AI-agent demos are easy to find. Production-ready agent systems are harder to understand. This handbook maps the workflows, tools, memory systems, context engineering, MCP/A2A interoperability, evaluation, observability, and multi-agent architecture behind real-world AI agents. Use it to understand, design, build, and operate production-minded AI agents from first principles to framework choices and implementation patterns.Documentation Index
Fetch the complete documentation index at: https://labs.prompthon.io/llms.txt
Use this file to discover all available pages before exploring further.
Explorer
Build a broad view of AI, agent systems, trends, and foundational ideas without needing to become an engineer first.
Practitioner
Learn how to apply AI tools, agents, and workflows to study, work, and one-person-company style execution.
Builder
Follow a technical path through concepts, patterns, systems, architecture choices, and starter projects.
Contributor
Add, revise, curate, or maintain handbook pages, radar notes, source projects, and reference notes.
What This Site Publishes
The site publishes the curated handbook pages and starter-project guide pages. Source code, notebooks, and embedded frontend/build artifacts remain in the repository, where students can inspect or clone them directly.This keeps the student reading experience focused while preserving the full project archive for GitHub, local work, and future curated demos.