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Ryan Peterman

@ryanlpeterman • 30,140 subscribers

Quit my job to build the podcast & ergonomic keyboard I wish existed • ex-software engineer @instagram, @meta • See what I'm building here ↓

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I don't think you'll be able to find a conversation like this one on the internet. I interviewed Ethan Evans (former Amazon VP) about every possible corporate politics situation I could think of and he told me everything since he's retired. Topics we covered: • Managing people out + promos via reorgs • Orgs trying to steal scope • How to fire managers • What leverage engineers have when getting managed out • Handling politically skilled operators • Examples of political messaging • Handling bad managers and mutiny • Empire building + effective backchanneling • Influence without authority • How to avoid politics if you hate them It was fascinating in a morbid curiosity kind of way. I heard so many things in this conversation which I wish weren't true but are. Hopefully this conversation is helpful for people navigating corporate politics. Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

I don't think you'll be able to find a conversation like this one on the internet. I interviewed Ethan Evans (former Amazon VP) about every possible corporate politics situation I could think of and he told me everything since he's retired. Topics we covered: • Managing people out + promos via reorgs • Orgs trying to steal scope • How to fire managers • What leverage engineers have when getting managed out • Handling politically skilled operators • Examples of political messaging • Handling bad managers and mutiny • Empire building + effective backchanneling • Influence without authority • How to avoid politics if you hate them It was fascinating in a morbid curiosity kind of way. I heard so many things in this conversation which I wish weren't true but are. Hopefully this conversation is helpful for people navigating corporate politics. Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

2,982,861 views • 7 months ago

Used Fable 5.1 to turn my Kindle into a Linux terminal so I could work without blue light at night

Used Fable 5.1 to turn my Kindle into a Linux terminal so I could work without blue light at night

562,917 views • 1 month ago

ex-Amazon VP (Ethan Evans): "One of the hardest things for people to understand is I've identified a legitimate weakness in my boss. I go to my skip. Why doesn't he do something? Well, if you come to me with a weakness in one of my employees, there is subconsciously this process that goes on that says, I have two choices. I can believe that you're overly sensitive and high maintenance. In which case, I don't really have a problem. You are the problem. And you know, you're two levels down for me. So if you quit, well, the manager has to do the backfill. And I can tell the manager, you know, Ryan was here. He said this, that and the other. Maybe you can work with him. And that's exactly what you don't want is me ratting you out. But I can make it my manager's problem. On the other hand, if I agree with you and I'm like, you know what, this manager I have really isn't that good. Now I have three problems. This is really bad for me. One, I have to decide what to do with my manager. Maybe I have to manage them out. Two, if I do manage them out, I have to hire and train somebody else. And three, while they're gone, I have to do all their work myself. So you can see why, even if it's subconscious, I have a lot of reasons not to listen "

ex-Amazon VP (Ethan Evans): "One of the hardest things for people to understand is I've identified a legitimate weakness in my boss. I go to my skip. Why doesn't he do something? Well, if you come to me with a weakness in one of my employees, there is subconsciously this process that goes on that says, I have two choices. I can believe that you're overly sensitive and high maintenance. In which case, I don't really have a problem. You are the problem. And you know, you're two levels down for me. So if you quit, well, the manager has to do the backfill. And I can tell the manager, you know, Ryan was here. He said this, that and the other. Maybe you can work with him. And that's exactly what you don't want is me ratting you out. But I can make it my manager's problem. On the other hand, if I agree with you and I'm like, you know what, this manager I have really isn't that good. Now I have three problems. This is really bad for me. One, I have to decide what to do with my manager. Maybe I have to manage them out. Two, if I do manage them out, I have to hire and train somebody else. And three, while they're gone, I have to do all their work myself. So you can see why, even if it's subconscious, I have a lot of reasons not to listen "

