Simon Willison — Week of 2026-05-08 to 2026-05-15#

Highlight of the Week#

The standout development this week is Simon’s rapid adaptation to the latest frontier model capabilities, most notably releasing llm 0.32a2 to expose and visualize the new interleaved reasoning tokens of GPT-5 class models directly in the terminal. This perfectly pairs with his hands-on explorations of embedding LLM calls deeply into developer workflows, such as executing prompts via script shebangs and leveraging models to output rich HTML rather than just Markdown.

Simon Willison — Week of 2026-06-18 to 2026-06-25#

Highlight of the Week#

This week’s absolute standout is the launch of the datasette-apps plugin, which fundamentally transforms how we build micro-applications over local databases. By utilizing tightly constrained iframe sandboxes and Content-Security-Policy headers, developers and LLMs alike can safely run custom HTML/JS interfaces against a persistent Datasette backend. It brilliantly merges Simon’s ongoing experiments with AI-assisted “vibe coding” and robust security architectures into a core ecosystem feature, effectively bridging the gap between Claude Artifacts and secure data environments.

Simon Willison — 2026-05-10#

Highlight#

Simon highlights a stark example of AI hallucination making its way into mainstream journalism, serving as a critical warning for anyone relying on LLMs for factual summarization.

Posts#

Quoting New York Times Editors’ Note · Source Simon shares a sobering editors’ note from the New York Times illustrating the dangers of unchecked generative AI in the newsroom. A reporter mistakenly attributed an AI-generated summary of Canadian Conservative leader Pierre Poilievre’s views as a direct, verbatim quote. The hallucinated text falsely claimed he called politicians who changed allegiances “turncoats,” underscoring exactly why LLM outputs must be rigorously verified against primary sources rather than trusted blindly.

Simon Willison — 2026-06-25#

Highlight#

Today’s most substantive post tackles the critical issue of AI liability, highlighting Bruce Schneier’s perspective on a recent German court ruling against Google. It is a vital read for anyone tracking the intersection of generative AI, corporate accountability, and the legal frameworks shaping how these models are deployed in production.

Posts#

AI and Liability · Source Simon shares commentary from Bruce Schneier regarding a recent German ruling that holds Google legally responsible for errors and hallucinations produced by its AI overviews. Schneier argues forcefully that AI models act as agents for the organizations deploying them, meaning companies should face the exact same liability as if they had hired human writers. Allowing corporations to dodge accountability by blaming “faulty AI” would create disastrous incentives, ultimately encouraging businesses to replace human experts—like doctors or lawyers—with cheaper, unaccountable models.

Simon Willison — Week of 2026-06-25 to 2026-07-03#

Highlight of the Week#

The single most impactful release this week was Simon’s launch of llm-coding-agent 0.1a0, which successfully turns his popular llm library into a full-fledged coding agent capable of file manipulation and command execution. Bootstrapped entirely using Claude Fable 5 via test-driven development, this represents a massive leap forward for his CLI ecosystem and a brilliant showcase of using frontier models to build the very tools that will orchestrate them.