A guided reading pathfrom search fundamentals to agent tooling.
This is the recommended order for the current Software Cookbook topics. It starts with durable discovery fundamentals, then moves into AI answer surfaces, and finishes with the protocol layer behind real model-powered tools.
Build durable discovery fundamentals
Start with the search and information-architecture layer because every other surface inherits its strengths and weaknesses.
Adapt the stack for AI answer surfaces
Once the foundation is sound, learn how generative discovery systems quote, condense, and rank source material.
Generative Engine Optimization
Getting your content cited, quoted, and recommended by LLMs and AI search systems.
llms.txt
A practical guide to `llms.txt`: what it is, what it is not, when it helps, and how to publish one without turning it into cargo cult AI SEO.
Understand the tool layer behind real agents
Finish with the protocol layer so you can connect content, products, and workflows to model-driven tooling.
Model Context Protocol
A practical guide to MCP for engineers: what it is, where it helps, how to design better tools, and where production implementations usually go wrong.
Evaluation for LLM Features
A practical 2026 guide to evaluating LLM features: task success, grader design, regression checks, safety coverage, and release decisions.