1,249,200 views • 7 months ago

The singularity has already begun for math: Scott Aaronson is one of the world's leading quantum computing researchers and spent two years at OpenAI working on AI safety. We talked about why he thinks the singularity has already begun for math, who gets credit when AI writes the proof, and whether intelligence will still matter once machines do the thinking. In this episode: • Why the singularity has already begun for math • Who gets credit when AI writes the proof • What a proof that P = NP would be worth • Why he turned down getting rich to keep blogging • Whether intelligence will still matter Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:34 Why he updated so hard on AI 01:14 The people still denying AI progress 03:53 The singularity has already begun for math 08:30 Will human-driven math research survive 13:12 Who gets credit for AI-written papers 15:55 OpenAI's $15M Navier-Stokes proof 19:20 What if AI proved P = NP 23:07 Why AI is so good at finding counterexamples 26:13 The goalposts keep moving 28:52 Why AI disclosure matters in research 32:59 The fake Monet experiment 35:23 Why he blogs instead of getting rich 39:45 Are AI labs racing too fast 42:01 Will intelligence still matter 47:12 Book recommendations 52:27 Advice for students today 57:23 Reacting live to a new AI result 59:58 Outro

The singularity has already begun for math: Scott Aaronson is one of the world's leading quantum computing researchers and spent two years at OpenAI working on AI safety. We talked about why he thinks the singularity has already begun for math, who gets credit when AI writes the proof, and whether intelligence will still matter once machines do the thinking. In this episode: • Why the singularity has already begun for math • Who gets credit when AI writes the proof • What a proof that P = NP would be worth • Why he turned down getting rich to keep blogging • Whether intelligence will still matter Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:34 Why he updated so hard on AI 01:14 The people still denying AI progress 03:53 The singularity has already begun for math 08:30 Will human-driven math research survive 13:12 Who gets credit for AI-written papers 15:55 OpenAI's $15M Navier-Stokes proof 19:20 What if AI proved P = NP 23:07 Why AI is so good at finding counterexamples 26:13 The goalposts keep moving 28:52 Why AI disclosure matters in research 32:59 The fake Monet experiment 35:23 Why he blogs instead of getting rich 39:45 Are AI labs racing too fast 42:01 Will intelligence still matter 47:12 Book recommendations 52:27 Advice for students today 57:23 Reacting live to a new AI result 59:58 Outro

78,801 views • 19 days ago

Anders Hejlsberg (creator of TypeScript and C#, Anders Hejlsberg) on two reasons they used Go, not Rust: Me: If you think about Rust, what didn't it have that, if it had it, you would have picked it? Anders: I think there are two things. It doesn't have garbage collection. It's done manually, or it's done through the borrow checker. But the borrow checker doesn't allow circular data structures, and our compiler is chock-full of circular data structures. We have trees with parent pointers. We have types that are recursive. We have symbols that refer. It's everywhere. And like I said, if we had chosen to rewrite, we could have probably solved all of that. But it wouldn't have been just porting the code. It would also have been solving a whole bunch of new problems that we had bought ourselves by going that route. We tried, and it just wasn't feasible. So we were just trying to optimize for doing as little work as possible to get us to the payout. And honestly, Rust is no better when it comes to the quality of the generated code or the concurrency gains that we could have gotten out of it. Go is just great. We got all the bennies for less work by going that route.

Anders Hejlsberg (creator of TypeScript and C#, Anders Hejlsberg) on two reasons they used Go, not Rust: Me: If you think about Rust, what didn't it have that, if it had it, you would have picked it? Anders: I think there are two things. It doesn't have garbage collection. It's done manually, or it's done through the borrow checker. But the borrow checker doesn't allow circular data structures, and our compiler is chock-full of circular data structures. We have trees with parent pointers. We have types that are recursive. We have symbols that refer. It's everywhere. And like I said, if we had chosen to rewrite, we could have probably solved all of that. But it wouldn't have been just porting the code. It would also have been solving a whole bunch of new problems that we had bought ourselves by going that route. We tried, and it just wasn't feasible. So we were just trying to optimize for doing as little work as possible to get us to the payout. And honestly, Rust is no better when it comes to the quality of the generated code or the concurrency gains that we could have gotten out of it. Go is just great. We got all the bennies for less work by going that route.

