LLM/Agent Engineering Academy
Master every layer of the AI agent stack. Six focused academies covering context engineering, observability, evals, RAG, multi-agent orchestration, and tool design — each with modules and interactive playgrounds.
Academies
Choose an academy to start learning
“Fill the context window with the right information”
Master the art and science of filling the context window with just the right information. 11 chapters covering fundamentals, strategies, techniques, anti-patterns, and production best practices — with interactive code examples.
“You can't fix what you can't see”
Learn how to trace, debug, and monitor AI agents in production. From structured logging to real-time dashboards — understand every step your agent takes.
“Ship with confidence”
Build evaluation systems that catch regressions before your users do. From simple assertions to complex rubric-based scoring — evaluate LLM outputs systematically.
“Everyone builds RAG, most do it wrong”
Go beyond naive RAG. Learn agentic retrieval patterns — query planning, multi-step reasoning, self-correcting retrieval, and production-grade RAG architectures.
“From single agents to agent teams”
Design, build, and orchestrate teams of specialized AI agents. 12 chapters covering orchestration patterns, communication, shared state, task decomposition, error handling, frameworks, and production deployment — with interactive code examples.
“Agents are only as good as their tools”
Master tool design for AI agents and the Model Context Protocol (MCP). 12 chapters covering fundamentals, MCP servers, tool selection, security, and production patterns — with interactive code examples.
Your codebase. Your examples.
Every enterprise spends separately on AI upskilling and internal onboarding. We merge them. Your engineers learn context engineering, RAG, evals, and agent patterns — using your actual codebase, products, and production incidents as the examples.
1. Connect Your Repo
Point the API at your GitHub org, internal docs, support tickets, and incident reports. We ingest and index everything.
2. Auto-Contextualize
Every module's code examples, playground scenarios, and anti-patterns are regenerated using your domain. Generic becomes specific.
3. Track & Measure
Dashboard for team progress, skill gaps, and ROI. Your engineers learn AI patterns AND your product domain simultaneously.
2x ROI
One program replaces separate AI training + internal onboarding
Self-hosted
Your code never leaves your infrastructure
API-first
Embed in your existing LMS or run standalone
Open core
Free academy forever. Enterprise features for teams