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 2026-05-16 to 2026-05-22#

Highlight of the Week#

The most impactful milestone this week is the official announcement of Datasette Agent, merging Simon’s three years of work on his LLM library directly into Datasette. This conversational AI interface allows users to naturally interrogate their databases, boasting an extensible plugin architecture for charts, image generation, and secure code execution.

Key Posts#

[The last six months in LLMs in five minutes] · Source Simon shared annotated slides from his PyCon US 2026 lightning talk capturing a major inflection point in AI developer tooling. He highlights how coding agents crossed the threshold to become reliable daily drivers, and points to the astonishing capabilities of massive local models running on consumer hardware like Mac Minis.

Simon Willison — Week of 2026-05-22 to 2026-05-29#

Highlight of the Week#

This week’s most significant milestone is the release of Datasette 1.0a31, which fundamentally shifts the project’s paradigm by introducing UI support for executing write queries directly against the database. This officially bridges Datasette from a purely read-only tool to one that embraces secure data mutation, allowing developers to save and template insert, update, and delete operations.

Key Posts#

[I think Anthropic and OpenAI have found product-market fit] · Source Simon analyzes the shift in enterprise pricing to argue that AI coding agents have crossed the threshold into massive usage and real revenue generation. He points to Anthropic’s staggering $1.25 billion monthly compute spend and notes that labs are pivoting to capture enterprise value directly from heavy agent users rather than relying on middlemen.

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 — 2026-07-10#

Highlight#

Today’s standout piece highlights a sharp critique from Nilay Patel on the unavoidable privacy tradeoffs inherent to augmented reality hardware. It serves as a necessary reality check on the physical limitations of face-worn AI devices and the societal cost of continuous cloud-based processing.

Posts#

Quoting Nilay Patel · Source Simon highlights a stark reality check from Nilay Patel regarding the physical limits and privacy implications of augmented reality glasses. Patel argues that because chips small enough to fit in glasses cannot handle real-time continuous video processing, the data must be sent to the cloud. This unavoidable architecture means that building the next major AR product requires invading user privacy, raising the critical ethical question of whether the societal tradeoffs are too high to justify building these devices at all.

Simon Willison — 2026-04-14#

Highlight#

Simon highlights a fascinating paradigm shift in AI security: treating vulnerability discovery as an economic “proof of work” equation where spending more tokens yields better hardening. This creates a compelling new argument for the enduring value of open-source libraries in the age of vibe-coding, as the massive cost of AI security reviews can be shared across all of a project’s users.

Posts#

[datasette PR #2689: Replace token-based CSRF with Sec-Fetch-Site header protection] · Source Simon has replaced Datasette’s cumbersome token-based CSRF protection with a new middleware relying on the Sec-Fetch-Site header, inspired by Filippo Valsorda’s research and recent changes in Go 1.25. This modern approach eliminates the need to scatter hidden CSRF token inputs throughout templates or selectively disable protection for external APIs. Interestingly, while Claude Code handled the bulk of the commits under Simon’s guidance with cross-review by GPT-5.4, Simon chose to hand-write the PR description himself as an exercise in conciseness and keeping himself honest.