62,661 views • 15 days ago

Why Rust is overused right now Martin Odersky (Creator of Scala): "Right now, rust is actually overused because a lot of people push Rust for things higher up in the stack Where a garbage collector is fine, but essentially you still want to code without. And that is, for me, a bit an exercise in doing it intellectually just because you can I don't really think there's a big sense in it. If you have the memory for a garbage collector, you should absolutely use one, because it makes a lot of things simpler. So, yes, of course, if given enough brains, I can write code around and I can do that, but why should you? It can be much simpler."

Why Rust is overused right now Martin Odersky (Creator of Scala): "Right now, rust is actually overused because a lot of people push Rust for things higher up in the stack Where a garbage collector is fine, but essentially you still want to code without. And that is, for me, a bit an exercise in doing it intellectually just because you can I don't really think there's a big sense in it. If you have the memory for a garbage collector, you should absolutely use one, because it makes a lot of things simpler. So, yes, of course, if given enough brains, I can write code around and I can do that, but why should you? It can be much simpler."

215,992 views • 2 months ago

Bjarne Stroustrup is the creator of C++ and a former researcher at Bell Labs at its peak. I interviewed him about: • What made Bell Labs different • Programming language design: types, memory safety, bootstrapping • When abstraction improves performance • Anecdotes from building C++ • Thoughts on AI writing C++ • Mistakes he'd change while building C++ Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript: Thank you to this episode's sponsors for supporting my work: • Cursor 3: a unified workspace for building software with agents, check it out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Timestamps: 0:00 - Intro 0:50 - The origin of C++ 8:46 - What Bell Labs was like 17:24 - Dennis Ritchie 24:00 - When to build a programming language 31:59 - Bootstrapping a language 33:58 - C++ is not object-oriented 37:32 - Discussing type systems 46:20 - Memory safety 49:26 - Standards committee anecdotes 1:09:40 - Adding automatic garbage collection to C++ 1:18:25 - Template instantiation is Turing complete 1:21:57 - Abstraction and performance 1:28:51 - AI writing code 1:35:54 - His motivation 1:39:18 - Famous quotes 1:46:48 - Reflecting on building C++ 1:49:12 - Top C++ book recommendation 1:50:59 - Advice for his younger self 1:58:06 - Outro

Bjarne Stroustrup is the creator of C++ and a former researcher at Bell Labs at its peak. I interviewed him about: • What made Bell Labs different • Programming language design: types, memory safety, bootstrapping • When abstraction improves performance • Anecdotes from building C++ • Thoughts on AI writing C++ • Mistakes he'd change while building C++ Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript: Thank you to this episode's sponsors for supporting my work: • Cursor 3: a unified workspace for building software with agents, check it out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Timestamps: 0:00 - Intro 0:50 - The origin of C++ 8:46 - What Bell Labs was like 17:24 - Dennis Ritchie 24:00 - When to build a programming language 31:59 - Bootstrapping a language 33:58 - C++ is not object-oriented 37:32 - Discussing type systems 46:20 - Memory safety 49:26 - Standards committee anecdotes 1:09:40 - Adding automatic garbage collection to C++ 1:18:25 - Template instantiation is Turing complete 1:21:57 - Abstraction and performance 1:28:51 - AI writing code 1:35:54 - His motivation 1:39:18 - Famous quotes 1:46:48 - Reflecting on building C++ 1:49:12 - Top C++ book recommendation 1:50:59 - Advice for his younger self 1:58:06 - Outro

322,916 views • 5 months ago

Boris Cherny ( Boris Cherny ) created Claude Code, but few know his full career story. Today I'm sharing an interview with him about how he grew as an engineer, we discussed: • Why every engineer needs "side quests" • Why being under leveled is a good thing • The story behind his growth to Principal (IC8) at Meta • Technical book that had the biggest impact on him as an engineer • The most important principle in product engineering • Claude Code stories & competition in AI coding products You can find the full episode here: • YouTube: • Spotify: • Transcript: • Apple:

