Kaspar Poland

@mitchellh @ludwigABAP I mean, most of the trust I have in my program comes from tests I wrote in that same language. Bun doesn’t have that constraint! Language runtimes, compilers, anything with many meaningful small EXTERNALLY DEFINED tests (sqlite!) is ripe for this sort of migration.

It isn't unexpected that the focus of the Bun Rust rewrite is on the anti-Zig side more than anything, since the internet loves to hate. What is unexpected and unfortunate is that leadership within Bun hasn't tried to steer the conversation away from that at all. There are so many positive and interesting takeaways from this and I'm not really seeing any of them pushed as the primary message. A positive thing that hasn't been talked about at all is how far Bun came thanks to Zig. And even if you dump it now, its meaningful for how good Zig was to even build a product to this point and impact by any metric. I would've loved to see anyone in leadership say this. On the interesting side is how fungible programming languages are nowadays. Programming languages used to be LOCK IN, and they're increasingly not so. You think the Bun rewrite in Rust is good for Rust? Bun has shown they can be in probably any language they want in roughly a week or two. Rust is expendable. Its useful until its not then it can be thrown out. That's interesting! There's been a lot of talk about memory safety and no doubt Rust provides more guarantees than Zig. But I'd love to see a better analysis of why Bun in particular suffered so much rather than take the language-blame path. How could engineering as a practice been more rigorous to prevent this? What were the largest sources of crashes other programs should watch out for? How does Rust prevent them? How could Zig theoretically prevent them? That's interesting. I know the official blog post hasn't come out yet from Bun. But they're smart enough to know that that PR would stir up controversy the moment it opened, or they should've been. And plenty in the company have been tweeting and writing about it. Its somewhat telling to me in various dimensions what they chose to talk about first. I tend to think I'm pretty good at corporate PR/comms (especially when it comes to developer audiences) and I think appealing to the negative is never the right long term strategy; it does work to get short term eyes though.

@muratdemirbas naadb?

Today, the Zoom AI dropped this pearl: Desegregated Storage!

ant website who is turning 4 years old on may 6, 2026

@peer_rich codecommit already existed! and then they deprecated it 😬 great job guys!

honestly AWS should launch an API only “github protocol” (git + social) and then let everyone else build the best frontend (better-hub, graphite, linear) AWS uptime is unbeatable

mm.. fry chicken

@elithrar why can't my agent query Cloudflare's domain registration recurring prices for the domains i own?

@BenjDicken agree about ddia’s second half. thought the same thing about “software engineering at google”’s second half, also highly recommend it though

Database Internals: Complete. I've now read both this and DDIA over the past 9 months. In some ways I liked DI more than DDIA. DDIA is great, but felt it was too verbose in the second half. DI is shorter and tighter. Every single engineer can benefit from reading Database Internals. (Yes, even all of you React Miami-ers!) This won't teach you everything, but it's a great place to start.

@malliktwts @kevindave__ u havent even read the whole thing dawg

@kevindave__ Def recommended for beginners

You know whats cooler than distributed systems? Distributed llm-serving systems…

@signulll bro never heard of da api

the craziest part now is that the modern computer probably has to be entirely reinvented, from scratch. pretty much like how jobs & co brought apple ii to market. like not improved. not given a chatbot sidebar or something but really from the ground up like the iphone redefined what it meant to be a pocket computer. the current paradigm for computers was built around a human staring at a screen, moving a cursor, opening apps, managing windows, naming files, remembering where things live, & manually translating intent into interface actions. that made sense when the human was the runtime. but in an ai native world, it starts to look kinda ridiculous. you can see this ridiculousness when you use computer use agents… they are useful sure, but they’re also obviously transitional. they’re teaching ai to operate machines designed for humans, which is clever, but also kind of absurd. it’s like making a robot hand so it can use a doorknob instead of asking why the door needs a knob at all. yes i know humans also need to use a door knob, but maybe in the future humans don’t need to use a computer, or at least what we think of a computer today at all. this all leads to some interesting questions: - what is a file when the system understands context? - what is an app when intent can route itself? - what is a desktop when work can be decomposed, executed, monitored, & summarized by agents? - what is a browser when the agent can retrieve, compare, transact, & remember? - what is an operating system when the primary user is no longer just a person, but a person plus a swarm of delegated intelligences? or no person at all. the old computer assumed navigation. the new computer has to assume a new kind of intention. the old computer organized information. the new computer has to try to organize agency. we’re still in the hacky middle stage at the moment with sidebars, copilots, agents clicking through legacy ui, & automation layers sitting on top of 40 year old metaphors. the new computer is likely one where memory, context, identity, permissions, tools, agents, & interfaces are native primitives. this means desktop, mobile, browser, apps, files, folders deserves another first principles look.

