DA

Diogo Almeida

Things Diogo Says on Podcasts

Where to Find Them

Diogo Almeida writes a16z Podcast . They have also been a guest on Venture Daily Digest , Robonaissance , TBPN and TBPN .

Recently: “AI Can Write Code. Why Isn’t Software Better?” on a16z Podcast (September 2026); “AI Can Write Code. Why Isn’t Software Better?” on a16z Podcast (September 2026); “The Model That Stopped Talking” on Robonaissance (September 2026); “Meta Connect Reactions, Zuck's Beer Pong Controversy, New Bentley EV | Shalev Lifshitz & Romi Lifshitz, Leif Abraham, Diogo Almeida, Hooman Reza Nezhad, Jordan Nanos, Erika Alden DeBenedictis” on TBPN (September 2026); “Everything Announced at Meta Connect” on TBPN (September 2026); “☕ OpenAI could burn $278 billion in cash by 2030 & Anthropic releasing new AI model ahead of IPO.” on Venture Daily Digest (September 2026).

What They Said

“Are you really telling me that math is solved, or even two years ago GPQA, Google-proof question answering, is solved, but we still can't handle a drive-through? It's a very hard thing to hold in your head at once.” — Diogo Almeida, a16z Podcast

Almeida argues that the real test of AI is whether it can automate ordinary productive work, not whether it can top hard benchmarks. Casado pushes back right after, suggesting the real world is long-tailed and the training data for it simply isn't there yet.

a16z Podcast · 2026-09-28 Permalink → Listen →
a16z Podcast Around 22:23 into the episode
Martin Casado

And so you think that the measure that we should have is to what extent can you automate actual productive tasks? That the overpromise and under deliver, that's

Speaker 4

the dimension in particular you're talking to. The ability to automate tasks.

Diogo Almeida

I think in my heart, it's like cool sci-fi. And I think that that is the canary in the coal mine for cool sci-fi. Like, are you really telling me that math is solved or like even two years ago, GPQA, that Google proof question answering is solved, but we still can't handle a drive-through, right? Like it's a very hard thing to hold in your head at once. And I think a lot of people don't have good answers to that.

Martin Casado

Can I just test one thing, which may not make sense, but I want to say, I mean, isn't there an argument, though, that like the distribution of the real world is different than the digital world, right? It's heavy-tailed. There's a lot of exceptions. We don't have all the data. And I mean, couldn't it be the case that the reason we're not doing productive stuff in the real world is just like we're not, we don't have the data for that distribution. We're not training on that distribution. And this is why it's just been basically relegated to like these lower dimensional manifolds, like whatever math or code or

Diogo Almeida

I don't entirely buy the data argument, in my opinion. I do believe that there's a long tail for sure. Like that, that would be kind of crazy to deny. And I don't think that in my like canary in the coal mine situation, we need to automate that long tail. Like I think that I think we need to be incredibly pragmatic on everything. And like building reliable software is always an investment, right? Like it like, you know, what were the three great virtues of a programmer? Laziness to not to do it again, hubris. And there's a third wall.

Martin Casado

Yeah, no, I remember this is from the Pearl days. Yeah, yeah.

Speaker names from our own diarization · position estimated from where the line sits in the episode

Collections They Appear In