Boris Cherny ( Boris Cherny ) created Claude Code, but few know his full career story. Today I'm sharing an interview with him about how he grew as an engineer, we discussed: • Why every engineer needs "side quests" • Why being under leveled is a good thing • The story behind his growth to Principal (IC8) at Meta • Technical book that had the biggest impact on him as an engineer • The most important principle in product engineering • Claude Code stories & competition in AI coding products You can find the full episode here: • YouTube: • Spotify: • Transcript: • Apple:

578,180 views • 10 months ago

Boris Cherny (Creator of Claude Code): "The one technical book I would recommend to everyone that has had the greatest impact on me as an engineer is functional programming in Scala. You're probably never going to use Scala day today, but the way it teaches you to think about coding problems is just such a change from the way that most people were in coding, either practically or in school. It's just. It's incredible. It's going to completely change the way that you code now. I think in types, when I code, the thing that matters in your code the most is the type signatures. This is more important than the code itself." Boris Cherny

Boris Cherny (Creator of Claude Code): "The one technical book I would recommend to everyone that has had the greatest impact on me as an engineer is functional programming in Scala. You're probably never going to use Scala day today, but the way it teaches you to think about coding problems is just such a change from the way that most people were in coding, either practically or in school. It's just. It's incredible. It's going to completely change the way that you code now. I think in types, when I code, the thing that matters in your code the most is the type signatures. This is more important than the code itself." Boris Cherny

365,661 views • 6 months ago

Avi Wigderson is the only person in history to have won both a Turing Award (computer science) and Abel Prize (math). I interviewed him all about his field. We discussed: • His intuition on a proof of P vs NP • Why we use SAT solvers for most NP problems • Zero knowledge proofs and their impact • Quantum computation and implications • Math and computer science's relationship Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript: Thank you to this episode's sponsors for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Timestamps: 00:00 - Intro 01:08 - P vs NP 14:51 - What if you relaxed correctness 25:38 - Why NP complete problems are equivalent 30:33 - Space vs time complexity 43:06 - Why people use SAT solvers 45:53 - Randomness is a resource 55:48 - Randomness depends on computational power 01:21:20 - Zero knowledge proofs and their significance 01:38:30 - Quantum computation and why it matters 01:56:24 - Math vs computer science 02:08:16 - Major breakthroughs and his experience 02:12:31 - Advice for his younger self 02:14:48 - Outro

Avi Wigderson is the only person in history to have won both a Turing Award (computer science) and Abel Prize (math). I interviewed him all about his field. We discussed: • His intuition on a proof of P vs NP • Why we use SAT solvers for most NP problems • Zero knowledge proofs and their impact • Quantum computation and implications • Math and computer science's relationship Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript: Thank you to this episode's sponsors for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Timestamps: 00:00 - Intro 01:08 - P vs NP 14:51 - What if you relaxed correctness 25:38 - Why NP complete problems are equivalent 30:33 - Space vs time complexity 43:06 - Why people use SAT solvers 45:53 - Randomness is a resource 55:48 - Randomness depends on computational power 01:21:20 - Zero knowledge proofs and their significance 01:38:30 - Quantum computation and why it matters 01:56:24 - Math vs computer science 02:08:16 - Major breakthroughs and his experience 02:12:31 - Advice for his younger self 02:14:48 - Outro

260,440 views • 5 months ago

Martin Odersky (Martin Odersky) is the creator of Scala and I interviewed him to compare different languages designs (Rust vs Zig vs Python vs Scala) and how AI will impact programming languages. In this episode: • Comparing Rust, Zig, Python, and Scala designs • Why its hard to write a compiler • Predictions about how AI will impact software • Why functional programming matters Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at Chapters: 00:00 Intro 00:44 Why care about functional programming 06:35 Why should people learn Scala 09:26 Rust vs Scala 12:42 Rust vs Zig 15:45 Scala vs Python 18:31 The programming languages that influenced him 22:16 How running on the JVM works 26:33 Why writing a compiler is hard 29:19 Why Twitter adopted Scala early on 31:00 How he believes AI will impact programming languages 43:40 Will there be less engineers in ten years 44:34 Top programming languages to learn to grow 46:18 Top technical book recommendation 46:51 Why he chose academia instead of industry 48:28 Reflecting on Scala 55:42 Advice for his younger self 56:33 Outro

