Agents

On Tuesday I did a talk to our internal AI group, along with talks by excellent colleagues, on Context Engineering. The very next day, Anthropic released a blog post on Effective harnesses for long-running agents and updated their prompting best practices guide. Note to Anthropic: please can you release relevant material the day before I do a talk rather than afterwards! I talked about managing context size, how LLM accuracy declines as the context window fills past 50% and my mental model of LLMs as amnesiac pedants, and how this drives Claude Code features like it’s heavy use of todo lists, summarising context into markdown files etc. ...

The Anthropic Cookbook is an excellent resource for learning how to write LLM code and it’s continually being updated, most recently with example code for agents. The Cookbook comes as a set of Jupyter notebooks. I prefer Marimo to Jupyter, mainly because it supports reactive cell reloading i.e. if you change an earlier notebook cell that a later cell depends on, the chain of dependencies is calculated and everything is re-run correctly which saves a lot of mental energy and stupid mistakes when working with notebooks. ...