John Carmack engagement report

Best tweets

• Jun 8, 202627x their median

  A French engineer who lives quietly in Paris has spent 30 years writing software that the entire internet now runs on without knowing his name. He wrote the code that streams every YouTube video, every Netflix show, every TikTok clip. He wrote the code that runs the virtual servers underneath AWS, Google Cloud, and Microsoft Azure. He calculated more digits of pi than anyone in history. He has no Twitter. He has no marketing. He just keeps shipping. His name is Fabrice Bellard. Here is the story, because almost nobody outside the systems programming world knows what one man has built. Fabrice was born in 1972 in Grenoble, France. He studied at École Polytechnique, the top French engineering school. He never went to Silicon Valley. He never built a startup empire. He just wrote code. In 2000 he started a project called FFmpeg, an open-source multimedia framework for encoding, decoding, and streaming video. He was 28. The project did one thing nobody else had done well. It handled every video and audio format that existed, in one library, on every operating system. He led it himself for years. Today FFmpeg is the invisible engine of the internet. YouTube uses it. Netflix uses it. VLC uses it. Chrome and Firefox use parts of it. Every Android phone, every iPhone, every smart TV, every video editing tool you have ever touched runs FFmpeg somewhere underneath. If you have watched a video on a screen in the last 20 years, Fabrice's code processed it. He was not done. In 2003 he started QEMU, a machine emulator and virtualizer. He wrote it solo until version 0.7.1 in 2005. QEMU lets you run any operating system on any other operating system. It became the foundation of modern virtualization. KVM, the Linux kernel hypervisor, runs on top of QEMU. Every major cloud provider, AWS, Google Cloud, Microsoft Azure, IBM Cloud, runs virtual machines on infrastructure built around it. The Quick Emulator is the most cited piece of cloud infrastructure code on Earth. He kept going. In 2001 he won the International Obfuscated C Code Contest with a small C compiler that grew into TCC, the Tiny C Compiler. TCC can compile and boot a Linux kernel from source in under 15 seconds. In 2004 he calculated the most digits of pi ever computed at the time, using a personal desktop computer and an algorithm he derived himself called Bellard's formula. In 2011 he wrote a complete PC emulator in pure JavaScript that runs Linux in your browser, a project called JSLinux that engineers still cannot believe is real. In 2019 he released QuickJS, a small but complete JavaScript engine that fits where V8 cannot. In 2021 he released NNCP, a neural network based lossless data compressor that immediately took the lead on the Large Text Compression Benchmark. Then he turned his attention to large language models. He built TextSynth Server, a web server with a REST API for running LLMs locally. He released ts_zip and ts_sms, compression utilities that use language models to compress text and short messages at ratios traditional algorithms cannot reach. He released TSAC, a very low bitrate audio compression system. In December 2025 he released Micro QuickJS, a new JavaScript engine for microcontrollers, separate from QuickJS, designed for environments with almost no memory. Fabrice co-founded a telecom company called Amarisoft in 2012, where he serves as CTO. Amarisoft builds 4G and 5G base station software used by carriers and labs around the world. He has been running it for over a decade while continuing to ship personal projects from his own home page at bellard dot org He has no Twitter. He has no Instagram. He gives almost no interviews. His personal website is a flat list of projects with no styling, no fonts, no marketing copy. Just titles and links. A quiet French engineer who never moved to Silicon Valley wrote the code that quietly runs the internet. He is still shipping.

  25K4.5K3834043.2M viewsView on X
• Jul 9, 202612x their median

  I have been trying to find something meaningful to say about the Id Software layoffs. My “Microsoft will probably be a good steward of the brand” statement isn’t aging well, and this is certainly going to dampen the mood of the founder reunion at QuakeCon next month. I’m saddened, but I can’t muster anger or outrage over it. I don’t have access to the books, but I suspect that Id Software was a marginal business from Microsoft’s perspective. I believe the reports that Minecraft revenues have been carrying several other studios. To continue being produced long term, games need to succeed, not just be beloved. Games are competing with every other option for spending your leisure time and money, and the competition is brutal. You can’t rule out the possibility that executives are idiots, but that shouldn’t be your default belief. I don’t think there is any obvious path that would have doubled the revenue from Id games. Could they have gotten more with a different pricing strategy? Could they have created more things for fans to buy? Could they have cost effectively marketed in a way that reached more players that would have loved and bought the games? Could they have changed the game designs and broadened the appeal to more players without alienating existing ones? Could they have produced the games at a lower cost, faster or cheaper? I really don’t know. The game isn’t over yet, and I hope the studio rallies through.

  12K1.2K5441271.1M viewsView on X
• Aug 6, 20269.0x their median

  Bonus! I will be joining Romero and Tom for the 9am session tomorrow at #quakecon https://t.co/dDzwS2NTrm

