# Slide Deck Outlines

Presentation outlines for all 8 modules. Each module has ~10-15 slides.

---

## Module 1: Foundations (~12 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Agentic Engineering: From Foundations to Production |
| 2 | What Makes an Agent? | LLM + Tools + Loop = Agent. Diagram of the 3 components. |
| 3 | The Harness vs The Model | Table comparing what matters. "The harness IS the product." |
| 4 | 5 Subsystems of a Harness | Instructions, Tools, Environment, State, Verification. Diagram. |
| 5 | 4 Dimensions of Control | Context, Model, Prompt, Tools. Which gives you leverage? |
| 6 | The Repository IS the Spec | Single source of truth. CLAUDE.md, init.sh, feature_list.json. |
| 7 | Decision Framework | 4-question filter. When to use agents, when not to. |
| 8 | The Agent Loop | Think → Act → Observe → Repeat. Pseudocode. |
| 9 | Tool Calling Deep Dive | Anatomy of a tool. The reasoning parameter. Forced vs auto. |
| 10 | Vibe Coding vs Agentic Engineering | 5 hard rules. Risk compounds with runtime. |
| 11 | Do You Trust Your Agents? | The course thesis. Discussion question. |
| 12 | Module Summary | Key takeaways. Prep for Lab 1.8. |

---

## Module 2: Architecture (~15 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Agent Architecture |
| 2 | The Four Pillars | Tools, Loop, Context, Memory. Diagram. |
| 3 | Tool Design Patterns | MCP vs CLI vs Script vs Skills. Context cost matrix. |
| 4 | LSP MCP Server | Symbol-level search. Diagram. When grep is too slow. |
| 5 | Agent Loop Variants | 5 levels: Simple → Tool-Use → Task-Completion → Sub-Agent → Multi-Agent |
| 6 | Skills System Deep Dive | Path-scoped skills, subdirectory CLAUDE.md, plugin distribution. |
| 7 | Agent-Readable Workspace | init.sh, feature_list.json, clean state. The discovery pattern. |
| 8 | Agent Loop Variants Detail | Code examples for each level. |
| 9 | Context Window Management | Sliding window, summarization, structured outputs. Hybrid approach. |
| 10 | Memory Patterns | Mental models, expertise files, scratch pads, session logs. |
| 11 | The Reasoning Parameter | Force chain-of-thought on every tool call. Code example. |
| 12 | Codebase Architectures | Atomic, Layered, Pipeline, Vertical Slice. Comparison. |
| 13 | Architecture Decision Tree | Which pattern for which project? |
| 14 | Module Summary | Key takeaways. Prep for labs. |

---

## Module 3: Safety & Security (~14 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Safety & Security |
| 2 | Prompt Injection (L0) | ACIP defense. Attack vectors: direct, indirect, role-play. |
| 3 | Why Bash Is the Problem | Single funnel for every destructive action. Diagram. |
| 4 | The Probability Math | 1% × 100 turns = 63%. The chart that changes everything. |
| 5 | The 6-Level Security Ladder | L0 (ACIP) → L1 (skill) → L2 (system prompt) → L3 (blacklist) → L4 (whitelist) → L5 (no bash) |
| 6 | L3 Marque Break | Agent writes cleanup.py → runs python cleanup.py. The demo. |
| 7 | Damage Control | 3 access levels: zero-access, read-only, no-delete. YAML config. |
| 8 | Hook Architecture | 13 lifecycle events. PreToolUse, PostToolUse, Stop, etc. |
| 9 | The Verifier Pattern | Builder + Verifier over Unix socket. Diagram. |
| 10 | Confidence Ladder | PERFECT → VERIFIED → PARTIAL → FEEDBACK → FAILED |
| 11 | Defense-in-Depth Stacking | All 6 levels stacked. No single point of failure. |
| 12 | Security Decision Tree | Which level for which deployment? |
| 13 | Module Summary | Key takeaways. Prep for labs. |

---

## Module 4: Multi-Agent Orchestration (~18 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Multi-Agent Orchestration |
| 2 | Why One Agent Is Not Enough | Context ceiling, capability ceiling, reliability ceiling. |
| 3 | 3 Orchestration Patterns | Dispatcher, Pipeline, P2P. Comparison diagram. |
| 4 | P-Threads | N agents in parallel. Pick best result. mprocs example. |
| 5 | F-Threads | N agents → Judge → Winner. Your UI Agents system. |
| 6 | Depth-2 Delegation | Orchestrator → Leads → Workers. Never execute. |
| 7 | Agent Experts That Remember | Mental models. Self-improve commands. Compounding knowledge. |
| 8 | Domain Locking | Per-agent permissions. Read/write/delete scope. |
| 9 | TillDone Task Discipline | Task list gating. Live progress. Nudge on incomplete. |
| 10 | Agent Chains | YAML-defined pipelines. $INPUT/$ORIGINAL variables. |
| 11 | P2P Communication | Pi-to-Pi. 4 tools. Hop limits. Self-healing. |
| 12 | MCP Agent Mail | Jeff's alternative: inboxes, threads, file leases. |
| 13 | Service Connectors | Twitter, GitHub, Linear, Slack via MCP. One per service. |
| 14 | Conversation Awareness | Shared JSONL logs. Cross-agent context. |
| 15 | CEO Board System | 8 agents. Adversarial debate. Fact verification. |
| 16 | UI Agents System | 12 agents. Brand → Product → Tree → Branch → Leaf. |
| 17 | Orchestration Decision Tree | Which pattern for which problem? |
| 18 | Module Summary | Key takeaways. Prep for labs. |

