The Peterman Pod

Jaksot

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  Casey Muratori: Surprises In Computer History And Where Bad Code Comes From 14.09.2026 1t 57min

  Casey Muratori is a video game developer and programming creator also known for his talks about the history of software and computing. We talked about surprising parts he found while digging through computer history, where bad code comes from, and his career story.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/jHLbL1Eg4gM• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/casey-muratori-surprises-in-computerThank you to this episode's sponsors 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 https://jira.dev/• 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 https://workos.com/Timestamps:(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) OutroWhere to find Casey:• Website: https://caseymuratori.com/• Newsletter: https://www.computerenhance.com/• X/Twitter: https://x.com/cmuratori• GitHub: https://github.com/cmuratori• YouTube: https://www.youtube.com/@MollyRocket• Bluesky: https://bsky.app/profile/cmuratori.bsky.social• Twitch: https://www.twitch.tv/molly_rocket• Handmade Network: https://handmade.network/m/cmuratori• Wikipedia: https://en.wikipedia.org/wiki/Casey_MuratoriWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• The Root of the Root of All Evil: https://computerenhance.com/theroot• The Big OOPS: Anatomy of a 35-Year Mistake: https://www.youtube.com/watch?v=wo84LFzx5nI• Edsger Dijkstra's "Notes on Structured Programming": https://www.cs.utexas.edu/~EWD/transcriptions/EWD02xx/EWD249/EWD249.html• Donald Knuth's "Structured Programming with go to Statements": https://doi.org/10.1145/356635.356640• Edsger Dijkstra's "Go To Statement Considered Harmful": https://www.cs.utexas.edu/~EWD/transcriptions/EWD02xx/EWD215.html• Ivan Sutherland's Sketchpad thesis: https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-574.html• Clean Code, Horrible Performance: https://www.computerenhance.com/p/clean-code-horrible-performance• Where Does Bad Code Come From?: https://www.youtube.com/watch?v=7YpFGkG-u1w• The Only Unbreakable Law: https://www.youtube.com/watch?v=5IUj1EZwpJY• Dijkstra letter's reference: https://medium.com/@acidflask/this-guys-arrogance-takes-your-breath-away-5b903624ca5f#.1rdj838x6
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  How Anthropic Builds And How Engineering Will Change Soon | Thariq Shihipar 07.09.2026 1t 10min

  Thariq Shihipar 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.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/2Kch3tWMnw8• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/how-anthropic-builds-and-how-engineeringThank you to this episode's sponsor 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 https://workos.com/Timestamps:(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) OutroWhere to find Thariq:• X/Twitter: https://x.com/trq212• LinkedIn: https://www.linkedin.com/in/thariqshihipar/• Personal Website: https://www.thariq.io/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Anthropic's post on removing 80% of Claude Code's system prompt: https://claude.com/blog/the-new-rules-of-context-engineering-for-claude-5-generation-models
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  Creator of Scala: Comparing Languages And How AI Will Impact Them | Martin Odersky 31.08.2026 57min

  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.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/LdN4sPWM-WY• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/creator-of-scala-comparing-languages?r=n49kyThank 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 https://workos.com/• Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at https://jira.dev/Timestamps:(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) OutroWhere to find Martin:• Wikipedia: https://en.wikipedia.org/wiki/Martin_Odersky• Website: https://people.epfl.ch/martin.odersky• X/Twitter: https://x.com/odersky• GitHub: https://github.com/oderskyWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Structure and Interpretation of Computer Programs: https://web.mit.edu/6.001/6.037/sicp.pdf• A Brief, Incomplete, and Mostly Wrong History of Programming Languages (book): http://james-iry.blogspot.com/2009/05/brief-incomplete-and-mostly-wrong.html
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  Sergey Levine: Current State of Humanoid Robotics, China & Future Predictions 24.08.2026 57min

