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Web infrastructure engineer and standards editor; chaired the IETF HTTP working group and co-authored core HTTP and Atom specifications.

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AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).

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Indonesian software engineer, educator and engineering manager at Zero One Group; open-source enthusiast writing at ripandis.com.

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Computer science professor who works on fast data processing; co-author of the simdjson parser and a weekly blogger about software performance since 2004.

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Creator of Flask and Jinja. Writes about software at lucumr.pocoo.org.

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Programmer, photographer and musician, best known for the Python Requests HTTP library and other Python tooling.

• Experimenting with making a little portable Requests–inspired Python module, called https://t.co/gzrf4pmNOY. Just for fun.

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Creator of the Keras deep-learning library and the ARC-AGI benchmark.

• > One could even define intelligence as the efficiency with which one converts experience into competence; by this definition they lag very far behind us Yes, one could define intelligence in this way, and one would be right. By this metric current AI is approximately 6 OOMs less intelligent than humans. Your ancestors' evolutionary history did not prepare you for Python programming, yet you can learn to competently program in Python in a few hundreds of hours. An LRM needs the training data equivalent of ~1B hours (on top of all of its non-programming related training data). Another dimensio…
  Quoting@DKokotajloDan Selsam is a current OpenAI capabilities researcher. (since 2022) He was my boss for a while. He doesn't have a twitter account but has made this public statement of his views on AI risk and sent it to me to share: Dan Selsam's Personal Statement on AI Risk: I have been working on AI for over fi…

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CEO of Vercel; creator of Next.js and Socket.IO. Writes at rauchg.com.

• I’m seeing teams at Vercel iterate just as fast on Zig, Go, Rust projects as TypeScript & Python ones. The days of language or runtime choice based on human convenience are over. Agents are the new compilers. They compile intent into fast software.

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Machine learning engineer and consultant focused on RAG and retrieval systems. He writes about applied AI engineering at jxnl.co and is the author of the instructor library.

• mf be like "it came to me in a dream" and its actually just 10 000 agent swarms writing markdown files on a sandbox and some python code

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Programmer, photographer and musician, best known for the Python Requests HTTP library and other Python tooling.

• Making a Python interpreter in 1024 bytes

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Creator of Flask and Jinja. Writes about software at lucumr.pocoo.org.

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Computer science professor who works on fast data processing; co-author of the simdjson parser and a weekly blogger about software performance since 2004.

• Python sets and dictionaries can have quadratic-time performance

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Software engineer and engineering leader at Canonical, working on Ubuntu; writes about his homelab, Nix and tooling at jnsgr.uk.

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AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).

• A little video that - explains the relationship between conventional LLMs and reasoning models (and agents), - philosophizes a about "from scratch" approaches, - and explains how to install Python & PyTorch requirements with uv.

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Indonesian software engineer, educator and engineering manager at Zero One Group; open-source enthusiast writing at ripandis.com.

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Moroccan senior frontend developer writing at smakosh.com; builds side projects and client work under Smakosh LLC.

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Founded Bridgewater Associates in 1975 and led it until stepping back from control in 2022. Author of Principles, The Changing World Order and How Countries Go Broke; publishes economic analysis at economicprinciples.org.

• How Countries Go Broke: The Dynamic Behind What is Happening Now

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Programmer, photographer and musician, best known for the Python Requests HTTP library and other Python tooling.

• noodler — A modular music environment where theory itself is patchable. Eurorack-inspired, built in Python around PyTheory.

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Web infrastructure engineer and standards editor; chaired the IETF HTTP working group and co-authored core HTTP and Atom specifications.

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Italian software architect working on Microsoft 365, Azure and GitHub tooling. Microsoft MVP and GitHub Star; writes, speaks and streams about developer productivity at emanuelebartolesi.com.

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Thai software engineer; publishes a public digital garden at garden.narze.live and builds developer and productivity tooling.

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• Monty Python and the Holy Grail, in alphabetical order: the latest submission to Supercut.org, inspired by Of Oz The Wizard

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Cryptography engineer; maintains Go's cryptography libraries as a full-time open-source maintainer, funded directly by companies that use them.

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AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).

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Indonesian software engineer, educator and engineering manager at Zero One Group; open-source enthusiast writing at ripandis.com.

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Indonesian software engineer, educator and engineering manager at Zero One Group; open-source enthusiast writing at ripandis.com.

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Freelance web developer and instructor. Author of the Dive Into Docker course; writes tutorials on Docker, deployment and development environments at nickjanetakis.com.

• It's sad to see trillion dollar AI companies end the careers of course creators. David has been making Python courses for 20 years and he just called it quits. https://t.co/09rHvd17i6 I've been doing it for 10 years and I'm at an impasse. Traffic is dead, I operate at a loss.

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Programmer, photographer and musician, best known for the Python Requests HTTP library and other Python tooling.

• interpretations — A new album, written in Python.

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Software engineer in Chicago; writes the cassidoo.co blog and a weekly developer newsletter.

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Machine learning engineer and consultant focused on RAG and retrieval systems. He writes about applied AI engineering at jxnl.co and is the author of the instructor library.

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Writes jvns.ca, turning "hard and scary" topics — networking, debugging, Linux internals — into plain explanations and hand-drawn comics. Publishes Wizard Zines, illustrated programming zines. Software developer based in Montreal.

• the next version of Python is going to have a built in sampling profiler!!!! this is so exciting to see

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• exciting to read about this work on rv, uv has made Python so much easier for me
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Technical educator, conference speaker and developer relations engineer based in Ottawa, Canada. Author of the Anubis bot filter and of over 400 articles at xeiaso.net.