Martin Odersky (Martin Odersky) is the creator of Scala and I interviewed him to compare different languages designs (Rust vs Zig vs Python vs Scala) and how AI will impact programming languages. In this episode: • Comparing Rust, Zig, Python, and Scala designs • Why its hard to write a compiler • Predictions about how AI will impact software • Why functional programming matters Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at Chapters: 00:00 Intro 00:44 Why care about functional programming 06:35 Why should people learn Scala 09:26 Rust vs Scala 12:42 Rust vs Zig 15:45 Scala vs Python 18:31 The programming languages that influenced him 22:16 How running on the JVM works 26:33 Why writing a compiler is hard 29:19 Why Twitter adopted Scala early on 31:00 How he believes AI will impact programming languages 43:40 Will there be less engineers in ten years 44:34 Top programming languages to learn to grow 46:18 Top technical book recommendation 46:51 Why he chose academia instead of industry 48:28 Reflecting on Scala 55:42 Advice for his younger self 56:33 Outro

103,762 views • 2 months ago

Leslie Lamport won a Turing award for his fundamental contributions to distributed systems. For instance, he invented the Paxos consensus algorithm that is a critical component of many distributed systems today. I interviewed him about his work and career. We discussed: • Why he never considered himself smart • The stories behind Paxos and Byzantine Generals Problem • Experiences working with Dijkstra • Paxos vs Raft Algorithms • How to improve your thinking Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

Leslie Lamport won a Turing award for his fundamental contributions to distributed systems. For instance, he invented the Paxos consensus algorithm that is a critical component of many distributed systems today. I interviewed him about his work and career. We discussed: • Why he never considered himself smart • The stories behind Paxos and Byzantine Generals Problem • Experiences working with Dijkstra • Paxos vs Raft Algorithms • How to improve your thinking Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

339,159 views • 8 months ago

Vlad Feinberg (Vlad Feinberg) is Google DeepMind’s pre-training area lead and I asked him all about how to land a job at a frontier lab like Google DeepMind, Anthropic or OpenAI. In this episode: • Skills frontier labs need • Differences between software engineering and AI research • Domains that matter for frontier research • Concrete steps engineers can take to get closer to research • Jeff Dean spot bonus story Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 - Intro 00:33 - Skills frontier labs need 08:45 - The difference between AI research and engineering 21:41 - Domains that matter for the frontier 30:50 - Marketing yourself to frontier labs 35:13 - Concrete steps engineers can take 38:29 - Overview of pre-training areas 47:23 - Jeff Dean spot bonus story 50:14 - Favorite Gemini war story 58:59 - Advice for his younger self 01:03:07 - Outro

Vlad Feinberg (Vlad Feinberg) is Google DeepMind’s pre-training area lead and I asked him all about how to land a job at a frontier lab like Google DeepMind, Anthropic or OpenAI. In this episode: • Skills frontier labs need • Differences between software engineering and AI research • Domains that matter for frontier research • Concrete steps engineers can take to get closer to research • Jeff Dean spot bonus story Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 - Intro 00:33 - Skills frontier labs need 08:45 - The difference between AI research and engineering 21:41 - Domains that matter for the frontier 30:50 - Marketing yourself to frontier labs 35:13 - Concrete steps engineers can take 38:29 - Overview of pre-training areas 47:23 - Jeff Dean spot bonus story 50:14 - Favorite Gemini war story 58:59 - Advice for his younger self 01:03:07 - Outro

191,973 views • 4 months ago

Brian Kernighan is a former Bell Labs member of technical staff, co-author of the original C book, and the one who popularized “Hello World.” We talked about what Bell Labs was like and the stories behind all the famous tools that were built there. In this episode: • Bell Labs culture and how he got hired • Day in the life at Bell Labs and the best engineer • Unix, C, and how awk got created • His favorite languages and advice for students Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:42 What Bell Labs was and how he got hired 06:34 Why so many inventions came from Bell Labs 14:15 A day in the life at Bell Labs 27:55 The most impressive people he worked with 33:50 The AT&T film explaining Unix 39:46 Why C was so influential 43:25 How awk was created 48:40 What he misses most about Bell Labs 54:10 Are LLMs bad for computer science education 01:01:46 His 1972 commit in the Go repo 01:03:43 Grace Emlen, the fake Bell Labs employee 01:07:39 Why he writes so many books 01:19:58 His favorite and least favorite languages 01:24:28 Advice for students and young people 01:27:42 Outro