  Sergey Levine is one of the world's top robotics researchers and co-founder of Physical Intelligence. We talked about where humanoid robotics is today, thoughts on the Chinese robotics ecosystem, and his predictions for future timelines.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/9OSbaPjv0Rc• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/sergey-levine-current-state-of-humanoid?r=n49kyThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:37) Where are we today(04:20) Most surprising capabilities so far(07:03) The most inspiring real world robotics(08:36) If OpenAI or Anthropic got into robotics(10:22) Chinese robotics(13:15) Will one lab breakout from the rest(16:59) Thoughts on a concrete roadmap(21:03) Generalization and demonstrating it(26:04) Types of data and which is best for robotics(34:34) Why humanoid robotics differs from Waymo(37:10) If humanoid robotics failed here is why(39:55) Are there hot take modeling architectures in robotics(42:05) Thoughts on AI safety in robotics(46:44) Top robotics research paper recommendation(49:35) Why is Boston Dynamics less top of mind(53:47) Advice for his younger self(56:42) OutroWhere to find Sergey:• Google Scholar: https://scholar.google.com/citations?user=8R35rCwAAAAJ&hl=en• Website: https://people.eecs.berkeley.edu/~svlevine/• Wikipedia: https://en.wikipedia.org/wiki/Sergey_Levine• X/Twitter: https://x.com/svlevine?lang=en• LinkedIn: https://www.linkedin.com/in/sergey-levine-5a31a24/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware (ALOHA / ACT paper): https://arxiv.org/abs/2304.13705• Emergence of Human to Robot Transfer in Vision-Language-Action Models: https://arxiv.org/abs/2512.22414• Summary of human to robot paper: https://www.pi.website/research/human_to_robot
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  Creator of TypeScript: 10x Faster Typescript, Why AI Won't Replace SWEs | Anders Hejlsberg 17.08.2026 1t 5min

  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.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://www.youtube.com/watch?v=cywK3XYYJ2o• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/creator-of-typescript-10x-fasterThank 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 https://workos.com/• Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at https://jira.dev/Timestamps:(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) OutroWhere to find Anders:• GitHub: https://github.com/ahejlsberg• X/Twitter: https://x.com/ahejlsberg• Wikipedia: https://en.wikipedia.org/wiki/Anders_Hejlsberg• LinkedIn: https://www.linkedin.com/in/ahejlsberg/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Flow type checker repository: https://github.com/facebook/flow• TypeScript compiler repository: https://github.com/microsoft/TypeScript• Algorithms + Data Structures = Programs (book): https://en.wikipedia.org/wiki/Algorithms_%2B_Data_Structures_%3D_Programs• TypeScript native rewrite: https://devblogs.microsoft.com/typescript/announcing-typescript-7-0/
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  Creator of Lean: Handwritten Math Will Change Dramatically | Leonardo de Moura 10.08.2026 1t 8min

  Leonardo de Moura is the creator of Lean and the Z3 theorem prover. I talked with him about how Lean works and why LLMs plus Lean will fundamentally change how we write software and do math.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/KzdYKeAqWhY• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/creator-of-lean-the-end-of-handwrittenThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:28) How formal verification works(05:21) A new way of writing software(13:15) Proof assistants vs programming languages(21:06) How Lean has assisted in mathematical breakthroughs(32:03) When is it worth formalizing software(33:29) How Lean will impact handwritten math(38:55) The Z3 theorem prover project he started(45:44) The most technically challenging work of his career(51:10) Lean vs its competitors(01:00:37) The future of Lean(01:04:10) Technical book recommendations(01:06:15) Advice for his younger self(01:07:10) OutroWhere to find Leonardo:• Wikipedia: https://en.wikipedia.org/wiki/Leonardo_de_Moura• Website: https://leodemoura.github.io/• GitHub: https://github.com/leodemoura• LinkedIn: https://www.linkedin.com/in/leonardo-de-moura-26a27b5/• X/Twitter: https://x.com/Leonard41111588Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Lean 4: https://github.com/leanprover/lean4• Mathlib: Lean Mathematical Library: https://github.com/leanprover-community/mathlib4• Lean4Lean: https://github.com/digama0/lean4lean• Liquid Tensor Experiment: https://xenaproject.wordpress.com/2020/12/05/liquid-tensor-experiment/• Veil protocol verification language: https://veil.dev/• Z3 theorem prover: https://github.com/Z3Prover/z3• seL4 formally verified microkernel: https://github.com/seL4/seL4
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  Creator of Lua: Scripting, Programming Languages, Predictions | Roberto Ierusalimschy 03.08.2026 1t 5min

