Interactive guides for product managers
Understand AI agents well enough to make good product calls
Seven modules, written for PMs rather than engineers. Start with how agents work and the tools at a glance, go deeper on each tool, learn what to measure in production, then how to launch. Modules 1 to 5 and 7 follow the same example: a research assistant that takes a question, searches the web, reads the results and writes a short report. Module 6 takes those ideas into a regulated setting, a wealth assistant for investors. Every module has a hands-on demo you can click through, and quizzes to check yourself.
1
What an agent is, and how it gets from idea to launch.
planactobserverepeat
- Agent vs chatbot vs workflow, and the spectrum in between
- The five parts, choosing a model, tool failures and MCP
- Evals that account for randomness, and how agents fail
- Guardrails, human approval, cost, monitoring and staged rollout
about 30 minstep-by-step agent demo5 quizzesspec templatecheat sheet
Start module 1 →
2
The three tools at a glance: what each one does and how they fit together.
buildorchestrateobserve
- What each tool is, in plain language and a kitchen analogy
- Why real agents need a graph, not a straight line
- Reading a trace to debug cost, speed and wrong answers
- A decision guide, the alternatives and what each really costs
about 25 minclickable graph + trace demo3 quizzesdecision guide with alternatives
Start module 2 →
Builds on module 1. If agents are new to you, start there.
Module 6 · Running it in production
What to measure when an AI assistant talks to investors: 7 categories split into P0 launch blockers, P1 core health and P2 optimisation. Includes a spot-the-breach demo, how to prove a zero, wiring it up in Langfuse, an incident runbook and a P0 launch checklist.
complianceaccuracygovernance
about 35 minspot-the-breach demo3 quizzes
Start module 6 →