Booking · Q4 2026 · 2 slots open20+ yrs shipping systemsSecure AI · regulated environmentsStrategy → production

Course Arc

Build a multi-agent AI office, one guide at a time.

Thirteen guides, in dependency order, from a single agent-or-not decision through retrieval, guardrails, routing, and the flywheel that improves it. By the end you have a scoped, instrumented system, not a pile of demos.

The sequence

Thirteen steps, in the order they depend on each other.

Sec. 01: Arc
  1. 01

    AI Agents vs. Prompts: When to Use Each, and When Not To

    Use one prompt for single-step work you can check yourself. Use AI agents when the next step depends on what the model finds. Here is how I decide.

    August 13, 2026

  2. 02Scheduled

    Structured Outputs and Cognitive Architectures

    Getting a model to return a shape you can act on instead of prose, plus the reasoning loops built on top of it: ReAct, Reflexion, plan-and-execute.

    Shipping September 3, 2026

    Read Step 1 first.

  3. 03Scheduled

    Tool Interfaces: Reaching a Database or an API

    How an agent reaches out to fetch or change something: the MCP bridge, and the read-vs-write scopes that keep it from doing more than it was asked.

    Shipping September 18, 2026

    Read Step 1 and Step 2 first.

  4. 04

    How RAG Answers From Your Own Documents

    Learn how RAG searches your documents, where retrieval breaks, and how to choose chunks, embeddings, and a similarity floor.

    August 8, 2026

  5. 05

    How to Choose a Retrieval Cutoff

    A practical way to set the similarity floor for RAG: real questions, source checks, ranked scores, and a refusal rule.

    August 21, 2026

    Read Step 4 first.

  6. 06Scheduled

    Knowledge Graphs

    The other way to answer a retrieval question. Sometimes a graph of entities and relationships beats a similarity search, and sometimes it does not.

    Shipping September 8, 2026

    Read Step 4 first.

  7. 07Scheduled

    Routing Work to Specialists

    How one request gets handed to the right agent instead of one model trying to do everything: the fan-out pattern this Office runs on.

    Shipping September 4, 2026

    Read Step 1 first.

  8. 08Scheduled

    Concurrency and What Agents Can't See

    What breaks when two agents run at the same time and neither one can see what the other just decided.

    Shipping September 15, 2026

    Read Step 7 first.

  9. 09

    The AI Builder Stack, Translated: LangChain, LangGraph, CrewAI, n8n

    Your proposal says LangChain, LangGraph, CrewAI, n8n, MCP, Streamlit. What each one is, when it is overkill, and what to ask before you sign.

    August 18, 2026

    Read Step 1 and Step 3 first.

  10. 10Scheduled

    Dialog State: Remembering Mid-Conversation

    How an agent holds onto what a reader already told it, and picks the thread back up after a restart instead of losing it.

    Shipping September 14, 2026

    Read Step 1 and Step 9 first.

  11. 11Scheduled

    Evaluating an Agent, With No Fine-Tuning

    Grading what an agent does against real questions, using the same retrieval floor and refusal rule from Step 5.

    Shipping September 9, 2026

    Read Step 4 and Step 5 first.

  12. 12Scheduled

    Scaling: Real Time and More Than One Tenant

    What breaks first when one agent becomes many concurrent users, built before it is written.

    Shipping September 22, 2026

    Read Step 8 and Step 11 first.

  13. 13Scheduled

    Data Flywheels

    Turning graded results back into better retrieval and better prompts. The loop that closes the arc.

    Shipping September 29, 2026

    Read Step 11 and Step 12 first.

Start a project

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