  Roberto Ierusalimschy is the creator of the Lua programming language. I interviewed him about Lua's unique strengths, programming language design and predictions for how AI will impact programming languages.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/jCZnFKk6M9A• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/creator-of-lua-scripting-programmingThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:43) What sets Lua apart(08:35) Comparing Lua with Python(13:04) Top book recommendation on language design(14:20) How JIT works and why it is hard(23:21) Compiling Python and interpreting C(30:31) How cross language calls work(36:58) Lua unique design decisions(51:17) Predictions for AIs impact on languages(01:00:10) Top 3 languages to learn to become a better engineer(01:03:21) Advice for his younger self(01:04:19) OutroWhere to find Roberto:• Website: https://www.inf.puc-rio.br/~roberto/• Wikipedia: https://en.wikipedia.org/wiki/Roberto_IerusalimschyWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• The Evolution of Lua: https://www.lua.org/doc/hopl.pdf• LuaJIT: https://luajit.org/• How much does it cost: https://www.youtube.com/watch?v=EUvgoxBm7uc• JavaScript: The Good Parts (not an affiliate link): https://www.amazon.com/dp/0596517742
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  Turing Award Winner: Early AI, LLM Predictions, Causality | Judea Pearl 27.07.2026 1t 27min

  Judea Pearl is a Turing Award winner and a pioneer in artificial intelligence and causal reasoning. We talked about how he got into science, his major breakthroughs and his predictions for AI today.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/FleTXB1fAcQ• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/turing-award-winner-early-ai-llmThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:54) How he got into AI(11:17) Greatest scientist of all time(20:15) What people thought of AI in the 80s(26:23) Entering academia and researching AI(34:52) The invention of Bayesian networks(46:28) Pioneering work in causality(55:38) The causal hierarchy(59:34) LLMs and predictions(01:20:12) A restless mind pays(01:24:36) Advice for his younger self(01:26:37) OutroWhere to find Judea:• X/Twitter: https://twitter.com/yudapearl• Website: https://bayes.cs.ucla.edu/jp_home.html• Wikipedia: https://en.wikipedia.org/wiki/Judea_PearlWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• The Book of Why: https://en.wikipedia.org/wiki/The_Book_of_Why• Bayesian networks: https://en.wikipedia.org/wiki/Bayesian_network• Alpha-beta pruning: https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning• Pearl vortex: https://en.wikipedia.org/wiki/Pearl_vortex• Graphoid: https://en.wikipedia.org/wiki/Graphoid• Causality: Models, Reasoning, and Inference: https://en.wikipedia.org/wiki/Causality_(book)• Coexistence and Other Fighting Words: Selected Writings of Judea Pearl, 2002–2025: https://bayes.cs.ucla.edu/COEXISTENCE/
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  Creator of OCaml: Functional Programming, Formal Verification, Programming Languages | Xavier Leroy 20.07.2026 1t 24min

  Xavier Leroy (creator of OCaml) is an expert in compilers, formal verification of software and functional programming. This interview should be an approachable resource if you're curious about formal verification of software since I was learning that on the fly during it.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/9Cswiqrq6So• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/creator-of-ocaml-functional-programmingThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:43) What sets OCaml apart(04:39) OCaml vs Rust(07:57) Why is manual memory management more performant(11:21) Javascript vs OCaml(14:00) Famous Rob Pike quote(16:05) Type inference and how it works(22:12) What is formal verification and how does it work(40:07) What made multicore support difficult for OCaml(50:17) How programming languages interface and call each other(57:41) The danger of almost-correct LLM code(01:05:39) How LLMs will change programming languages(01:10:26) Industry vs academia(01:15:05) Most interesting unsolved problems(01:18:30) Top book recommendations for engineers(01:21:17) Advice for his younger self(01:23:31) OutroWhere to find Xavier:• Wikipedia: https://en.wikipedia.org/wiki/Xavier_Leroy• Website: https://xavierleroy.org/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• CompCert verified C compiler: https://compcert.org/• seL4 microkernel: https://sel4.systems/• Programming Pearls (book, not an affiliate link): https://www.amazon.com/dp/0201657880• How to Design Programs (book): https://htdp.org/
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  Turing Award Winner: TPU vs GPU vs CPU, Computer Architecture, RISC vs CISC | David Patterson 13.07.2026 59min