Brian Kernighan is a former Bell Labs member of technical staff, co-author of the original C book, and the one who popularized “Hello World.” We talked about what Bell Labs was like and the stories behind all the famous tools that were built there. In this episode: • Bell Labs culture and how he got hired • Day in the life at Bell Labs and the best engineer • Unix, C, and how awk got created • His favorite languages and advice for students Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:42 What Bell Labs was and how he got hired 06:34 Why so many inventions came from Bell Labs 14:15 A day in the life at Bell Labs 27:55 The most impressive people he worked with 33:50 The AT&T film explaining Unix 39:46 Why C was so influential 43:25 How awk was created 48:40 What he misses most about Bell Labs 54:10 Are LLMs bad for computer science education 01:01:46 His 1972 commit in the Go repo 01:03:43 Grace Emlen, the fake Bell Labs employee 01:07:39 Why he writes so many books 01:19:58 His favorite and least favorite languages 01:24:28 Advice for students and young people 01:27:42 Outro

11,107 views • 5 days ago

Anders Hejlsberg ( Anders Hejlsberg ) is the creator of TypeScript and C#, and I asked him about how the TypeScript compiler got 10x faster through a rewrite in Go and his thoughts on how AI has impacted software engineering. In this episode: • How rewriting the compiler makes it 10x faster • Why they picked Go instead of Rust • Why they didn't use LLMs for the migration • Predictions on AI's impact on software engineering Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at Chapters: 00:00 Intro 00:48 Why write a compiler in JavaScript 07:29 Why rewrite the compiler in Go 14:49 LLMs for large migrations 20:12 Why Javascript is so popular 26:32 Why ever use Javascript on the backend 32:59 What it takes to build a programming language 37:06 Will there be fewer languages in 10 years 42:57 Hands on engineering vs delegation 49:14 Why fast tooling matters more now 51:16 AI software engineering predictions 58:52 The most technically challenging work 01:02:04 Top book recommendation 01:03:50 Advice for his younger self 01:05:00 Outro

Anders Hejlsberg ( Anders Hejlsberg ) is the creator of TypeScript and C#, and I asked him about how the TypeScript compiler got 10x faster through a rewrite in Go and his thoughts on how AI has impacted software engineering. In this episode: • How rewriting the compiler makes it 10x faster • Why they picked Go instead of Rust • Why they didn't use LLMs for the migration • Predictions on AI's impact on software engineering Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at Chapters: 00:00 Intro 00:48 Why write a compiler in JavaScript 07:29 Why rewrite the compiler in Go 14:49 LLMs for large migrations 20:12 Why Javascript is so popular 26:32 Why ever use Javascript on the backend 32:59 What it takes to build a programming language 37:06 Will there be fewer languages in 10 years 42:57 Hands on engineering vs delegation 49:14 Why fast tooling matters more now 51:16 AI software engineering predictions 58:52 The most technically challenging work 01:02:04 Top book recommendation 01:03:50 Advice for his younger self 01:05:00 Outro

104,338 views • 2 months ago

My goal was to record a conversation completely free of "AI doomer" takes as a timeline cleanser. For this episode, I interviewed Casey Muratori (Casey Muratori) who is a video game developer and programming creator also known for his talks about the history of computing. In this episode: • Surprising findings in computer history • Where bad code comes from • The only unbreakable law in software engineering • His career in the video game industry • Why you should read technical papers Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 01:08 Digging into computer science history 04:08 What shocked him 16:23 Dijkstra was depressed 26:17 The personal side of goto considered harmful 35:09 The anatomy of a 35 year mistake 50:12 Clean code horrible performance 58:33 How to write high performance code 01:01:18 Where bad code comes from 01:06:37 Why design docs before code is a bad idea 01:09:20 The only unbreakable law in software engineering 01:15:57 How he got into programming 01:21:16 Why he didnt work in big tech 01:30:44 Should you work at a startup early on 01:34:52 What video game engineering is like 01:39:57 Why preventing recursion is reasonable 01:43:24 Is vibe coding bad for the industry 01:50:17 Technical reading recommendation 01:54:27 Advice for his younger self 01:56:54 Outro

