Anj Midha

speaker

721 appearances 1 recordings 1 series first heard Apr 2026 last heard 14 Apr

Anj Midha’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 — 1 in all, peaking in Apr 2026 with 1.

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch · 20VC: Anj Midha on Investing $300M into Anthropic | The Early Days of Anthropic & How 21 of 22 VCs Turned it Down | The Four Bottlenecks to Compute | What the China Has Smashed and Why We Should Be Worried · 14 Apr 2026 podcast

And so Tom gave me a call and said, Anj, for various reasons, we want to leave and start this new lab called Anthropic.

We're going to need a lot of capital.

We're going to need compute.

I had already sold Ubiquity6 at that point.

So I'd kind of gone through the founder journey.

And so Dario, Tom, and I started doing these weekly sessions in early 2021 to try to figure out how to turn what was really a research hypothesis, right?

Which is the scaling recipe into a business hypothesis.

And look, I would say it took like really 12 to 24 months, and they did a lot of the hard work on figuring out how do we really sort of operationalize this, the idea of this AI pair programmer, where you take the context feedback loop of the local repository, the files, the directories of programming, and sort of in a very methodical way, make predictable progress on the capabilities of software engineering.

If anything, my biggest flaw as an investor, as a founder, is being too early to things.

That was my lesson with Ubiquity6.

I was early to the whole computer vision, which is now, you know, obviously blowing up the whole multimodal sort of generative modeling space.

And since then, I have, I think, updated my strategy on how to get timing right.

But at the time, the recipe was pretty simple, right?

Raise some money, buy some compute, get a little bit of context data on programming, put out a basic version of the model, deploy it with teams that we trust who are doing coding,

And then pipe that feedback loop back into the training run over and over again.

And when you do that with inference, inference gives you sort of two things.

It gives you revenue to buy more compute, and it gives you the context feedback to keep improving the capabilities curve.

And I was like, great, this makes total sense, guys.

Let's go raise money.

I invested a bunch of my money that was just life savings, which was not much given I was a poor founder at the time, where most of my net worth was tied up in Discord stock.

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