  9.3K604245101374K viewsView on X
• Jul 6, 20267.2x their median

  Memory cost and capacity are significant issues for AI accelerators. Unlike game rendering, model inference can have a deterministic memory access pattern. You don’t need “random access memory” at all for model weights, and you could tolerate cold-start latencies in the multiple milliseconds, as long as continuous reads were delivered at the necessary bandwidth. NAND flash is over 100 times cheaper per GB than HBM, so there should be opportunity there, even after giving a flash controller a 1024 bit interface with HBM bandwidth. You could make a specialized pin protocol that just supported pipelined transfer of full 16KB+ pages from the flash to program-managed accelerator scratchpad memory and improve per-pin performance over HBM, but it might be more convenient to make it still look like a true random access memory with very fragile performance characteristics, where anything but sequential reads falls off a 1000x+ performance cliff. That has the advantage of automatically using existing cache hierarchies, and providing a natural path to update the flash memory with new model weights. With the stream-to-scratch interface, code has to be completely rewritten before it works at all, while the ram-emulation interface will start off just extremely slow, and you can incrementally sort out the changes for full performance. There may be cases where there isn’t enough scratchpad SRAM to hold the weights for a layer, which might force you to deploy the old optical drive optimization technique of duplicating data in multiple places on a sequential read to avoid seeking, but there would be capacity to burn. It might be possible to do something like cuda graph capture to record a memory access trace and have everything magically remapped to a linear sequence, but deploying programmer / agent elbow grease to manage transfers and access in a scratch ram ring buffer would be lower risk. A split memory system consisting of some channels of flash and some channels of HBM will probably be suboptimal compared to a uniform memory, but it could be much cheaper, and allow much larger models to be run. I think th case is strong for inference, but you have to stretch more for training. You can still linearize all the weight memory accesses, both reads and writes, but flash memory would quickly wear out from the writes, even if they were all perfectly page aligned. Replacing low-latency HBM with massively parallel cheap(er) DRAM at high latency might still be a worthwhile cost savings.

  7.3K4912981501.7M viewsView on X
• May 12, 20266.4x their median

  My reply to someone considering starting a video game company: The distribution of possible rewards for starting a video game company are generally not very good today. The market is well served, and gaining a foothold requires strong execution on both business and product issues, along with a substantial amount of luck. Plan to burn through seven figures with a not-great chance of making it back. If you do go for it, some bits of advice: Identify your customers clearly before you start. Not just a broad community, but specific people, and imagine them as you make decisions. Initially, build the smallest, most concise game you can imagine anyone paying for. It will still take much longer than you expect. Once something exists, hill-climb the value. Hopefully you will have some elements that clearly bring joy to people, which you can magnify. There will inevitably be tons of things that people find confusing, frustrating, or just boring that you will need to fix.

  6.5K51926387371K viewsView on X
• Jun 24, 20265.5x their median

  How Quake ruined id Software. There has been a lot of praise of Quake of late, with its 30th anniversary, and it's deserved. Quake is an amazing feat of art, programming, and design. I worked on it, and everything came together almost perfectly from all of us. We ended up with a free-wheeling, frenetic action game with enough of a visible world to grip the imagination. All the team did a brilliant job, fulfilling tasks just right. But at a grim cost. We worked long and hard, and I think it broke us spiritually. 1/3

  5.6K362286651.2M viewsView on X
• May 18, 20264.9x their median

  I loved the Project Hail Mary movie (and the book). Science, technology, competence, and openness – this is my culture.

  5.2K23213632185K viewsView on X
• Jul 24, 20264.4x their median

  Sometimes I look out over a body of water and think about pixel shaders — superimposed waveforms, fresnel effects, intra-pixel maximum finding and analytical anti-aliasing. In the age of gen-AI rendering, this is like the old mechanics working on WW2 era piston planes. A craft of a prior era.

  4.6K21921450258K viewsView on X
• May 12, 20263.9x their median

  I've been coding for 40 years. Here are the top 5 things I wish I knew when I started. 1. 90% of the job is debugging and fixing, not creating new code. Which is still fun if you're good at it. I used to think programming was mostly writing fresh, clever stuff. In reality, most of your time is spent in other people's (or your own past self's) messy code, chasing down why something that "should" work doesn't. Get really good at debugging early. Learn assembly reading, call stacks, and kernel debuggers. It pays off hugely. The best engineers I saw were absolute magicians at this. 2. Manage complexity from day one (ie: don't write slop and "fix it later" if it goes somewhere). Very early on, I'd hammer out code and refactor afterward. Big mistake. Now I start with clean, skeletal structure (minimalism first) and flesh it out carefully, with AI or not. Messy code compounds and becomes unfixable. Upfront discipline on architecture, naming, and simplicity saves enormous pain later, especially in large systems like Windows. 3. Tools and processes matter more than you think We suffered with basic diff/manual deltas instead of modern source control like Git. Branching, testing, and good tooling would have made porting and collaboration way smoother. Invest in your environment, automation, and reproducible builds early. Good tools amplify your output; bad ones (or none) drag everything down. 4. Understand the problem and existing code deeply before writing Don't jump straight to coding. Map out the problem, study what's already there (you'll inherit a lot), and plan. Low-level knowledge (hardware quirks, alignment issues on different architectures like MIPS/Alpha) was crucial. Also: assert early and often. It forces clarity. 5. People, politics, and "the right tool for the job" beat pure tech arguments. Brilliant engineers still argue endlessly. Sometimes it's about ego, not merit. Learn to spot the difference and "steer" the conversation rather than "winning" it. Bonus from experience: Side projects like Task Manager (started at home because I wanted the tool) can become your biggest hits. Ship small, useful things often. If you're just starting, focus on fundamentals, patterns over syntax, and building resilience for the long haul. It's going to be a wild ride, but the fundamentals still matter.

  4.1K52918549201K viewsView on X
• Jun 22, 20264.1x their median

  Anti-data center yard signs are popping up in my area. I am entertaining the idea of paying for a billboard with something like “Data centers are awesome, Texas should lead!”

  4.1K15939650286K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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