Simon Willison — 2026-06-02#

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The most substantive post today is Simon’s commentary on Microsoft’s newly announced MAI models, which stand out not just for their small parameter counts (5B and 35B) but for the surprising claim that they were trained entirely on “clean and commercially licensed data”. This could signal a major shift away from models relying on unlicensed web scrapes.

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Microsoft’s new MAI models · Source Simon dissects the surprise drop of two new text LLMs at Microsoft Build: MAI-Thinking-1 (a 35B reasoning model) and MAI-Code-1-Flash (a 5B model for Copilot/VS Code). He’s particularly impressed that a 35B model reportedly beats Sonnet 4.6 in human evaluations, given he regularly runs larger models locally. The biggest takeaway, however, is Microsoft’s emphasis on using “appropriately licensed” data—raising the exciting prospect of highly capable code models built without controversial web scraping.

Engineering Reads — 2026-06-10#

The Big Idea#

Refining the developer workflow requires robust, specialized tooling, particularly for rendering and previewing documentation formats like Markdown.

Deep Reads#

Marked 3 giveaway! · Brett Terpstra Brett Terpstra announces a giveaway for three lifetime licenses of Marked 3, marking the tool’s most substantial update in over a decade. The release targets friction in text processing pipelines by introducing expanded format support, specifically DOCX handling, alongside new features like speed reading. While the post functions as a community reward rather than a technical deep dive, it underscores the value of local, specialized tooling for optimizing the documentation preview loop. Notably, the giveaway relies on a basic automated filter, skipping entries that do not explicitly provide both a first and last name. This brief update is relevant for macOS-based engineers and technical writers looking to reduce latency in their Markdown authoring and review workflows.

Simon Willison — 2026-06-12#

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Simon updated his OpenAI WebRTC audio playground to support the newly released GPT-Realtime-2 model and added support for custom document context. This highlights a great use case for building small, sharp tools: bypassing official app delays to immediately experiment with bleeding-edge AI capabilities on your own terms.

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OpenAI WebRTC Audio Session, now with document context · Source Simon revisited and upgraded a browser-based tool he originally built in December 2024 for interacting with OpenAI’s realtime audio API. Users can now select GPT-Realtime-2—a model promoted as having “GPT-5-class reasoning”—because it still hasn’t rolled out to the official ChatGPT iPhone app. Most practically, he added a feature to paste large chunks of document context directly into the tool, enabling interactive audio conversations grounded in specific reference material.

Simon Willison — 2026-06-29#

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Today’s standout piece is a hands-on exploration of Ornith-1.0, a newly released family of open-weights models specifically optimized for agentic coding. Simon tests its local execution capabilities and tool-calling proficiency, signaling another practical step forward for open-source AI developer tooling.

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Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding Simon goes hands-on with Ornith-1.0, a new MIT-licensed model family from DeepReinforce built on top of Gemma 4 and Qwen 3.5. Testing the 35B MoE variant locally via LM Studio, he finds it highly proficient at executing agent harnesses and running tool calls against a Datasette checkout. He highlights that the underlying models use clean Apache 2.0 licenses, successfully avoiding the “janky” terms of use that affected earlier Gemma 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.