  David Patterson is a Turing Award winner famous for his contributions to computer architecture. I interviewed him about his past work, thoughts on GPU/TPUs and career advice from half a century of experience.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/Pn4ZwlEh5nw• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/turing-award-winner-tpu-vs-gpu-vs?r=n49kyTimestamps:(00:00) Intro(00:42) RISC vs CISC(12:51) Compilers(17:38) GPUs(23:07) GPU vs TPU vs CPU(32:12) Is Moores law dead?(38:04) GPU benchmarks(41:40) How to have a bad career(49:59) Courage and optimism(55:56) Advice for his younger self(58:15) OutroWhere to find David:• Wikipedia: https://en.wikipedia.org/wiki/David_Patterson_(computer_scientist)Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• AlexNet paper: https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf• David Patterson's “How to Have a Bad Career” talk: https://www.youtube.com/watch?v=Rn1w4MRHIhc• “Life Lessons from the First Half-Century of My Career”: https://cacm.acm.org/opinion/life-lessons-from-the-first-half-century-of-my-career/• The 7 Habits of Highly Effective People (book): https://en.wikipedia.org/wiki/The_7_Habits_of_Highly_Effective_People• Working (book): https://en.wikipedia.org/wiki/Working_(Terkel_book)
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  Turing Award Winner: NSA, Public Key Cryptography, Crypto Wars | Martin Hellman 06.07.2026 1t 1min

  Martin Hellman is a Turing Award winner who helped to invent public-key cryptography against the NSA's wishes. I interviewed him all about his work and why it broke the law at the time.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/AZLOETBCQM4• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/turing-award-winner-nsa-public-keyThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:34) Why his work broke the law(08:39) How people did encryption before(18:51) The crypto wars(26:22) The story behind Diffie Hellman key exchange(36:48) Signatures vs key exchange(43:05) RSA patent wars(48:08) Why inventions happen at similar times(50:29) What he worked on after cryptography(57:31) His thoughts on death(59:40) Advice for his younger self(01:00:45) OutroWhere to find Martin:• Wikipedia: https://en.wikipedia.org/wiki/Martin_Hellman• Website: https://ee.stanford.edu/~hellman/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Martin Hellman's “The Evolution of Public Key Cryptography”: https://www.youtube.com/watch?v=Tev3tVzH91s• Keys Under Doormats: https://cacm.acm.org/opinion/keys-under-doormats/• Cryptography's Role in Securing the Information Society (CRISIS report): https://nap.nationalacademies.org/catalog/5131/cryptographys-role-in-securing-the-information-society• Secure Communications Over Insecure Channels: https://doi.org/10.1145/359460.359473• New Directions in Cryptography: https://doi.org/10.1109/TIT.1976.1055638
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  MIT Complexity Theorist: Why You Can Do Better Than “Optimal” On Leetcode & SAT | Ryan Williams 29.06.2026 1t 12min

  Ryan Williams 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).Correction: In this podcast I say "lower bound" when I mean "upper bound" and vice versa. Was speaking using the intuition that lower is better for running time. In reality, the accurate usage is:"Lower bound" = A proven floor for a problem e.g. "no algorithm can possibly be faster""Upper bound" = A proven ceiling for a specific solution e.g. "there exists an algorithm this fast"Professor Williams answers as if I spoke accurately so the error didn't impact the flow of conversation. Just a correction for the record• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/AaK1SL2i_4Y• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/mit-complexity-theorist-on-leetcodeThank you to this episode's sponsor 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 https://workos.com/Timestamps:(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) OutroWhere to find Ryan:• Wikipedia: https://en.wikipedia.org/wiki/Ryan_Williams_(computer_scientist)• Website: https://people.csail.mit.edu/rrw/• LinkedIn: https://www.linkedin.com/in/r-ryan-williams-a1b534a/• X/Twitter: https://twitter.com/rrwilliamsWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Some Estimated Likelihoods for Computational Complexity: https://people.csail.mit.edu/rrw/likelihoods.pdf• Simulating Time with Square-Root Space: https://arxiv.org/abs/2502.17779• Cook and Mertz's tree evaluation paper: https://dl.acm.org/doi/10.1145/3618260.3649664
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  OpenAI Eng & Dev Tools Founder: How Software Engineering Is Changing | Charlie Marsh 22.06.2026 1t 22min

