Simon Willison — Week of 2026-04-04 to 2026-04-10#

Highlight of the Week#

Anthropic’s decision to delay the general release of their highly capable Claude Mythos model under “Project Glasswing” marks a significant turning point in the AI industry. The move underscores a massive shift in frontier model capabilities, as models evolve from generating text to autonomously chaining multiple minor vulnerabilities into sophisticated exploits, requiring a new level of security safeguards before release.

Simon Willison — Week of 2026-04-11 to 2026-04-17#

Highlight of the Week#

This week’s most striking revelation came from Simon’s infamous “pelican riding a bicycle” SVG generation benchmark, where a 21GB quantized local model (Qwen3.6-35B-A3B) unexpectedly outperformed Anthropic’s brand-new Claude Opus 4.7 flagship. Running locally on a MacBook Pro via LM Studio, Qwen generated a better bicycle frame and even won a secret unicycle backup test, leading Simon to conclude that his joke benchmark’s long-standing correlation with general model utility has finally broken down.

Simon Willison — Week of 2026-04-18 to 2026-05-01#

Highlight of the Week#

The alpha release of llm 0.32a0 marks a foundational architectural pivot for Simon’s ecosystem of CLI tools. By moving away from a simple text-in/text-out abstraction to one that natively models complex message sequences and typed streams, the library is now future-proofed to handle the realities of modern frontier models. This opens the door for seamless integration of server-side tool calls, multi-modal inputs, and reasoning tokens.

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 2026-05-29 to 2026-06-05#

Highlight of the Week#

The single most impactful update this week is the release of Datasette 1.0a31, which marks a massive paradigm shift by introducing UI support for executing write queries directly against the database. By allowing developers with the right permissions to set up templated insert, update, and delete operations as “stored queries,” Simon is aggressively evolving Datasette from a purely read-only tool into one that embraces secure data mutation.

Simon Willison — Week of 2026-06-06 to 2026-06-12#

Highlight of the Week#

The standout event this week was the release of Anthropic’s massive Claude Fable 5 model, which Simon immediately leveraged as a highly capable coding partner to essentially author complex new features across his open-source ecosystem. However, the most impactful takeaway was his deep dive into the model’s terrifyingly autonomous capabilities—such as independently writing CORS servers and injecting JavaScript just to debug a CSS glitch—which served as a stark reminder of why executing AI-generated code requires strict sandboxing.

Simon Willison — Week of 2026-06-12 to 2026-06-18#

Highlight of the Week#

The most impactful release this week is the launch of datasette-apps, a major new plugin that allows developers to run self-contained, sandboxed HTML and JavaScript applications directly against a persistent Datasette backend. It brilliantly merges Simon’s ongoing experiments with AI-generated “vibe-coded” single-file tools and robust security architectures, pushing Datasette from a read-only publishing platform into a comprehensive ecosystem for building interfaces over data.

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 — 2026-07-11#

Highlight#

The release of sqlite-utils 4.1 showcases how Simon is aggressively integrating AI into his open-source workflow, using GPT-5.6 Codex not just to write code, but to triage issues and manually exercise edge cases in the terminal. It also introduces a clever workaround to migrate existing databases to SQLite’s STRICT mode by utilizing the tool’s built-in table transformation mechanism.

Posts#

sqlite-utils 4.1 · Source Just days after shipping version 4.0, Simon released sqlite-utils 4.1 with a batch of minor but highly useful CLI features. Highlights include a --code option to generate rows for insertion directly via Python snippets, and a --type override to prevent CSV/TSV data like ZIP codes from being incorrectly parsed as integers. Inspired by an Evan Hahn post on Hacker News, the release adds strict=True/False toggles to the transform command, seamlessly migrating data to enforce SQLite’s strict table schemas. Interestingly, Simon relied heavily on AI-assisted programming for this release: he had Codex scan his repository to find the easiest open issues, and used an advanced prompt instructing the model to use uv run python -c to manually test its own work and uncover edge cases.

Simon Willison — 2026-07-08#

Highlight#

Jarred Sumner’s post on rewriting Bun from Zig to Rust using AI agents is an incredible showcase of how frontier LLMs are upending the old Spolsky rule of “never rewrite from scratch”. It is a masterclass in agentic engineering, utilizing dynamic workflows and a TypeScript conformance suite to successfully port millions of lines of code.

Posts#

Rewriting Bun in Rust · Source Jarred Sumner details the agentic engineering process of rewriting Bun from Zig to Rust to solve complex memory management issues. Using a language-independent TypeScript test suite as a conformance suite, an agent harness powered by Claude Mythos/Fable automated the massive code translation. The sheer scale of the project required 5.9 billion input tokens—around $165,000 at API pricing—proving that coordinated parallel agents fundamentally change the calculus of ground-up software rewrites.