6 lessons
Prompt engineering foundations
Move from vague requests to explicit jobs, context, constraints, examples, and evaluators.
Start path →Learn by building, testing, and explaining.
Short practical paths connected to community prompts, critiques, and real implementation decisions.
8 lessons
Context engineering in practice
Design retrieval, memory, grounding, and context budgets that improve reliability.
Start path →7 lessons
Evaluate AI systems
Build representative datasets, weighted rubrics, adversarial tests, and regression gates.
Start path →9 lessons
Build dependable agents
Define tool contracts, state, permissions, recovery, human escalation, and traces.
Start path →How learning works
No certificates. Evidence of practice.
- Study a working pattern.
- Adapt it to a real constraint.
- Publish the result or failure.
- Critique another member’s approach.