My team has started using Claude Code to build and ship software, but I have never run an AI coding agent. I still open and edit files manually, so I'm trying to figure out the best way to get started. Should I take a structured course, such as one from Udacity, Pluralsight, LinkedIn Learning, or the official training materials, or is it better to learn by experimenting with the command-line tool and following tutorials? I'm mainly looking for advice aimed at someone who has never used an agent before.
4 Answers
The fastest way to begin is to open the CLI in a real project and ask it a focused question, such as “Where is the user’s password verified?” Then try a small change, like adding WebP upload support to an existing upload flow. You’ll learn the basic loop quickly: explain the goal, provide context, let it investigate or edit, and review the result. A course can help later, but it isn’t required for the first steps.
I wouldn’t spend money on training immediately. Make a small practice project—a to-do app, weather client, or something similar—and try doing the whole project through the agent. Ask it to explain the code, propose a plan, implement one piece at a time, and help debug failures. The documentation and an official beginner course are useful references, but hands-on repetition is what makes the workflow click.
Think of the agent like a capable junior developer sitting beside you. You describe the outcome and constraints, it drives the implementation, and you review what it produces. Be specific about the relevant files, expected behavior, edge cases, and tradeoffs. For example: “Add an endpoint for these resources and parameters, keep authorization consistent with this existing file, and explain the tests you’ll add.” Then challenge anything that doesn’t match your intent. Features such as skills, MCP servers, and subagents can improve the workflow later, but they aren’t necessary to get started.
A good practical workflow is to paste in the task or ticket, ask the agent to clarify anything ambiguous, have it create an implementation plan, and only then let it make changes. Review the diff and tests carefully rather than treating the output as automatically correct. It’s also worth continuing to write and read code manually sometimes; relying entirely on the agent can weaken your understanding of the system over time.

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