Agentic Engineering Course
From Foundations to Production — build, deploy, and maintain production-grade AI agent systems.
Quick Start
# Read this first:
less GETTING-STARTED.md
# Then start with Module 1:
less M1-FOUNDATIONS.md
# Need API keys?
less API-KEYS.md
# Something broken?
less TROUBLESHOOTING.md
Course Map
| Module |
Title |
Est. Hours |
Prerequisites |
| M1 |
Foundations |
4-6 |
None |
| M2 |
Architecture |
6-8 |
M1 |
| M3 |
Safety & Security |
5-7 |
M1 |
| M4 |
Multi-Agent Orchestration |
7-9 |
M1, M2 |
| M5 |
Production Patterns |
5-7 |
M1, M2 |
| M6 |
Economics & Evaluation |
4-6 |
M1 |
| M7 |
Advanced Topics |
5-7 |
M1-M6 |
| M8 |
Capstone |
8-12 |
M1-M7 |
File Structure
course/
├── 00-CURRICULUM.md # Full curriculum with lesson plans
├── M1-FOUNDATIONS.md # What are agents, harness vs model, decision frameworks
├── M2-ARCHITECTURE.md # Tools, loops, context, memory, codebase patterns
├── M3-SAFETY.md # 5-level security ladder, hooks, verifier pattern
├── M4-ORCHESTRATION.md # Multi-agent patterns, delegation, P2P comms
├── M5-PRODUCTION.md # CI/CD, shadow deploys, monitoring, rollback
├── M6-ECONOMICS.md # Model pricing, cascade routing, evals
├── M7-ADVANCED.md # Autoresearch, meta-agents, Beyond MCP
├── M8-CAPSTONE.md # 3 project options with phases and rubrics
├── NON-TECHNICAL.md # 7 decision frameworks for managers/PMs
├── ASSESSMENTS.md # 56 quiz questions + answer keys + rubric
├── COMPETITIVE-ANALYSIS.md # vs Anthropic, TAC, DL.AI, ClaudeFAST
├── DEBATE.md # Armin vs George — the two poles of agent debate
├── FEYNMAN.md # 15 core concepts explained in plain language
├── FIELD-MANUAL.md # Consolidated technical quick reference (11 sections)
├── JEFF-INTEGRATION.md # Jeff Emanuel's 14-tool flywheel mapped to course
├── REFERENCE-STACK.md # Production 5-tool architecture
├── TOOL-REFERENCE.md # 5-tool comparison reference
└── labs/
├── L1-first-agent/ # Your first single-tool agent
├── L2-multi-tool/ # Add file + search tools
├── L2-context/ # Sliding window + summarization
├── L3-whitelist-hook/ # L4 security whitelist implementation
├── L3-verifier/ # Read-only verification agent
├── L4-agent-chain/ # YAML-defined plan→build→review pipeline
├── L4-multi-team/ # Multi-team system setup
├── L5-observability/ # SQLite-based tool call tracing
├── L5-cicd/ # Golden dataset + regression gate
├── L6-eval-harness/ # pass@k evaluation system
├── L6-cost-optimization/# Cascade routing optimizer
├── L7-autoresearch/ # Self-improving experiment loop
└── L7-meta-agent/ # Agent that builds agents
How Each Module Is Structured
Lesson X.Y: Title
Type: Concept | Technical | Architecture | Lab | Assessment
Est. Time: XX min
Body:
- Core teaching points
- Examples from tac/ repository
- Code snippets where applicable
Key sources in your repo: [file paths]
Resource Index
Every lesson references specific files from the tac/ directory:
| Module |
Primary Sources |
| M1 |
single-file-agents/sfa_poc.py, mythos-learnings.md |
| M2 |
single-file-agents/codebase-architectures/, 20 sfa_*.py files |
| M3 |
bash-damage-from-within/, the-verifier-agent/, damage-control.ts |
| M4 |
lead-agents/, ui-agents/, ceo-agents/, pi-vs-claude-code/ |
| M5 |
paperclip/doc/DEPLOYMENT-MODES.md, hooks-multi-agent-observability/ |
| M6 |
aiproxy/benchmarks, benchy/, agentic-coding-tool-eval/ |
| M7 |
mythos-learnings.md, brand-monitor/autoresearch, beyond-mcp/ |
| M8 |
brand-monitor/, the-verifier-agent/, ceo-agents/ |
| Reference |
REFERENCE-STACK.md, TOOL-REFERENCE.md, COMPETITIVE-ANALYSIS.md |
What This Course Covers That No Other Does
- Original security research: mythos-learnings (reward hacking, grinding, confabulation cascades from Anthropic's 244-page paper)
- Hands-on security ladder: bash-damage-from-within L1→L5 with runnable demos and the L3 marquee break
- Production verifier pattern: read-only agent that independently verifies builder's work
- Autoresearch loop: brand-monitor's self-improving agent with real latency data (52→46ms)
- Complete multi-team architecture: depth-3 delegation (orchestrator → leads → workers) from your own ceo-agents/lead-agents/ui-agents
- Model economics: LLM pricing 100x range, cascade routing, the 3x rule, pass@k math
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