Simon Willison releases llm-coding-agent 0.1a0, a simple coding agent built on his LLM library. Developed with Claude Code, it includes tools for file editing, command execution, and a Python API.

Simon Willison leverages the DSPy framework to evaluate and refine the core production system prompts for Datasette Agent's read-only SQL question answerer. Using DSPy agents that invoke actual tool implementations against a live in-process Datasette, and a gold-standard auto-generated dataset, the project identifies promising improvements, such as including column names in the schema listing or softening advice that causes column-name guessing.

Amazon Bedrock detects AI-generated phishing by analyzing behavioral patterns rather than grammar. Its multi-stage pipeline includes authentication checks, AI model analysis with guardrails, multi-factor risk scoring, and automated routing.

In this post, we share best practices for reliable multi-turn RL training. We cover how to build a training environment you can trust, set up an external evaluation, design a reward aligned with the end task, manage what changes once the agent runs for multiple turns, and monitor the metrics that tell you when to iterate.

Learn why coding agent bills spiral out of control — and how to trace, compare, and govern spend across Claude Code, Cursor, Copilot, and more in one place.