Skip to content

Labs Overview

13 hands-on labs covering the full agentic engineering stack. Each lab has a starter.py (fill in the blanks) and solution.py (reference answer).

Lab Index

LabModuleTopicEst. Time
L1: First AgentM1Single-tool agent from scratch60 min
L2a: Multi-Tool AgentM2File ops + web search75 min
L2b: Context-AwareM2Sliding window + summarization60 min
L3a: Whitelist HookM3L4 security implementation60 min
L3b: Verifier AgentM3Read-only verification75 min
L4a: Agent ChainM4YAML pipeline60 min
L4b: Multi-TeamM4Team config + domain locking90 min
L5a: ObservabilityM5SQLite tool tracing60 min
L5b: CI/CDM5Golden dataset + regression gate60 min
L6a: Eval HarnessM6pass@k evaluation60 min
L6b: Cost OptimizationM6Cascade routing45 min
L7a: AutoresearchM7Self-improving experiment loop75 min
L7b: Meta-AgentM7Agent that builds agents60 min

Running Labs

bash
cd course/labs/L1-first-agent/

# Without API key (uses mock LLM automatically):
python starter.py test.txt "What is this file about?"

# With API key:
export ANTHROPIC_API_KEY="sk-ant-..."
python starter.py test.txt "What is this file about?"

# Check solution after attempting:
python solution.py test.txt "What is this file about?"

Lab Structure

Each lab has:

  • starter.py — Code skeleton with TODO markers
  • solution.py — Complete reference implementation
  • No additional files needed — all labs are self-contained

Offline Mode

All labs include automatic mock LLM fallback. No API keys required. The mock client returns realistic, deterministic responses so you can verify your code logic without paying for API calls.

FDSA Agency — Agentic Engineering Course. Part of the fdsa.ai orchestration platform.