  Charlie Marsh is the founder of Astral, the Python devtool startup that was acquired by OpenAI. I inteviewed him about how software engineering is changing and learnings from starting his own company as an engineer.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/Iw65FD4MGgs• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/openai-eng-and-dev-tools-founderThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:40) Origin story(06:04) The front page of Hacker News(14:35) Why he chose Rust(20:10) Full codebase migration from Zig to Rust(28:40) LLM generated code and open source(35:34) Performance optimizations(44:54) Optimization with AI and combating slop(01:02:08) Learnings as an eng starting a company(01:17:55) Top technical talk recommendation(01:18:56) Advice for his younger self(01:22:00) OutroWhere to find Charlie:• LinkedIn: https://www.linkedin.com/in/marshcharles/• GitHub: https://github.com/charliermarsh• X/Twitter: https://x.com/charliermarshWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Python tooling could be much, much faster: https://notes.crmarsh.com/python-tooling-could-be-much-much-faster• The coolest PR he's ever seen: https://github.com/astral-sh/uv/pull/789• Andrew Kelley’s data-oriented design talk: https://www.youtube.com/watch?v=IroPQ150F6c• Ruff: https://github.com/astral-sh/ruff• uv: https://github.com/astral-sh/uv• ty: https://github.com/astral-sh/ty• Salsa: https://github.com/salsa-rs/salsa
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  Google DeepMind Pre-Training Lead: How To Land a Job at a Frontier Lab | Vlad Feinberg 15.06.2026 1t 4min

  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.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-donePodcast links:• YouTube: https://youtu.be/cDyi91onoJ8• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/google-deepmind-pre-training-leadThank you to this episode's sponsor 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 https://workos.com/Timestamps:(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) OutroWhere to find Vlad:• Personal Website: https://vladfeinberg.com/• Twitter/X: https://x.com/FeinbergVlad• LinkedIn: https://www.linkedin.com/in/vladimirfeinberg/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• How to Land a Job at a Frontier Lab: https://vladfeinberg.com/2026/05/10/how-to-land-a-job-at-a-frontier-lab.html• ThunderKittens: https://github.com/HazyResearch/ThunderKittens• Deedy's doomer Tweet: https://x.com/FeinbergVlad/status/2056383124829872466?s=20• Jacob Steinhardt's "Research as a Stochastic Decision Process": https://cs.stanford.edu/~jsteinhardt/ResearchasaStochasticDecisionProcess.html• The Scaling Book: https://jax-ml.github.io/scaling-book/• Dwarkesh and Reiner's video: https://www.youtube.com/watch?v=xmkSf5IS-zw
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  Co-Creator of Haskell: Functional Programming, Thinking in Types, Useless Languages | Simon Jones 08.06.2026 1t 27min

  Simon Peyton Jones is the co-creator of Haskell (pure functional programming language) and I interviewed him about functional programming, why it matters, and his thoughts on other programming languages.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/Podcast links:• YouTube: https://youtu.be/xcB_LF3cdqw• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/co-creator-of-haskell-functionalThank you to this episode's sponsor 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 https://workos.com/Timestamps:(00:00) Intro(00:39) What functional programming is(09:18) Downsides of functional programming(10:53) Specialized hardware for functional programming(21:47) Haskell is useless(25:59) Rust vs C(28:26) Haskell vs OCaml(35:26) Side effects in Haskell(44:26) Type systems(57:30) How the Haskell compiler works(01:04:35) Why Haskell is talked about more than used(01:09:07) Avoiding success at all costs(01:11:12) LLMs and programming languages(01:13:57) New programming language design(01:15:59) Should students continue to learn programming(01:22:33) Why Excel is his 2nd favorite programming language(01:25:04) Advice for his younger selfWhere to find Simon:• LinkedIn: https://www.linkedin.com/in/simonpj/• Wikipedia: https://en.wikipedia.org/wiki/Simon_Peyton_Jones• Personal Website: https://simon.peytonjones.org/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• Haskell is useless: https://www.youtube.com/watch?v=iSmkqocn0oQ• John Backus Turing Award lecture: https://worrydream.com/refs/Backus_1978_-_Can_Programming_Be_Liberated_from_the_von_Neumann_Style.pdf• Why functional programming matters: https://www.cs.kent.ac.uk/people/staff/dat/miranda/whyfp90.pdf• Excel is his 2nd favorite programming language: https://www.youtube.com/watch?v=_M4P5M85KO8
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  Turing Award Winner: P vs NP, Zero-Knowledge Proofs, Quantum Computation | Avi Wigderson 01.06.2026 2t 15min

