Nikesh Arora

speaker

2,918 appearances 12 recordings 8 series first heard Nov 2025 last heard 6 Aug

Nikesh Arora’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 — 12 in all, peaking in Jun 2026 with 5.

Appearances

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch · 20VC: Nikesh Arora on the Frontier Model Problem: Breadth vs Depth | The Future of Token Costs | Memory Becoming the Moat | Where Value Accrues: Infra, Models, or Apps? | Why Enterprise AI is Not Ready & Systems of Record vs Systems of Intelligence · 22 Jun 2026 podcast

And as you start building context on a user basis, you create stickiness, and that becomes your moat.

Mythos ended up, I think ends up being an accelerant to cybersecurity.

I think what happened when you saw Mythos came out, it demonstrated that all the training we've been giving these models on how great code is written, the models are able to turn around saying, well, I also know how to find bad code.

So what happens is you point the gun the different way and the model says, oh my God, look at all this code that you have.

There are so many flaws in it.

As we talked about, the challenge is like every model, it also suffers from false positives.

If you're an offensive actor,

And I point the model against, let's just say, 20 VC enterprises, and I go look at everything you've done.

Somebody's left a web socket open.

Somebody's done some mess up in IP addressing, et cetera.

So it finds the flaws outside in.

That allows the bad actor to go figure out how can they daisy chain vulnerabilities and get into your infrastructure.

It's not good enough from a defensive perspective because I can't use the model and say, go take every vulnerability you found and build a patch and go patch my system and protect me.

So guess what?

It's going to patch 30% of things that are not wrong.

Who knows what that's going to do to blow up your infrastructure.

So when Mythos came, we looked at it, we treated it with respect, we ran it against our code, we discovered it finds bad stuff much faster than humans can.

We found in six weeks would have taken us five to six years.

So we got it.

We ran around, we patch it, but Cloud Code helps build the patch, but you still have to run it through human evals, through testing, through production testing, through sandboxing to see, does this patch break anything in the infrastructure?

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