---

## Module 5: Production Patterns (~14 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Production Patterns |
| 2 | Production Is Different | Deterministic vs non-deterministic. Fixed vs variable cost. |
| 3 | CI/CD for Agents | Golden datasets. Regression testing. Prompt versioning. |
| 4 | The 5-Tool Production Stack | Your architecture: Claude Code, Pi, OpenCode, Hermes, OpenClaw. |
| 5 | Stack Diagram | agent-mux → mprocs → psmux → dmux. Full stack. |
| 6 | The Agent Manager Role | 5 areas of ownership. 90-day playbook. |
| 7 | Shadow Deployments | Run new agent alongside prod. Compare before switching. |
| 8 | Rollback Strategies | Prompt + model + parameters + config. Version-locked configs. |
| 9 | Observability | SQLite tracing. Every tool call logged. Decision tracing. |
| 10 | Cross-Provider Session Search | Jeff's tool. Index sessions across 11 providers. |
| 11 | Alerting | Agent-specific signals: tool loops, cost spikes, grinding. P0/P1/P2 routing. |
| 12 | Deployment Modes | Local trusted, authenticated private, authenticated public. |
| 13 | Cost Control | Budgets per agent/session/task. Warnings vs hard stops. |
| 14 | Module Summary | Key takeaways. Prep for labs. |

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## Module 6: Economics & Evaluation (~12 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Economics & Evaluation |
| 2 | The Compute Advantage Equation | (Compute Scaling × Autonomy) ÷ (Time + Effort + Cost). |
| 3 | Your Stack's Compute Advantage | Real numbers for each tool in your stack. |
| 4 | LLM Pricing Landscape | 100x range. Gemini Flash ($0.15/M) to Claude Opus ($15/$75/M). |
| 5 | Cascade Routing | Cheap model for simple steps, expensive for complex. 66% savings. |
| 6 | Cost Per Session Math | The 3x rule. Retries, tool overhead, context growth. |
| 7 | Jeff Emanuel Case Study | 52 subs, $12K/mo, 85K commits. What's his CAC? |
| 8 | Agent Evaluation Metrics | pass@k, tool call accuracy, cost per task, loop efficiency. |
| 9 | Automated Evaluation | Golden datasets. VCR-style recording. Regression detection. |
| 10 | A/B Testing Agents | Canary deployments. 5% traffic split. Compare success rate, cost. |
| 11 | Human Evaluation | Spot-check 5-10%. Catches 2-3x more failures than automated. |
| 12 | Module Summary | Key takeaways. Prep for labs. |

---

## Module 7: Advanced Topics (~10 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Advanced Topics |
| 2 | Autoresearch | Run → Measure → Log → Decide. Self-improving agents. |
| 3 | Integrity Guards | Code hashing (anti-grinding). Median over best. Test set integrity. |
| 4 | Meta-Agents | Agents that build agents. Parallel research experts. |
| 5 | Beyond MCP | MCP vs CLI vs Script vs Skills. Context cost matrix. |
| 6 | Mac Mini Agent | Physical sandbox. Steer + Drive + Listen + Direct. |
| 7 | Always-On Agents | Voice→CLI bridge. Job server pattern. Heartbeat execution. |
| 8 | Framework Comparison | Paperclip vs Multica vs Cabinet. When to use which. |
| 9 | The Future | Agentic Coding 2.0. Agents conducting agents. |
| 10 | Module Summary | Key takeaways. Prep for labs. |

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## Module 8: Capstone (~8 slides)

| Slide | Title | Content |
|-------|-------|---------|
| 1 | Title | Capstone: Production Multi-Agent System |
| 2 | Project Options | Brand Monitor, Code Review Pipeline, Strategic Decision Board. |
| 3 | Phase 1: System Design | Architecture diagram. Agent roster. Data model. Cost estimate. |
| 4 | Phase 2-3: Build + Integrate | Agent implementation. Mental models. Wiring agents together. |
| 5 | Phase 4-5: Security + Test | L3 minimum. Golden dataset. pass@k evaluation. |
| 6 | Phase 6-7: Deploy + Review | CI/CD. Shadow deploy. Red-team. Retrospective. |
| 7 | Pass Criteria | What constitutes a passing project. Rubric. |
| 8 | Next Steps | After the capstone. Continuing education. Community. |
