 million seed round, ask yourself: does this company have a product I can use today? Do they solve a real problem I have? Or are they just really good at raising money?

Because in my experience reviewing tools, those are very different skills. And only one of them matters when you’re trying to get work done.

🕒 Published: April 1, 2026