OpenAI's Pando Git backend cuts push latency nearly 5x and serves almost a petabyte a day

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Qwen 3.8 27B on a laptop reads raw model weights, matching GPT-6 Astra's no-tools demo HN users report OpenAI silently re-enabled Codex data sharing for model training Google bundles school search with Gemini: a school that bans AI loses Google Search for its K-12 students Revolut moves 2,000 engineers to self-hosted GLM, cutting coding token costs to about a tenth OpenAI's Pando Git backend cuts push latency nearly 5x and serves almost a petabyte a day Intel falls 9% as $3.7T chip rout spreads; Nvidia down 16% since Oct. 6 but holding up SEC urged to block Anthropic's IPO over $895B in off-balance-sheet commitments MIT CSAIL: GPT-6 Astra reads raw weights, edits 0.016% of Qwen3.5-0.8B to lift MATH-500 from 7.9% to 48.1%LeCun co-authored paper proves Platonic Representation Theorem for JEPAs, says good views need 42x fewer samples than next-token prediction Postgres 19 slips to November as LLM-found bugs push back-patched commits up 74%Frank Calegari on Terry Tao's blog: OpenAI's 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releases LFM3: six 2B-class multimodal models on one tri-hybrid backbone, open weights on Hugging Face Anthropic reports Claude Code cut a CAR-T component 70% and generated 35,000 antibody designs in a month AxiomMath formalizes the Classification of Finite Simple Groups in Lean, 43.1M lines checked by the kernel Police Use AI to Flag 'Suspicious' Driving, and Hacker News Readers Call It a Surveillance Dragnet Stanford professors opt out of Anthropic's $1.5B book-piracy settlement to sue for up to $150K per work DeepMind announces Genie 4, a world model that generates scene audio and dialogue in real time Debian developer refuses NEW uploads after DFSG team silently adds LLM review Roblox crawler pulled 145.5 GB from 3D model sites, ignored robots.txt and non-commercial licenses Cloudflare's GLM-5.3 Workers AI endpoint leaked 155 cross-tenant responses through an SGLang KV cache bug OpenAI posts a preprint titled "The Exponential Time Hypothesis is False" with no abstract or 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research ideas that fit the literature but that no author community is positioned to pursue Fable 5.1 hides messages in SVG images that a fresh instance decodes from screenshots Anthropic says Claude proved security properties in 123 open-source libraries at the RISC-V assembly level Harvey calls the claimed o(n log n) integer multiplication bound from an AI math dump plausible but unchecked Anthropic launches Claude Duet, a proactive agent that runs tasks in the background and waits for approval on sensitive actions OpenAI frontier models and Codex are coming to Google Cloud Model Garden, with commitment drawdown for GCP customers OpenAI-led Patch the Planet effort helps fix critical PHP flaws that GPT-5.6 Sol helped uncover Mistral Large 4 ships as a 1.05T-parameter open-weight multimodal model at $1.36 per million input tokens LiteLLM 1.107.0 on PyPI Shipped a Credential Stealer and Backdoor Wiz says AI helped it chain decade-old flaws into unauthenticated RCE in core PHP OpenAI 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experts say Developer uses Claude Code to reverse engineer a scanner and a laptop MIPI camera driver from Windows USB traces Jev sacrifices one to save five, but twenty to save its own server Krea 3 image editing model enters open beta, claiming 4x speed over Nano Banana Pro Simons Foundation launches $15M AI effort for mathematicians, backed by Anthropic and OpenAI OpenAI's math proofs leave top mathematicians grieving, Steven Strogatz says Goodfire essay argues neural networks are already clean and mostly interpretable Meta releases Muse Spark Open weights, an 816B model that runs on two Mac Studios Liquid AI releases open-weight LFM2.5-24B-A2B, a 2B-active reasoning model for on-device agents Banks try to offload $38B of AI data center debt they just underwrote Frontier AI labs' agent hacks blamed on basic containment failures, not rogue AI ASML says customers are already ordering chip tools for 2029 and 2030, easing AI spending fears Google's Gemini 4 Argon scores 87% on ERQA and controls robots in simulation and on hardware

OpenAI's Pando Git backend cuts push latency nearly 5x and serves almost a petabyte a day

Pando, a new Git backend OpenAI built, now powers all development in its monorepo: it cut median push latency by nearly 5x and delivers nearly a petabyte of Git data per day.
Pando coordinates updates to each branch independently so pushes to unrelated branches run in parallel, and it reuses packfiles across fetches instead of generating one per client, letting the server send the same bytes to many clients with little computation; the tradeoff is that a reader looking at several branches can see them at different points in time.
Commits landed on master grew +1,378% in Q3 2026 relative to Q1 2024, with a Q4 2026 estimate of +2,442%; OpenAI attributes the pace to Codex letting engineers run far more work in parallel.
Reliability of the monorepo systems fell below 90% around the end of 2025, with slow fetches and pushes and failed merges, which pushed the rebuild; Pando kept Git protocol and client compatibility so engineers and agents changed nothing in their workflow.
OpenAI maintains its own copy of Git and plans to contribute client improvements upstream, and says it will keep investing in the Git ecosystem for agent-scale work.

Hacker News opinions

Technical details aside, this volume is ridiculous. How is exponential commit growth an asset and not a liability?

This is obviously just a response to Anthropic's redesigning source control post. I doubt anyone in the chain writing this even thought about that question.

That volume is a liability only for human engineers, with limited memory, short attention spans and quirky coding preferences. LLMs don't have any of those problems.

Not really, this is fairly mild for OpenAI's size. For my own work I've stopped counting commits and started looking at disk size changes.

I have no particular interest in the topic but this is a great blog post. No AI in every second line, no needless hype, just engineers talking in their own voice with numbers and charts.

Naive to think you can tell whether a human or their unreleased model wrote this.

What is this massive volume of code actually doing? They have model architectures, training, serving, and app source. Why would any of it grow exponentially while the products barely seem to change?

It's AI slop. Coding agents write much more voluminous code, more tests, and many more commits from fixing and fixing over and over.

RL environments. RL environments as far as the eye can see.

Engineers run multiple sessions now and the LLM does most of the commits and pushes. That's becoming the norm at big tech.

Supply was always the limiting factor, not demand. When an engineer shipped 100 lines of production code a week you only did the critical things, and cheaper code makes the marginal projects worth doing.