Is AI writing code that's already out of date?

Who checks the big AI labs? Until now, mostly the labs themselves. New York wants to change that. TechCrunch reports the state is preparing to enforce its sweeping AI safety law.

Major developers like OpenAI and Anthropic must register with the state. They must disclose their safety practices. And they must report critical incidents, or face fines. Our sources do not give the reporting deadlines or the size of the fines.

It comes right after the US midterms. The AI Safety Newsletter from CAIS says voters favored candidates who back AI regulation, while safety advocates still clash over strategy. Yesterday, we saw Australia move toward deadlines for reporting AI incidents. Two governments in one week, one idea: tell us when something goes wrong.

Grok Build is a coding agent: an AI that writes and ships apps for you. Ars Technica reports that a security researcher found 35,000 Grok Build apps wide open to anyone who looked for them.

According to Ars, the apps leak a lot of confidential information. Some of it belongs to SpaceXSI, a frontier AI lab. Our sources do not say how long the apps were exposed, or if anyone misused the data.

Same story as Tuesday, new tool. Then, it was Claude Code settings files exposing passwords and API keys. Last Saturday, it was hundreds of AI hacking tools left open on the internet. Different companies, same weak spot: agents build and publish fast, and nobody checks what they leave open.

Two weeks ago, Google gave Gemini 4 Carbon only to a select group of 'cybersecurity defenders'. Now everyone can use it. Google calls it its strongest model yet, able to compete with the best from Anthropic and OpenAI. It comes with an agent 'swarm' feature, meaning many agents working together.

Simon Willison notes the launch price: $2 per million input tokens and $10 per million output tokens. A token is a small piece of text. On December 1, the price doubles to $4 and $20. The launch got 287 points on Hacker News.

Google DeepMind also showed AlphaProof Code. Its agents wrote three million lines of proofs in Lean, a language that lets a computer check math, to verify Signal's core encryption. And on Hacker News (429 points), the security firm VulnCheck published a November update tracking vulnerabilities discovered by Anthropic.

Remember last week's token on GPT-6 Astra changing a tiny part of a small Qwen model's weights? Weights are the billions of numbers that make up a model. Small edits are now a whole field, and today it shows a darker side.

A post on r/LocalLLaMA says Microsoft Research backdoored an AI agent by directly editing fewer than 10 'dormant' neurons, parts of the model that are usually quiet. A backdoor is a hidden trigger that makes a model misbehave. The poster warns people who run 'sketchy' modified models, and asks if 'sleeper agents' could become a real attack. We only have the Reddit post, not the details of the research.

Other new work points the same way. A paper on Deletion Tuning finds that zeroing fewer than 0.05% of a model's weights can match full fine-tuning. And Tree-Ising, a new paper, builds on the Astra work to repair models with tiny bit-level edits.

Last Thursday, IEEE Spectrum said AI is forcing us to pay off 40 years of technical debt, the old messy code we never fixed. Now the top AI story on Hacker News asks if AI is creating new debt. A post by Evan X. Merz, titled 'AI usage generates a fragile codebase', got 605 points and 574 comments. That many comments shows developers have strong feelings.

A second story points to one possible cause. Google Chrome's team shared a free guide on GitHub to get coding agents 'off ~2019 JavaScript, onto modern web primitives'. In simple words: agents often write web code the old way, because that is what they learned from. It got 401 points.

So the debate is no longer only 'can AI write code?'. It is 'can we live with the code it writes, five years from now?'

Local AI means the model runs on your own computer, not in a company's cloud. Your questions and files stay at home. Today, setting it up is still a bit technical for most people.

According to 9to5Mac, Apple has a new Mac app coming to make running local AI models easy. The report got 358 points and 352 comments on Hacker News, and buzz on r/LocalLLaMA. Our sources give no name, no date and no list of models, so treat it as an early report.

It fits a clear trend. Local tools keep getting better, like the free project we saw Monday that claims to run a 284-billion-parameter model with no GPU.