The Peterman Post

At first, I was planning to talk to Professor Aaronson about quantum computing since it’s his field of expertise. But in doing my research, I found that he used to be a big skeptic of AI in the 2000s. Now though, he’s completely updated his opinion based on how AI has changed his field recently. This made me curious to hear what the changes are like to him that caused him to change his mind that much.

Neetcode is the most well-known coding interview prep creator with over 1M+ subs on YouTube. I interviewed him about the latest on coding interviews, his career at Amazon vs Google, and what it was like quitting big tech to do his own thing. Check out the episode wherever you get your podcasts: YouTube, Spotify, Apple Podcasts. 27:47 - How it was quitting big tech 29:38 - What he hated most about Google 32:34 - Advice for his younger self [00:33] You ended up unemployed.

I put together a set of questions on corporate politics that get increasingly darker. I was aiming for the questions to test Ethan’s unusual level of transparency since he retired from being a VP at Amazon. For instance, I asked him if he had burned people to get ahead or if he was empire building at Amazon. He shared a story of how he did and Jeff Bezos caught him. It didn’t go well for him. He also had some interesting stories about unusual HR situations.

Philip Su grew quickly to a Distinguished Engineer at Facebook and OpenAI. We talked about the psychology behind peaking in a tech career and the pressure at the highest levels. Check out the episode wherever you get your podcasts: YouTube, Spotify, Apple Podcasts.

For the first time in my career, I made a decision that didn’t make sense on paper. Last year, I started a podcast to practice speaking and share software engineering career stories that inspired me. Everything felt new and I was learning a lot. After work, I kept thinking about ways to make the podcast better. I dreamed of working on it full time but it never made sense because I’d only ever lost money on it.

In this episode, my goal was to record a conversation that was completely free of any “AI doom” content. There’s so much of it out there, I hope that this can be a nice timeline cleanser. I had Casey Muratori on who is a video game developer and programming creator also known for several talks (ex1, ex2) on the history of computing. In putting together those talks he dug deep into computing history. Enough where he had interesting stories and tidbits to share.

When I talk with my friends who work at Anthropic it always surprises me how far ahead they are in adopting AI within their processes and workflows. Generally what engineers in the industry start doing, these top AI labs have already been doing for a while. In this conversation, I asked Thariq Shihipar who is an engineer on Anthropic’s Claude Code team how Anthropic makes the most out of the models for engineering and how the industry will change soon.

There are so many choices every programming language creator makes while navigating engineering tradeoffs in building one. This made me curious about Martin Odersky’s (the creator of Scala) thoughts comparing different languages. His deep domain expertise made his responses comparing Rust, Zig, Python and Scala interesting. He also had a lot to say about how AI will impact programming language ecosystems in the future.

Sergey Levine is one of the world’s top robotics researchers and co-founder of Physical Intelligence. Recently I talked to him to dig into where we are today with humanoid robotics. He also had a lot to say about the Chinese robotics ecosystem. I asked him questions about that and about competitors such as “what if Anthropic and OpenAI started their own robotics labs?” We went over a bunch of questions about predictions on future timelines.

It was interesting talking to Anders Hejlsberg, the creator of TypeScript and C#, about all the technical details behind rewriting the TypeScript compiler in Go. I had a lot of questions about why they chose Go (vs Rust) and if they used LLMs in the rewrite. Turns out they used LLMs much less than expected in the rewrite. He explained why in the conversation.