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The Peterman Pod

Ryan Peterman

Sharing the transparent career stories of technical people. Hosted by an ex-Staff engineer at Instagram

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  • 22 episodes
  • weekly
  • Avg 1 hr 18 min
  • English

Episodes 22

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  • August 24 · 57 min

    Sergey Levine: Current State of Humanoid Robotics, China & Future Predictions

    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-done Podcast 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=n49ky Thank 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) Outro Where 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/@ryanlpeterman Referenced 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

  • August 17 · 1 hr 5 min

    Creator of TypeScript: 10x Faster Typescript, Why AI Won't Replace SWEs | 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. • 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-done Podcast 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-faster 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 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) Outro Where 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/@ryanlpeterman Referenced 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/

  • August 10 · 1 hr 8 min

    Creator of Lean: Handwritten Math Will Change Dramatically | Leonardo de Moura

    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-done Podcast 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-handwritten Thank 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) Outro Where 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/Leonard41111588 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/@ryanlpeterman Referenced 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

  • August 3 · 1 hr 5 min

    Creator of Lua: Scripting, Programming Languages, Predictions | Roberto Ierusalimschy

    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-done Podcast 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-programming Thank 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) Outro Where to find Roberto: • Website: https://www.inf.puc-rio.br/~roberto/ • Wikipedia: https://en.wikipedia.org/wiki/Roberto_Ierusalimschy 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/@ryanlpeterman Referenced 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

  • July 27 · 1 hr 27 min

    Turing Award Winner: Early AI, LLM Predictions, Causality | Judea Pearl

    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-done Podcast 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-llm Thank 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) Outro Where 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_Pearl 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/@ryanlpeterman Referenced 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/

  • July 20 · 1 hr 24 min

    Creator of OCaml: Functional Programming, Formal Verification, Programming Languages | Xavier Leroy

    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-done Podcast 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-programming Thank 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) Outro Where 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/@ryanlpeterman Referenced 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/

  • July 13 · 59 min

    Turing Award Winner: TPU vs GPU vs CPU, Computer Architecture, RISC vs CISC | David Patterson

    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-done Podcast 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=n49ky Timestamps: (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) Outro Where 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/@ryanlpeterman Referenced 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)

  • July 6 · 1 hr 1 min

    Turing Award Winner: NSA, Public Key Cryptography, Crypto Wars | Martin Hellman

    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-done Podcast 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-key Thank 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) Outro Where 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/@ryanlpeterman Referenced 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

  • June 29 · 1 hr 12 min

    MIT Complexity Theorist: Why You Can Do Better Than “Optimal” On Leetcode & SAT | Ryan Williams

    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-done Podcast 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-leetcode Thank 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) Outro Where 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/rrwilliams 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/@ryanlpeterman Referenced 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

  • June 22 · 1 hr 22 min

    OpenAI Eng & Dev Tools Founder: How Software Engineering Is Changing | Charlie Marsh

    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-done Podcast 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-founder Thank 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) Outro Where to find Charlie: • LinkedIn: https://www.linkedin.com/in/marshcharles/ • GitHub: https://github.com/charliermarsh • X/Twitter: https://x.com/charliermarsh 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/@ryanlpeterman Referenced 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

  • June 15 · 1 hr 4 min

    Google DeepMind Pre-Training Lead: How To Land a Job at a Frontier Lab | 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. • 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-done Podcast 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-lead Thank 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) Outro Where 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/@ryanlpeterman Referenced 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

  • June 8 · 1 hr 27 min

    Co-Creator of Haskell: Functional Programming, Thinking in Types, Useless Languages | Simon Jones

    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-functional Thank 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 self Where 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/@ryanlpeterman Referenced 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

  • June 1 · 2 hr 15 min

    Turing Award Winner: P vs NP, Zero-Knowledge Proofs, Quantum Computation | Avi Wigderson

    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-zero Thank 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) Outro Where to find Avi: • Wikipedia: https://en.wikipedia.org/wiki/Avi_Wigderson • Personal Website: https://www.math.ias.edu/avi/home 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/@ryanlpeterman Referenced 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

