I’m ready to go deeper: a practical AI learning path

Delegate a bounded project and evaluate whether the full workflow helps.

Agents, systems, testing, and work that lasts.

Delegate a bounded project and evaluate whether the full workflow helps.

Take these at your own pace. Mark completion after practicing, not as a qualification.

1. Chat, workflow, or agent: choose how much work to delegate

Understand the difference between a conversation, a repeatable sequence, and an agent that can choose actions.

Practice: Use the workflow planner to describe one recurring task. Decide whether you need a conversation, a fixed sequence, or an agent.

Translate a broad goal into permitted actions, review points, and evidence of completion.

Practice: Write an agent brief with five lines: goal, inputs, permitted actions, review point, and completion evidence.

Make a reusable project brief with facts, examples, constraints, and a clear record of what changed.

Practice: Create a one-page context pack for something you do regularly. Remove one outdated fact and identify one missing fact.

Build a small test set, define useful success criteria, and measure the corrections as well as the output.

Practice: Create five cases for a recurring task and write three pass/fail criteria. Try the workflow and record one actual failure.

Create a compact record of decisions, artifacts, unresolved questions, and the next action so a project can resume cleanly.

Practice: Write a handoff for an unfinished personal project. Come back later and use it to identify the next action without rereading the chat.

Run one bounded workflow on five cases, inspect the results, and leave a handoff another person could use.