# best-practices

Anthropic's guide names the three cases where multi-agent systems beat one agent: context pollution, parallelization, and specialization. Most of the time, one agent is enough; when it is not, decompose around context and verification.

Simon Willison finally defines Agentic Engineering after 11 hands-on chapters: using coding agents to help build software. The interesting part is why he needed the patterns first before the simple definition felt earned.

Simon Willison's Agentic Engineering Patterns, Chapter 3: AI should help us ship better code, not worse. Technical debt cleanup costs near zero now, architecture decisions can be validated with prototypes instead of guesses, and quality compounds over time.

Simon Willison's First Run the Tests pattern is four words with three effects: the agent learns the test command, gauges codebase size, and shifts into a test-maintenance mindset. Tiny instruction, large behavioral nudge.

Simon Willison shared his agentic engineering playbook at the Pragmatic Summit — five tokens to start TDD, Showboat for manual verification, reverse-engineering six frameworks into a standard, and why bad code is a choice you make.

A guide to Codex best practices from prompting and planning to MCP, Skills, and Automations — building a more reliable agent workflow.

Simon Willison's new Agentic Engineering anti-pattern hits hard: do not submit AI-generated code you have not personally verified. That is not saving time; it is stealing reviewer time. The post pairs principles with a terraform destroy horror story.

Simon Willison introduces Agentic Manual Testing: let AI agents manually operate code and UI like humans do, catching bugs that automated tests miss. With Playwright, Rodney, and Showboat, the 'tests pass but it's broken' nightmare becomes a thing of the past.

Chapter 5 of Simon Willison's Agentic Engineering Patterns: Interactive Explanations. Core thesis: instead of staring at AI-generated code trying to understand it, ask your agent to build an interactive animation that shows you how the algorithm works. Pay down cognitive debt visually.

Chapter 4 of Simon Willison's Agentic Engineering Patterns: Hoard Things You Know How to Do. Core thesis: every problem you've solved should leave behind working code, because coding agents can recombine your old solutions into things you never imagined.

Chapter 3 of Simon Willison's Agentic Engineering Patterns: the Linear Walkthrough pattern. This technique transforms even vibe-coded toy projects into valuable learning resources. Core trick: make the agent use sed/grep/cat to fetch code snippets, preventing hallucination.

Anthropic analyzed 9,830 Claude.ai conversations and defined 11 observable AI fluency behaviors. Key finding: people who iterate show 2x the fluency. But when AI produces beautiful artifacts, users question its reasoning less. The prettier the output, the more dangerous it gets.

Simon Willison launched Agentic Engineering Patterns, a playbook for coding agents like Claude Code and Codex. Lesson one: writing code got cheap, but good code remains expensive. Lesson two: red/green TDD is the six-word spell.

OpenAI released three primitives for long-running agents: Skills (reusable SKILL.md instruction packs), Shell (hosted container runtime), and Compaction (automatic context compression). Includes 10 battle-tested tips and Glean's production data.

StrongDM's AI team built a 'Software Factory' where AI agents write & review code. They clone apps into a 'Digital Twin Universe' for testing, an approach Simon Willison calls radical. At $10k/engineer/day in token costs, is it worth it?