My goal was to record a conversation completely free of "AI doomer" takes as a timeline cleanser. For this episode, I interviewed Casey Muratori (Casey Muratori) who is a video game developer and programming creator also known for his talks about the history of computing. In this episode: • Surprising findings in computer history • Where bad code comes from • The only unbreakable law in software engineering • His career in the video game industry • Why you should read technical papers Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 01:08 Digging into computer science history 04:08 What shocked him 16:23 Dijkstra was depressed 26:17 The personal side of goto considered harmful 35:09 The anatomy of a 35 year mistake 50:12 Clean code horrible performance 58:33 How to write high performance code 01:01:18 Where bad code comes from 01:06:37 Why design docs before code is a bad idea 01:09:20 The only unbreakable law in software engineering 01:15:57 How he got into programming 01:21:16 Why he didnt work in big tech 01:30:44 Should you work at a startup early on 01:34:52 What video game engineering is like 01:39:57 Why preventing recursion is reasonable 01:43:24 Is vibe coding bad for the industry 01:50:17 Technical reading recommendation 01:54:27 Advice for his younger self 01:56:54 Outro

62,932 views • 1 month ago

Ryan Williams (Ryan Williams @rrwilliams.bsky.social) is a professor at MIT and the winner of the Gödel Prize in theoretical computer science. I interviewed him all about his work starting by asking him a popular Leetcode question (3 SUM). In this episode: • Solving Leetcode faster than popular "optimal" solutions • SAT problems and solvers • Hot takes on famous open questions • How to pick good research direction Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 - Intro 00:41 - Asking him a popular Leetcode question 03:54 - Doing better than the popular optimal solution 08:26 - Fine grained complexity 17:00 - A severe strengthening of P vs NP 24:38 - SAT problems and solvers 34:51 - Hot takes on famous open questions 46:57 - Simulating space with time 01:01:02 - Why he solves hard problems 01:02:35 - How to pick good research direction 01:07:14 - Technical book recommendations 01:08:31 - Advice for his younger self 01:11:56 - Outro

Ryan Williams (Ryan Williams @rrwilliams.bsky.social) is a professor at MIT and the winner of the Gödel Prize in theoretical computer science. I interviewed him all about his work starting by asking him a popular Leetcode question (3 SUM). In this episode: • Solving Leetcode faster than popular "optimal" solutions • SAT problems and solvers • Hot takes on famous open questions • How to pick good research direction Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 - Intro 00:41 - Asking him a popular Leetcode question 03:54 - Doing better than the popular optimal solution 08:26 - Fine grained complexity 17:00 - A severe strengthening of P vs NP 24:38 - SAT problems and solvers 34:51 - Hot takes on famous open questions 46:57 - Simulating space with time 01:01:02 - Why he solves hard problems 01:02:35 - How to pick good research direction 01:07:14 - Technical book recommendations 01:08:31 - Advice for his younger self 01:11:56 - Outro

148,279 views • 4 months ago

Marc Brooker ( Marc Brooker ) is a Distinguished Eng at AWS who has been building distributed systems there for almost 2 decades. I interviewed him about technical learnings from his experience. We discussed: • Learnings from 3000+ post mortems • When caching is a bad idea • How software engineering is changing • Visibility and apparent expertise • How to find the best problems Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

Marc Brooker ( Marc Brooker ) is a Distinguished Eng at AWS who has been building distributed systems there for almost 2 decades. I interviewed him about technical learnings from his experience. We discussed: • Learnings from 3000+ post mortems • When caching is a bad idea • How software engineering is changing • Visibility and apparent expertise • How to find the best problems Where to watch: • YouTube: • Spotify: • Apple Podcasts: • Transcript:

