Mike Mignano

speaker

1,346 appearances 2 recordings 2 series first heard Jul 2026 last heard 6 Jul

Mike Mignano’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 2 in all, peaking in Jul 2026 with 2.

Appearances

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch · 20VC: Why Now is the Time for the Application Layer | Why OpenAI & Anthropic Won't Win the App Layer | Why Startups Should be TokenMaxxing | Why VCs Should Reduce Weighting on Price & Ownership in an Age of AI with Mike Mignano, USV · 6 Jul 2026 podcast

And I think you need to be willing to take bets on people, which, again, I think you've done a good job of with your program.

I think that's totally okay.

Much like building a startup or building a product.

I think if you're investing, you also have to be willing to put yourself out there and take a risk and place a bet.

Now, listen, you can hedge that bet a little bit.

You can place a counter position bet and something else maybe to offset the risk of that.

But I think you have to be willing to put yourself out there if you want to succeed at anything in technology, whether it's a startup or a venture capitalist.

You know, one future is that the labs, especially the ones that are starting to approach something that feels like super intelligence, if they reach it, once they reach it, we will have some form of recursive self-improvement such that we hit this exponential growth of intelligence.

The thinking goes that whoever gets there first will run away with it, right?

Once you reach recursive self-improvement, you're gone.

No one can catch up.

That's not necessarily the future that I am hoping for.

For everyone who doesn't know, what is recursive self-improvement?

This is self-improving AI.

This is super intelligent AI that can do its own AI research.

So once you have it, once you deploy it, it can just continually improve itself

on the exponential forever, until it plateaus, until it self-limits in some way.

And by the way, we don't know what that self-limiting factor may be.

It may be that for some reason, these architectures, the transformer architecture, let's say, doesn't scale past a certain point.

We don't know if that's going to happen.

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