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Freelance web developer and instructor. Author of the Dive Into Docker course; writes tutorials on Docker, deployment and development environments at nickjanetakis.com.

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• People get confused when language implementations break language guarantees

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AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).

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Founding member of OpenAI and former director of AI at Tesla; creator of nanoGPT and the term "vibe coding".

• microgpt

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Technical educator, conference speaker and developer relations engineer based in Ottawa, Canada. Author of the Anubis bot filter and of over 400 articles at xeiaso.net.

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Theoretical physicist and philosopher, Homewood Professor of Natural Philosophy at Johns Hopkins and fractal faculty at the Santa Fe Institute. Writes the Preposterous Universe blog and hosts the Mindscape podcast.

• Thanksgiving

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Creator of the Keras deep-learning library and the ARC-AGI benchmark.

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Software engineer who writes the blog Made of Bugs about performance, debugging and understanding computer systems. Previously worked at Anthropic on interpretability, at Stripe on Sorbet, and at Ksplice.

• The ITTAGE indirect branch predictor

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Software engineer who writes the blog Made of Bugs about performance, debugging and understanding computer systems. Previously worked at Anthropic on interpretability, at Stripe on Sorbet, and at Ksplice.

• Performance of the Python 3.14 tail-call interpreter

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Machine learning engineer working on recommender systems, personalization and information retrieval. Previously worked on LLMs and LLM infrastructure at Mozilla.ai and on ML and recsys at Duo, Tumblr, Automattic and Comcast; wrote the 'What are embeddings?' text and ran the Normconf conference.

• How FastAPI path operations work

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Game developer, formerly at Looking Glass Studios, and author of the stb single-file public-domain C libraries used across the games industry.

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Machine learning engineer working on recommender systems, personalization and information retrieval. Previously worked on LLMs and LLM infrastructure at Mozilla.ai and on ML and recsys at Duo, Tumblr, Automattic and Comcast; wrote the 'What are embeddings?' text and ran the Normconf conference.

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Machine-learning researcher on open language models; writes the Interconnects newsletter and the RLHF Book, after leading post-training at Ai2.

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Writer and consultant on formal methods and software correctness; author of Practical TLA+ and Logic for Programmers.

• Toolbox languages

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Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.

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Machine-learning researcher at Cursor working on post-training for coding models; a professor at Harvard and then Cornell from 2016 to 2026, and a researcher at Hugging Face from 2019 to 2024.

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Member of technical staff at Anthropic. He has led ML/AI teams at Amazon, Alibaba and Lazada, and writes about LLMs, recommender systems and engineering at eugeneyan.com.

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Creator of the Keras deep-learning library and the ARC-AGI benchmark.

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Interpretability researcher at Anthropic, which he co-founded; before that at OpenAI and Google Brain, where he wrote the explanations of neural networks most people learned them from.

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Software engineer who writes the blog Made of Bugs about performance, debugging and understanding computer systems. Previously worked at Anthropic on interpretability, at Stripe on Sorbet, and at Ksplice.

• MastodonI got nerdsniped much harder than intended by Advent of Code and so here's a writeup of how to process a 20,000 element list in C++ template metaprogramming without blowing your compiler's stack, and also about manually compiling a regular expression into a compile-time state machine. Sorry but also not sorry:

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• BlogAdvent of Code in C++ Template Metaprogramming

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Brazilian-American staff software engineer working on platforms, AI and developer productivity. Writes about engineering and his setup at ivansantos.me.

• I am starting a new journey where I play with LLMs while refusing to touch Python. Wish me luck, let’s see how far I can get lol

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Author of Shape Up; formerly head of strategy at Basecamp, where he worked on product design for seventeen years; now runs Felt Presence.

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Author of Shape Up; formerly head of strategy at Basecamp, where he worked on product design for seventeen years; now runs Felt Presence.

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Novelist and writer, author of Mr. Penumbra's 24-Hour Bookstore and Sourdough; previously worked at Twitter and Current TV.

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Founder and chief executive of Replit. Previously an engineer at Facebook and Codecademy. Writes essays on programming, philosophy and entrepreneurship at amasad.me.

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Programmer; co-founded GitHub and was its CEO, and created the Mustache templating language and Resque.

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Founding member of OpenAI and former director of AI at Tesla; creator of nanoGPT and the term "vibe coding".

• A from-scratch tour of Bitcoin in Python

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Creator of the Keras deep-learning library and the ARC-AGI benchmark.

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Programmer and entrepreneur; co-founded GitHub and created Jekyll, Gravatar and the Semantic Versioning spec.

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Engineer and writer on machine-learning systems; author of Designing Machine Learning Systems and AI Engineering. "I work to bring AI into production. I write about AI system design."

• python-is-cool — Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

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Data scientist and machine-learning researcher; chief scientist at bitly, founder of Fast Forward Labs and Hidden Door.

• introbot — A python script to generate the text of intro e-mails.

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Data scientist and machine-learning researcher; chief scientist at bitly, founder of Fast Forward Labs and Hidden Door.

• randomness_beacon — A python module for using the NIST randomness beacon, generating 512-bits of randomness every 60 seconds

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Data scientist and machine-learning researcher; chief scientist at bitly, founder of Fast Forward Labs and Hidden Door.

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Writes The Pragmatic Engineer, the software-engineering newsletter, and wrote The Software Engineer's Guidebook. Formerly an engineering manager at Uber, and at Microsoft/Skype and Skyscanner before that.

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Machine-learning researcher; has written the Lil'Log survey posts on how a model technique works since 2017, and worked at OpenAI from 2018 to 2024, latterly leading its safety systems team.

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