AI Agents

Microsoft announced two new models: MAI-Thinking-1 for reasoning and MAI-Code-1-Flash for coding. The latter is already rolling out to some GitHub Copilot users in VS Code. It's a massive 137B parameter model, but with only 5B active parameters—a design aimed at delivering high performance at lower cost and latency. The companion MAI-Thinking-1 is even larger (1T params, 35B active). Notably, Microsoft claims they were trained on commercially licensed data without distillation from third-party models.

Simon Willison released an alpha of datasette-agent-micropython, a new plugin for his Datasette Agent framework. The goal is to enable safe execution of agent-generated Python code by running it inside a sandbox built with MicroPython and WebAssembly. While still early, this approach is showing promise for containing potentially malicious or buggy code generated by LLMs; initial tests with GPT-5.5 have reportedly failed to produce a sandbox escape, demonstrating a practical path forward for a common agent safety problem.

Underpinning the datasette-agent-micropython plugin is this new low-level library, micropython-wasm. It's an alpha package that bundles a WebAssembly build of the MicroPython interpreter with Python bindings for the wasmtime runtime. This provides a core component for creating sandboxed environments where untrusted Python code can be executed with defined resource limits and without access to the host system. It's a foundational piece for building safer code-executing agents on any platform, not just Datasette.

In a discussion with Latent Space, GitHub's Kyle Daigle outlined the company's strategic thinking for the future of AI agents on the platform. The conversation covers how the explosive growth of agentic coding, spurred by GitHub's own Copilot, is creating new strains and opportunities. It provides a high-level view of how the world's largest developer platform plans to evolve to support and manage the next wave of autonomous and semi-autonomous software development tools that increasingly interact with its core infrastructure.

This post provides a general news recap of Microsoft's recent Build conference, focusing on the announcement of the new MAI family of models. It touches on the same MAI-Thinking-1 and code-focused models covered in more detail elsewhere today. For readers seeking the original Microsoft announcements and a high-level overview without a deep technical dive, this serves as a straightforward summary of the release news and its context from the conference. It offers little new information for those following closely.