@simonw

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27 April 2026 12h50

The sandbox needs to be one an agent can't break out of – otherwise it's not a sandbox

Verify Critical Systems Yourself Don’t Trust Documentation

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27 April 2026 12h44

Right, and those misunderstandings cost him his database You can't ever trust documentation, you have to prove to yourself that things this critical work the way you think they work

Designing safe environments for AI agent failures

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27 April 2026 12h43

AI agents make mistakes all the time – you have to assume they will make mistakes, and then design their environment so that when they do they can't delete your production database

Classifying Dangerous Code Execution Patterns in Python

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27 April 2026 12h41

Can that classify dangerous versions of something like "uv run python -c 'import graphql; graphql.delete(…)" ?

Safe AI Code Generation Platforms: Opportunity and Challenge

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27 April 2026 6h38

I agree with the general idea that the opportunity (and the challenge) to make safe production vibe coding platforms is enormous

Agent Frameworks Need Built-in Sandboxing Best Practices

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27 April 2026 6h37

I agree, I think every agent framework should come with best-in-class sandboxing out of the box Currently, setting up a sandbox is mostly left as an exercise for the user, and doing that well is really difficult

Agent Security: Protecting Production Credentials and Backups

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27 April 2026 5h01

The conclusions here feel wrong to me. The two lessons I see are: 1. Don't run agents anywhere they might be able to access production environment credentials – it's on you to know which credentials those are 2. Keep tested backups that are independent from your production host

DeepSeek-V4-Flash 2bit quantized model released on Hugging Face

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26 April 2026 16h15

I am refreshing https://
huggingface.co/mlx-community/
DeepSeek-V4-Flash-2bit-DQ
… with excitement waiting for the files to land!

26 April 2026

Hugging Face Models Directory Should Support Quantization Filtering

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24 April 2026 21h35

Ideal fix would be for the HF models directory to grow a direct understanding of the structure of those kinds of repos and treat them as individual models that can be listed separately, including filter by quantization type