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