Agentic AI
Chapters
- 01What Is an AI Agent?
Agent = Model + Harness, and Agency ≠ Authority
- 02Levels of Automation
Autonomy is a dial, not a switch: set a level per decision, and justify it
- 03Workflow Design Patterns
When code picks the next step: six workflow shapes, and where they live in real agents
- 04Agentic Design Patterns
When the model holds the pen: six agentic patterns, and the fence each one needs
- 05Retrieval-Augmented Generation
Semantic Chunking, Sparse(BM25) & Dense retrieval, Reciprocal Rank Fusion, Cross Encoder (Reranking), and Hallucination Checks
- 06Type Safety, Loop Control & State
Pydantic, Outlines, LMQL, Loop Control, and State Management
- 07Context Management
6 Strategies: Offload, Reduce, Retrieve, Isolate, Cache, and Consolidate, 5 Failures: Poisoning, Clash, Confusion, Confusion, and Rot
- 08Memory Management
Working memory, Long-term memory: Episodic, Semantic, and Procedural, and Dreams
- 09Hallucination Checks
Check each claim against what the agent saw, not how sure it sounded: NLI, token confidence, and repair-trim-withhold
- 10LLM as a Judge
A judge is an instrument: biases, Cohen's kappa, psychometrics, and why A-vs-B beats a score
- 11Agent Security Principles
OWASP Top 10, PII redaction, Prompt injection, Content noderation, RBAC, and the Gatekeeper
- 12Evals
Evaluating an AI Agent: Deterministic Checks, DeepEval, Promptfoo and an Eval harness
- 13Observability & Analytics
Analytics Dashboard(Rill), Langsmith trace, and Logging
- 14Model Context Protocol
MCP Server, Client and Ops Agent
- 15System Design Patterns
Timeouts, Retries, Circuit Breakers, Bulkheads, Idempotency, Saga, Rate Limit, Dead Letter Queue, and Hedging
- 16Build vs Buy
You can rent intelligence, you can't rent accountability: build, adopt, buy or partner, per component, with the arithmetic
This course includes
Course content
16 sections • 237 topics • Read: 3h 9m • Video: coming soon