  • May 25 · 2 hr 1 min

    Dropbox’s Former Most Senior Eng: Building Great Systems and Advice for the AI Era | James Cowling

    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-building Thank 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 Intro 00:00:53 Systems work during his PhD 00:13:05 Dropbox technical deep dive 00:21:57 Why Dropbox migrated from AWS 00:36:40 How to do massive migrations 00:44:31 Simplicity vs complexity in promos 00:49:23 What technical teams should be focused on 01:00:25 Doing the right thing vs promo hypothetical 01:08:13 Why he dipped into management sometimes 01:11:36 Why you should not lead by example 01:23:23 How to mentor Senior Staff engineers 01:27:30 Career advice for the AI era 01:37:21 Why he started his own company 01:46:05 The most technically challenging work of his career 01:48:10 How he got involved in Silicon Valley 01:52:16 Career regrets 01:55:54 Top technical book recommendation 01:56:36 Younger self and permanent underclass advice Where 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/@ryanlpeterman Referenced 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

  • May 18 · 1 hr 59 min

    Creator of C++: Bell Labs, Negative Overhead Abstraction, Mistakes | Bjarne Stroustrup

    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-overhead 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 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 - 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 𝗪𝗵𝗲𝗿𝗲 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/@ryanlpeterman 𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝗱 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

  • May 11 · 1 hr 3 min

    Harvard Professor: CS50, What Matters More Than CS, Lecturing Well | David J Malan

    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-matters 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 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 - Intro 1:09 - Getting into computer science 3:27 - Becoming the professor of CS50 11:19 - How to lecture well 14:25 - Depth vs engagement in education 18:11 - Why don't we consolidate educational resources 23:20 - Why start with C 31:51 - The ideal use of AI in education 34:54 - Cheating and AI 38:21 - Should we really learn CS still? 45:24 - College vs online education 47:06 - The most difficult concept to learn 51:00 - Growth vs fixed mindset 52:35 - The future of CS50 55:56 - Biggest career regret 1:00:29 - Top book recommendations 1:02:36 - Advice for his younger self 1:03:35 - Outro 𝗪𝗵𝗲𝗿𝗲 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/@davidjmalan 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/@ryanlpeterman 𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝗱 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

  • May 4 · 43 min

    PyTorch Eng Director: Promo Hacking, Industry Shifts, Regrets | John Myles White

    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-industry 𝗕𝗿𝗼𝘂𝗴𝗵𝘁 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 - Intro 0:54 - Is he bullish on MSL 5:23 - Running promotions at Meta 15:15 - Growing at Meta 22:22 - Julia core language contributor 29:24 - Academics failing into industry 31:48 - Stats book recommendations 38:02 - Biggest career regret 41:05 - Advice for his younger self 42:46 - Outro 𝗪𝗵𝗲𝗿𝗲 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/johnmyleswhite 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/@ryanlpeterman 𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝗱 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

  • April 27 · 34 min

    Turing Award Winner: Data Abstraction, Dijkstra, Distributed Systems | Barbara Liskov

    Barbara Liskov is a Turing Award winner known for her work in programming languages and distributed systems. We discussed the major problems she solved in her career, stories about Dijkstra, getting rejected from Princeton because she was a woman and misc topics around her work. 🔸 My keyboard Kickstarter: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done 𝗣𝗼𝗱𝗰𝗮𝘀𝘁 𝗹𝗶𝗻𝗸𝘀: • YouTube: https://youtu.be/T9CGjbPZeaM • Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835 • Transcript: https://www.developing.dev/p/turing-award-winner-data-abstraction 𝗘𝗽𝗶𝘀𝗼𝗱𝗲 𝗹𝗶𝗻𝗸𝘀: • Go To Statement Considered Harmful: https://homepages.cwi.nl/~storm/teaching/reader/Dijkstra68.pdf • Viewstamped Replication: https://www.cs.princeton.edu/courses/archive/fall09/cos518/papers/viewstamped.pdf 𝗧𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀: 0:00 - Intro 1:00 - Getting rejected from Princeton 2:53 - The software crisis 9:03 - The drawbacks of Python 10:17 - Getting into distributed computing 13:09 - Paxos vs Viewstamped replication 21:44 - The significance of Dijkstras letter 25:04 - Why she stayed in academia 30:39 - Why her award was questioned 33:51 - Outro 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗕𝗮𝗿𝗯𝗮𝗿𝗮: • Wikipedia: https://en.wikipedia.org/wiki/Barbara_Liskov 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/@ryanlpeterman