220,948 views • 6 months ago

Why Microsoft didn't have LLMs do their recent Typescript native rewrite in Go Anders Hejlsberg (Creator of Typescript): "If we just let AI loose on, what is it, half a million lines of code that we have in the old compiler? Well, I don't know that that would absolve us from then having go in and carefully examining every line that came out of it to make sure that there were no hallucinations. Right. Unless you have 100% perfect test coverage, you probably still gotta go check all of that. Now I think a better approach, quite honestly, would be enlist AI to write a program that helps you translate from TypeScript to go, because at that point you can park the stochastic ness in that program and then you can get deterministic behavior whenever you run the program, which means you get the same transformation every time you run it. Right. That's always the thing about AI that people forget it's not deterministic. Right. So you can't really trust that it's going to do the same thing twice. For the full conversation, you can search Anders Hejlsberg's name on my YouTube, Spotify or Apple Podcasts (link in bio)

Why Microsoft didn't have LLMs do their recent Typescript native rewrite in Go Anders Hejlsberg (Creator of Typescript): "If we just let AI loose on, what is it, half a million lines of code that we have in the old compiler? Well, I don't know that that would absolve us from then having go in and carefully examining every line that came out of it to make sure that there were no hallucinations. Right. Unless you have 100% perfect test coverage, you probably still gotta go check all of that. Now I think a better approach, quite honestly, would be enlist AI to write a program that helps you translate from TypeScript to go, because at that point you can park the stochastic ness in that program and then you can get deterministic behavior whenever you run the program, which means you get the same transformation every time you run it. Right. That's always the thing about AI that people forget it's not deterministic. Right. So you can't really trust that it's going to do the same thing twice. For the full conversation, you can search Anders Hejlsberg's name on my YouTube, Spotify or Apple Podcasts (link in bio)

84,913 views • 2 months ago

Thariq Shihipar (Thariq) is an engineer on Anthropic’s Claude Code team I asked him how Anthropic makes the most out of the models for engineering and how the industry will change soon. In this episode: • Internal best practices in leveraging the models • What percent of Anthropic's work is fully autonomous • How Anthropic maintains higher volumes of code • What has worked in preventing AI-written breakages Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:29 Onboarding at Anthropic 02:53 Internal capabilities vs external perception 06:16 Model vs Harness 08:55 What percent of Anthropics changes are fully autonomous 14:51 Computer use 17:42 How to make the most out of your compute 20:45 Loop engineering 22:47 Where the industry will go soon 26:02 Which model do Anthropic engineers use 27:38 Is learning a particular model worth it 30:56 Prompting tips for todays models 35:04 How to get the models to do tasteful work 39:00 How much of writing is done by AI at Anthropic 45:36 Code ownership and maintenance at Anthropic 52:04 How Anthropic prevents breakages 55:24 Visibility and sharing your work 58:42 Luck surface area example 01:00:57 Should people still learn to code 01:07:42 Advice for his younger self 01:09:58 Outro

Thariq Shihipar (Thariq) is an engineer on Anthropic’s Claude Code team I asked him how Anthropic makes the most out of the models for engineering and how the industry will change soon. In this episode: • Internal best practices in leveraging the models • What percent of Anthropic's work is fully autonomous • How Anthropic maintains higher volumes of code • What has worked in preventing AI-written breakages Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:29 Onboarding at Anthropic 02:53 Internal capabilities vs external perception 06:16 Model vs Harness 08:55 What percent of Anthropics changes are fully autonomous 14:51 Computer use 17:42 How to make the most out of your compute 20:45 Loop engineering 22:47 Where the industry will go soon 26:02 Which model do Anthropic engineers use 27:38 Is learning a particular model worth it 30:56 Prompting tips for todays models 35:04 How to get the models to do tasteful work 39:00 How much of writing is done by AI at Anthropic 45:36 Code ownership and maintenance at Anthropic 52:04 How Anthropic prevents breakages 55:24 Visibility and sharing your work 58:42 Luck surface area example 01:00:57 Should people still learn to code 01:07:42 Advice for his younger self 01:09:58 Outro

65,784 views • 1 month ago