The Peterman Pod

Ryan Peterman

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

  1. 2 ημ. πριν

    Casey Muratori: Surprises In Computer History And Where Bad Code Comes From

    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-done Podcast 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-computer Thank 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) Outro Where 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_Muratori 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 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

    Casey Muratori: Surprises In Computer History And Where Bad Code Comes From

  2. 7 Σεπ

    How Anthropic Builds And How Engineering Will Change Soon | Thariq Shihipar

    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-done Podcast 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-engineering 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 (00:29) Onboarding at Anthropic (02:53) Internal capabilities vs external perception (06:16) Model vs Harness (08:55) What percent of Anthropics changes are fully autonomous (14:51) Computer use (17:42) How to make the most out of your compute (20:45) Loop engineering (22:47) Where the industry will go soon (26:02) Which model do Anthropic engineers use (27:38) Is learning a particular model worth it (30:56) Prompting tips for todays models (35:04) How to get the models to do tasteful work (39:00) How much of writing is done by AI at Anthropic (45:36) Code ownership and maintenance at Anthropic (52:04) How Anthropic prevents breakages (55:24) Visibility and sharing your work (58:42) Luck surface area example (01:00:57) Should people still learn to code (01:07:42) Advice for his younger self (01:09:58) Outro Where 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/@ryanlpeterman Referenced 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

    How Anthropic Builds And How Engineering Will Change Soon | Thariq Shihipar

  3. 31 Αυγ

    Creator of Scala: Comparing Languages And How AI Will Impact Them | Martin Odersky

    Martin Odersky is the creator of Scala and I interviewed him to compare different languages designs (Rust vs Zig vs Python vs Scala) and how AI will impact programming languages. • 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/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=n49ky 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 (00:44) Why care about functional programming (06:35) Why should people learn Scala (09:26) Rust vs Scala (12:42) Rust vs Zig (15:45) Scala vs Python (18:31) The programming languages that influenced him (22:16) How running on the JVM works (26:33) Why writing a compiler is hard (29:19) Why Twitter adopted Scala early on (31:00) How he believes AI will impact programming languages (43:40) Will there be less engineers in ten years (44:34) Top programming languages to learn to grow (46:18) Top technical book recommendation (46:51) Why he chose academia instead of industry (48:28) Reflecting on Scala (55:42) Advice for his younger self (56:33) Outro Where 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/odersky 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: • 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

    Creator of Scala: Comparing Languages And How AI Will Impact Them | Martin Odersky

  4. 24 Αυγ

    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

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

  5. 17 Αυγ

    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/

    Creator of TypeScript: 10x Faster Typescript, Why AI Won't Replace SWEs | Anders Hejlsberg

  6. 10 Αυγ

    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

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

  7. 3 Αυγ

    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

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

  8. 27 Ιουλ

    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/

    Turing Award Winner: Early AI, LLM Predictions, Causality | Judea Pearl
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Sharing the transparent career stories of technical people. Hosted by an ex-Staff engineer at Instagram

Πληροφορίες

  • Δημιουργός
    Ryan Peterman
  • Έτη παρουσίας
    2024 - 2026
  • Επεισόδια
    67
  • Καταλληλότητα
    Κατάλληλο
  • Πνευματικά δικαιώματα
    © Ryan Peterman
  • Ιστότοπος εκπομπής
    The Peterman Pod

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