  • April 20 · 56 min

    Turing Award Winner: Postgres, Disagreeing with Google, Future Problems | Mike Stonebraker

    Mike Stonebraker is a Turing Award winner famous for his contributions to fundamental database technologies. We discussed the story behind building Postgres, where he disagrees with Google/Amazon on databases, and what he's working on now. 🔸 My keyboard Kickstarter: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done 𝗣𝗼𝗱𝗰𝗮𝘀𝘁 𝗹𝗶𝗻𝗸𝘀: • YouTube: https://youtu.be/YPObBOwIrHk • Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835 • Transcript: https://www.developing.dev/p/turing-award-winner-postgres-disagreeing 𝗘𝗽𝗶𝘀𝗼𝗱𝗲 𝗹𝗶𝗻𝗸𝘀: • Red book of database readings: http://www.redbook.io/ • BEAVER: An Enterprise Benchmark for Text-to-SQL: https://arxiv.org/abs/2409.02038 𝗧𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀: 0:00 - Intro 1:03 - How he got into databases 6:43 - Competing with Oracle 9:07 - What made Postgres special 15:55 - One size fits none 21:37 - Why he disagreed with Google 29:14 - Why he chose academia over big tech 30:58 - Replacing state in an OS with a DB 42:02 - Future problems in databases 51:36 - Technical book recommendations to learn databases 52:20 - Advice for younger self 55:52 - Outro 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗠𝗶𝗸𝗲: • His current company DBOS: https://dbos.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/@ryanlpeterman

  • April 13 · 1 hr 11 min

    AWS Distinguished Eng: Learning From 3000 Incidents And How Engineering Is Changing | Marc Brooker

    In this episode, I talked to Marc Brooker, a distinguished engineer at AWS who started there as a new grad and rose through the ranks. We discussed technical learnings from 3,000+ cloud system postmortems, how software engineering is changing with AI, how to find impactful problems and much more. 🔶 My keyboard Kickstarter: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done 𝗣𝗼𝗱𝗰𝗮𝘀𝘁 𝗹𝗶𝗻𝗸𝘀: • YouTube: https://youtu.be/u3GjIXP9N0s • Spotify: https://open.spotify.com/episode/1qX2GfpbzxzGpGvDZVINdO?si=wsDGZo9PTbCNalKVybFVnA • Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835 • Transcript: https://www.developing.dev/p/aws-distinguished-eng-learnings-from 𝗘𝗽𝗶𝘀𝗼𝗱𝗲 𝗹𝗶𝗻𝗸𝘀: • Post we discussed on hobbies and apparent expertise: https://brooker.co.za/blog/2023/04/20/hobbies.html • Post on software engineering changing: https://brooker.co.za/blog/2026/02/07/you-are-here.html • Post about Senior engineers and AI: https://brooker.co.za/blog/2026/03/20/ic-leadership.html • Post on Junior engineers and AI: https://brooker.co.za/blog/2026/03/25/ic-junior.html 𝗧𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀: 0:00 - Intro 1:27 - Finding problems that matter 11:42 - Learnings from 3000 postmortems 23:58 - Why caches are bad 29:37 - How AI will change software engineering 36:49 - Advice for junior engineers given AI 44:02 - Thoughts for senior engineers 49:59 - Why engineers should write 57:51 - Visibility and apparent expertise 1:04:23 - AWS engineers he admires 1:06:53 - Technical book recommendations 1:09:06 - Advice for his younger self 1:10:37 - Outro 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗠𝗮𝗿𝗰: • LinkedIn: https://www.linkedin.com/in/marc-brooker-b431772b/ • Twitter/X: https://x.com/MarcJBrooker • Personal Blog: https://brooker.co.za/blog/ 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/@ryanlpeterman

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