  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.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/Podcast links:• YouTube: https://youtu.be/5GUcvSAJcJw• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/turing-award-winner-p-vs-np-zeroThank you to this episode's sponsor 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 https://workos.com/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) OutroWhere to find Avi:• Wikipedia: https://en.wikipedia.org/wiki/Avi_Wigderson• Personal Website: https://www.math.ias.edu/avi/homeWhere to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• PCP Theorem paper: https://www.cs.umd.edu/~gasarch/TOPICS/pcp/AS.pdf• Paper on SAT approximation hardness: https://www.cs.umd.edu/~gasarch/BLOGPAPERS/max3satl.pdf• Turing's paper: https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf• Original paper on NP completeness: https://www.cs.toronto.edu/~sacook/homepage/1971.pdf• Ryan William's breakthrough result on space vs time: https://people.csail.mit.edu/rrw/time-vs-space.pdf• Old result on space vs time: https://www-wjp.cs.uni-saarland.de/publikationen/HPV75.pdf• Paper describing constant space majority solution: https://people.cs.umass.edu/~barring/publications/bwbp.pdf• Fast primality test paper: https://www.sciencedirect.com/science/article/pii/0022314X80900840/pdf?md5=6f748cd82fa8efa1a637efab5f632baa&pid=1-s2.0-0022314X80900840-main.pdf• Deterministic primality test paper: https://www.cse.iitk.ac.in/users/manindra/algebra/primality_v6.pdf• Randomness vs observer paper: https://people.csail.mit.edu/silvio/Selected%20Scientific%20Papers/Pseudo%20Randomness/How_To_Generate_Cryptographically_Strong_Sequences_Of_Pseudo-Random_Bits.pdf• Hardness vs randomness paper: https://www.math.ias.edu/~avi/PUBLICATIONS/MYPAPERS/NOAM/HARDNESS/final.pdf• Erdos original sum vs product paper: https://users.renyi.hu/~p_erdos/1983-18.pdf• Terrence Tao sum vs product paper: https://arxiv.org/pdf/math/0301343• Seminal interactive proof paper: https://www.cs.miami.edu/home/burt/learning/csc609.221/goldwasser-micali-rackoff-knoweldge-complexity.pdf• Zero knowledge proof paper: https://www.math.ias.edu/~avi/PUBLICATIONS/MYPAPERS/GMW86/GMW86.pdf• Shor's algorithm original paper: https://arxiv.org/pdf/quant-ph/9508027• Lattice paper (new hard problems): https://dl.acm.org/doi/epdf/10.1145/258533.258604• MIP* vs RE paper: https://arxiv.org/pdf/2001.04383• Zero knowledge non-interactive proofs: https://eprint.iacr.org/2025/1296.pdf
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  Dropbox’s Former Most Senior Eng: Building Great Systems and Advice for the AI Era | James Cowling 25.05.2026 2t 1min

  James Cowling is the CTO at Convex and was previously the most senior engineer at Dropbox. We discussed technical details of his past projects, simplicity vs complexity, and career advice given where AI is today.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/Podcast links:• YouTube: https://youtu.be/3XkmNSuHFmY• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/dropboxs-former-most-senior-eng-buildingThank you to this episode's sponsor 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 https://workos.com/Timestamps:00:00:00 Intro00:00:53 Systems work during his PhD00:13:05 Dropbox technical deep dive00:21:57 Why Dropbox migrated from AWS00:36:40 How to do massive migrations00:44:31 Simplicity vs complexity in promos00:49:23 What technical teams should be focused on01:00:25 Doing the right thing vs promo hypothetical01:08:13 Why he dipped into management sometimes01:11:36 Why you should not lead by example01:23:23 How to mentor Senior Staff engineers01:27:30 Career advice for the AI era01:37:21 Why he started his own company01:46:05 The most technically challenging work of his career01:48:10 How he got involved in Silicon Valley01:52:16 Career regrets01:55:54 Top technical book recommendation01:56:36 Younger self and permanent underclass adviceWhere to find James:• LinkedIn: https://www.linkedin.com/in/jcowling/• Twitter/X: https://x.com/jamesacowling• His company: https://www.convex.dev/Where to find Ryan:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpetermanReferenced in this episode:• His PhD Thesis: https://www.usenix.org/system/files/conference/atc12/atc12-final118.pdf• Masters paper: https://www.cs.princeton.edu/courses/archive/fall19/cos418/papers/vr-revisited.pdf• Papercuts writing he mentioned: https://medium.com/@jamesacowling/embracing-papercuts-e6390055dfc4• "Don't lead by example": https://medium.com/@jamesacowling/dont-lead-by-example-4f86b1174e64• His writing about orienting teams around missions: https://medium.com/@jamesacowling/your-system-is-not-a-sports-team-e17f9eb16b94
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  Creator of C++: Bell Labs, Negative Overhead Abstraction, Mistakes | Bjarne Stroustrup 18.05.2026 1t 59min

