Building AI Agents tutorial

Build an AI helper inside your own app. Pick the right shape, give it tools, set its limits and test it, without writing code.

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Course contents

One Agent That Works

  1. Workflow or Agent? — The four shapes of an AI helper inside an app: one model call, a chain, a router and an agent. Learn what each one can do, what it costs, and how to pick the simplest one that works.
  2. The Agent Loop by Hand — How an agent works inside an app: it asks the model, runs a tool, reads the result and repeats. Learn why every loop needs a stop rule, a step limit and a budget.
  3. Tool Design — The model picks a tool by reading its name and description. Learn to write clear tool cards, clear input rules and helpful error messages, so your agent picks the right tool and fixes its own mistakes.
  4. Structured Output and Validation — Give the helper's answer a fixed shape with named boxes, then check every box before the customer sees it. Send problems back for a fix, and pass to a person after too many tries.
  5. State, Memory and Context Limits — An AI helper can only read so much of a long chat. Learn how a memory window, a summary, a sticky note and customer memory keep the important facts close, and keep them with the right customer.
  6. Guardrails, Permissions and Human Approval — Some actions are never allowed, and some need a person's OK. Learn how the app checks every tool request, keeps customers to their own orders, sends big refunds to a person and resists prompt injection.
  7. Streaming and Interruptions — Show the customer what the helper is doing while it works, and stop cleanly when they press Stop. Learn streaming, progress chips, cancel checks and honest stopped messages.

Agents in a Real Product

  1. Multi-Agent: Subagents, Handoffs, Orchestrators — When one AI helper has too many tools and a long chat, a front desk can split the work between specialists. Learn handoff notes, lost facts and the scorecard rule.
  2. MCP: Tools from Outside the App — MCP lets an AI helper plug in tools from other services. Learn how an app connects to an MCP server, gets its tool cards, checks who may use them, and copes when the server stops answering.
  3. Evaluating Agents — Test the helper with many sample chats, every time you change it. Each scenario gets three checks: the reply, the tools it used and what really changed in the shop.
  4. Observability, Cost and Reliability — Read a trace to see what every step of an agent costs in coins and time. Cut a bloated prompt, set a budget per message, add timeouts and retries, and send easy questions to a smaller model.
  5. Framework Tour: The Same Agent, Five Ways — Frameworks run the agent loop for you. See what five popular frameworks give, what they hide, and how to choose one by your team's needs.
  6. Capstone: An Agent for Your App — Put every choice from the course on one Agent Card, then test the whole helper with 20 test chats, attacks included. Export the card and a starter file, and fill in the same card for your own app.

Reference

  1. Cheat Sheet — Every idea from Building AI Agents on one page: the four shapes, the agent loop, tool cards, answer checks, memory, guardrails, live replies, teams, MCP, testing, cost, frameworks and the Agent Card.