The Peterman Pod

The Peterman Pod

By Ryan PetermanTechnology
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The Peterman Pod episodes

  • 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/

    1 hr 28 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/

    1 hr 25 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)

    1 hr
  • 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

    1 hr 2 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

    1 hr 13 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

    1 hr 23 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

    1 hr 5 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

    1 hr 28 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

    2 hr 16 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

    2 hr 2 min

About The Peterman Pod

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

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