  Bjarne Stroustrup is the creator of the C++ programming language and a former researcher at Bell Labs. We talked about what Bell Labs was like, programming language design, and interesting anecdotes from his experience.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/𝗣𝗼𝗱𝗰𝗮𝘀𝘁 𝗹𝗶𝗻𝗸𝘀:• YouTube: https://youtu.be/U46fJ2bJ-co• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/creator-of-c-bell-labs-negative-overhead𝗧𝗵𝗮𝗻𝗸 𝘆𝗼𝘂 𝘁𝗼 𝘁𝗵𝗶𝘀 𝗲𝗽𝗶𝘀𝗼𝗱𝗲'𝘀 𝘀𝗽𝗼𝗻𝘀𝗼𝗿𝘀 𝗳𝗼𝗿 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗺𝘆 𝘄𝗼𝗿𝗸:• Cursor 3: a unified workspace for building software with agents, check it out at https://cursor.com/• 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 https://workos.com/𝗧𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀:0:00 - Intro0:50 - The origin of C++8:46 - What Bell Labs was like17:24 - Dennis Ritchie24:00 - When to build a programming language31:59 - Bootstrapping a language33:58 - C++ is not object-oriented37:32 - Discussing type systems46:20 - Memory safety49:26 - Standards committee anecdotes1:09:40 - Adding automatic garbage collection to C++1:18:25 - Template instantiation is Turing complete1:21:57 - Abstraction and performance1:28:51 - AI writing code1:35:54 - His motivation1:39:18 - Famous quotes1:46:48 - Reflecting on building C++1:49:12 - Top C++ book recommendation1:50:59 - Advice for his younger self1:58:06 - Outro𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗕𝗷𝗮𝗿𝗻𝗲:• Wikipedia: https://en.wikipedia.org/wiki/Bjarne_Stroustrup• Personal Website: https://www.stroustrup.com/𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗥𝘆𝗮𝗻:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpeterman𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝗱 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗲𝗽𝗶𝘀𝗼𝗱𝗲:• "A History of C++": https://www.stroustrup.com/hopl2.pdf• "Evolving a language in and for the real world": https://www.stroustrup.com/hopl-almost-final.pdf• "Thriving in a Crowded and Changing World": https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2020/p2184r0.pdf• The lecture where he mentioned he lost half his hair: https://youtu.be/69edOm889V4?si=IAZxYNwlUALodEV7&t=474• Quotes I pulled: https://www.stroustrup.com/quotes.html
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  Harvard Professor: CS50, What Matters More Than CS, Lecturing Well | David J Malan 11.05.2026 1t 3min

