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Vibe coding SwiftUI apps is a lot of fun
IA Programmation

Vibe coding SwiftUI apps is a lot of fun

I have a new laptop - a 128GB M5 MacBook Pro, which early impressions show to be very capable for running good local LLMs. I got frustrated with Activity Monitor and decided to vibe code up some alternative tools for monitoring performance and I'm very happy with the results. This is my second experiment with vibe coding macOS apps - the first was this presentation app a few weeks ago. It turns out Claude Opus 4.6 and GPT-5.4 are both very competent at SwiftUI - and a full SwiftUI app can fit…

Simon Willison's Weblog
We Rewrote JSONata with AI in a Day, Saved $500K/Year
IA Programmation

We Rewrote JSONata with AI in a Day, Saved $500K/Year

We Rewrote JSONata with AI in a Day, Saved $500K/Year Bit of a hyperbolic framing but this looks like another case study of vibe porting, this time spinning up a new custom Go implementation of the JSONata JSON expression language - similar in focus to jq, and heavily associated with the Node-RED platform. As with other vibe-porting projects the key enabling factor was JSONata's existing test suite, which helped build the first working Go version in 7 hours and $400 of token spend. The Reco…

Simon Willison's Weblog
My minute-by-minute response to the LiteLLM malware attack
IA Programmation

My minute-by-minute response to the LiteLLM malware attack

My minute-by-minute response to the LiteLLM malware attack Callum McMahon reported the LiteLLM malware attack to PyPI. Here he shares the Claude transcripts he used to help him confirm the vulnerability and decide what to do about it. Claude even suggested the PyPI security contact address after confirming the malicious code in a Docker container: Confirmed. Fresh download from PyPI right now in an isolated Docker container: Inspecting: litellm-1.82.8-py3-none-any.whl FOUND: litellm_init.pth…

Simon Willison's Weblog
Quantization from the ground up
IA Programmation

Quantization from the ground up

Quantization from the ground up Sam Rose continues his streak of publishing spectacularly informative interactive essays, this time explaining how quantization of Large Language Models works (which he says might be "the best post I've ever made".) Also included is the best visual explanation I've ever seen of how floating point numbers are represented using binary digits. I hadn't heard about outlier values in quantization - rare float values that exist outside of the normal tiny-value…

Simon Willison's Weblog
Thoughts on slowing the fuck down
IA Programmation

Thoughts on slowing the fuck down

Thoughts on slowing the fuck down Mario Zechner created the Pi agent framework used by OpenClaw, giving considerable credibility to his opinions on current trends in agentic engineering. He's not impressed: We have basically given up all discipline and agency for a sort of addiction, where your highest goal is to produce the largest amount of code in the shortest amount of time. Consequences be damned. Agents and humans both make mistakes, but agent mistakes accumulate much faster: A human is a…

Simon Willison's Weblog
datasette-llm 0.1a1
IA Programmation

datasette-llm 0.1a1

Release: datasette-llm 0.1a1 New release of the base plugin that makes models from LLM available for use by other Datasette plugins such as datasette-enrichments-llm. New register_llm_purposes() plugin hook and get_purposes() function for retrieving registered purpose strings. #1 One of the responsibilities of this plugin is to configure which models are used for which purposes, so you can say in one place "data enrichment uses GPT-5.4-nano but SQL query assistance happens using Sonnet 4.6",…

Simon Willison's Weblog
LiteLLM Hack: Were You One of the 47,000?
IA Programmation

LiteLLM Hack: Were You One of the 47,000?

LiteLLM Hack: Were You One of the 47,000? Daniel Hnyk used the BigQuery PyPI dataset to determine how many downloads there were of the exploited LiteLLM packages during the 46 minute period they were live on PyPI. The answer was 46,996 across the two compromised release versions (1.82.7 and 1.82.8). They also identified 2,337 packages that depended on LiteLLM - 88% of which did not pin versions in a way that would have avoided the exploited version. Via @hnykda Tags: packaging, pypi, python,…

Simon Willison's Weblog