@DominikTornow i think the bigger problem is the state/context of where you’re jumping to. DBOS/temporal solve this by just rerunning and skipping already-seen steps with already-seen args. Long jump wouldn’t help here?

Not enough programming languages implement a long jump. Long jump makes implementing durable execution trivial.

@veorq @bwesterb no button for hybrid because it’s silly NOT to wrap PQC in regular C?

🟥 red button: elliptic-curve crypto until 2050, secure implementation, side channel-safe, meaningfully formally verified etc. 🟦 blue button: PQC (your favorite) but newly vibe-coded, at least matches the test vectors no button for hybrid 😈

@aakashgupta slopposting :( just write it yourself

Earlier this year Yann LeCun left Meta because Mark Zuckerberg wouldn't bet the company on JEPA. Last week his group dropped the first JEPA that actually trains end-to-end from raw pixels. 15 million parameters. Single GPU. A few hours. The timing is not a coincidence. For four years Meta has been the house that JEPA built. LeCun published the original paper from FAIR in 2022. I-JEPA and V-JEPA came out of his lab. The architecture was supposed to be the escape hatch from LLMs, the path to robots that actually learn physics instead of hallucinating about it. Every version shipped fragile. Stop-gradients. Exponential moving averages. Frozen pretrained encoders. Six or seven loss terms that had to be hand-tuned or the model collapsed into garbage representations. Meta kept funding LLMs. Llama shipped. Llama scaled. Llama got beat by Qwen and DeepSeek. Zuck spent $14 billion to buy ScaleAI and install Alexandr Wang. The FAIR robotics group was dissolved. LeCun's research kept winning papers and losing the product roadmap. He left, started AMI Labs, and said publicly that LLMs were a dead end. Now the paper. LeWorldModel. One regularizer replaces the entire pile of heuristics. Project the latent embeddings onto random directions, run a normality test, penalize deviation from Gaussian. The model cannot collapse because collapsed embeddings fail the test by construction. Hyperparameter search went from O(n^6) polynomial to O(log n) logarithmic. Six tunable knobs became one. The downstream numbers are what should scare the robotics capex class. 200 times fewer tokens per observation than DINO-WM. Planning time drops from 47 seconds to 0.98 seconds per cycle. 48x faster at matching or beating foundation-model performance on Push-T and 3D cube control. The latent space probes cleanly for agent position, block velocity, end-effector pose. It correctly flags physically impossible events as surprising. It learned physics without being told physics existed. Figure AI is valued at $39 billion. Tesla Optimus is mass-producing. World Labs raised $230 million to sell generative world models. Everyone in humanoid robotics is burning capital on foundation-model pipelines that plan in 47 seconds per cycle. LeCun's group just showed you can do it with 15 million parameters on a single GPU in a few hours. This is the Xerox PARC pattern running again. Meta had the next architecture. Meta had the scientist. Meta dissolved the robotics team, passed on the productization, and watched the exit. Three months later the lab that was supposed to be Meta's publishes the result that resets the robotics cost structure. The paper is worth more than Alexandr Wang.

@typesofants prescription of course

drug user ant

@madjid_tehrani @hashbreaker then they can choose not to deploy it?

@hashbreaker They don’t just need security, they need cost-performance at mission speed. In zero-trust, near real-time sensor-to-shooter pipelines, hybrid only works if it meets strict latency and throughput constraints.

Why add a PQ layer? To try to reduce the damage caused by quantum computers. Why also keep the existing (low-cost) ECC layer? To try to reduce the damage from further PQ security failures. For some reason this suddenly seems difficult for U.S. military contractors to understand.

@tqbf good commands but it’s so irritating to read this AI slop writing style

Kicking myself for not already having these in my zshrc. piechowski.io/post/git-comma…

@mitchellh If you worked for AWS 15 years ago you would have written this and titled it “the Platform Economy”

kid who just graduated first grade: yeah it was kinda like kindergarten

@chooweepy this about @lo0nerism

@BijanAnjavi @BenjDicken did u read the tweet

Hard to take all these “automate everything and log off” people seriously. I *enjoy* creating things on and with my computer. If you don't, why become a software engineer in the first place?

@typesofants EWWWW

constipated ant