  David Malan is a Harvard professor known for turning CS50 into a popular online computer science course. We discussed the story behind CS50, how to lecture well, and how AI is changing CS education including in cheating/academic dishonesty.• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/𝗣𝗼𝗱𝗰𝗮𝘀𝘁 𝗹𝗶𝗻𝗸𝘀:• YouTube: https://youtu.be/bB2o81DnKHk• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/harvard-professor-cs50-what-matters𝗧𝗵𝗮𝗻𝗸 𝘆𝗼𝘂 𝘁𝗼 𝘁𝗵𝗶𝘀 𝗲𝗽𝗶𝘀𝗼𝗱𝗲'𝘀 𝘀𝗽𝗼𝗻𝘀𝗼𝗿𝘀 𝗳𝗼𝗿 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝗺𝘆 𝘄𝗼𝗿𝗸:• Cursor 3: a unified workspace for building software with agents, check it out at https://cursor.com/• 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 https://workos.com/𝗧𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀:0:00 - Intro1:09 - Getting into computer science3:27 - Becoming the professor of CS5011:19 - How to lecture well14:25 - Depth vs engagement in education18:11 - Why don't we consolidate educational resources23:20 - Why start with C31:51 - The ideal use of AI in education34:54 - Cheating and AI38:21 - Should we really learn CS still?45:24 - College vs online education47:06 - The most difficult concept to learn51:00 - Growth vs fixed mindset52:35 - The future of CS5055:56 - Biggest career regret1:00:29 - Top book recommendations1:02:36 - Advice for his younger self1:03:35 - Outro𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗮𝘃𝗶𝗱:• Personal website: https://cs.harvard.edu/malan/• Facebook: https://www.facebook.com/dmalan• Github: https://github.com/dmalan• Instagram: https://www.instagram.com/davidjmalan/• LinkedIn: https://www.linkedin.com/in/malan/• Reddit: https://www.reddit.com/user/davidjmalan/• X/Twitter: https://x.com/davidjmalan• Threads: https://www.threads.com/@davidjmalan𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗥𝘆𝗮𝗻:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpeterman𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝗱 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗲𝗽𝗶𝘀𝗼𝗱𝗲:• His first program for CS50: https://x.com/davidjmalan/status/1432538424590929920• Paper about CS50 improvements: https://cs.harvard.edu/malan/publications/fp310-malan.pdf• Hitchhiker's Guide to the Galaxy: https://en.wikipedia.org/wiki/The_Hitchhiker%27s_Guide_to_the_Galaxy• How Computers Work book (not affiliate link): https://www.amazon.com/How-Computers-Work-Evolution-Technology/dp/078974984X
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  PyTorch Eng Director: Promo Hacking, Industry Shifts, Regrets | John Myles White 04.05.2026 43min

  John Myles White recently left his role as a director of engineering at Meta Superintelligence Labs (MSL) so we spoke freely about promo culture, how big tech has changed, and how his career grew.𝗣𝗼𝗱𝗰𝗮𝘀𝘁 𝗹𝗶𝗻𝗸𝘀:• YouTube: https://youtu.be/aPfnP4iAIH8• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835• Transcript: https://www.developing.dev/p/msl-eng-director-promo-hacking-industry𝗕𝗿𝗼𝘂𝗴𝗵𝘁 𝘁𝗼 𝘆𝗼𝘂 𝗯𝘆:• Cursor 3: a unified workspace for building software with agents, check it out at https://cursor.com/• My ergonomic keyboard project, you can follow along here: https://read.compose.llc/ 𝗧𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀:0:00 - Intro0:54 - Is he bullish on MSL5:23 - Running promotions at Meta15:15 - Growing at Meta22:22 - Julia core language contributor29:24 - Academics failing into industry31:48 - Stats book recommendations38:02 - Biggest career regret41:05 - Advice for his younger self42:46 - Outro𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗝𝗼𝗵𝗻:• LinkedIn: https://www.linkedin.com/in/john-myles-white-115697180/• X/Twitter: https://x.com/johnmyleswhite• Personal Website: https://www.johnmyleswhite.com/• Github: https://github.com/johnmyleswhite𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗥𝘆𝗮𝗻:• Newsletter: https://www.developing.dev/• X/Twitter: https://x.com/ryanlpeterman• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/• Threads: https://www.threads.com/@ryanlpeterman• Instagram: https://www.instagram.com/ryanlpeterman• TikTok: https://www.tiktok.com/@ryanlpeterman𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝗱 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗲𝗽𝗶𝘀𝗼𝗱𝗲:• Evaluating the design of the R language - https://www.researchgate.net/publication/240040602_Evaluating_the_Design_of_the_R_Language• Stats book he mentioned (not affiliate link) - https://www.amazon.com/Foundations-Agnostic-Statistics-Peter-Aronow/dp/1316631141• Stats book he mentioned (not affiliate link) - https://www.amazon.com/All-Statistics-Statistical-Inference-Springer/dp/0387402721