Claude Code Masterclass: Ship Real Code with AI

Install, verify, and sign in to Claude Code on macOS, Linux, or Windows (WSL2), and learn to pick the right model — Sonnet first, Opus for design, Haiku for bulk. Then internalize the loop that runs through the whole course: Plan → Implement → Test → Review → Commit. We close by having Claude read a repo it's never seen and name what it is.

A great prompt is a spec. Learn the GCOE framework — Goal, Constraints, Output format, Examples — and watch how each constraint deletes one wrong guess Claude could make. We build a small command-line task manager from a single well-structured prompt, turning plausible-but-fragile output into code you can actually merge.

Stop re-explaining your stack every prompt. Author a CLAUDE.md — a behavior file, not documentation — with five sections that earn their place: Stack, Conventions, Commands, Do-not, Glossary. Have Claude draft it from your real repo, trim it with the "trim test," and prove in a fresh chat that Claude silently obeys your rules.

The first answer is rarely the best. Learn Best-of-N: generate independent candidates, score them on a rubric where correctness is the gate and simplicity and fit break ties, then ship the winner with evidence — not a gut feeling. We build a Notes API two ways and let the rubric, not our mood, pick the winner.

Untested AI code is a guess. Generate a real pytest suite that runs the app in-process against a temp database, covering error paths and boundaries — Claude's blind spots. Then learn the "stranger's PR" self-review prompt that flips Claude from cheerleader to critic: plant a bug, and watch it name the file, line, and fix in a bug_report.md.

Never let Claude push to main. Learn the safe AI git flow: branch first, split work into atomic Conventional Commits, and generate a proper pull request description from the actual diff — never from your prompt. You stay the gate: Claude proposes, you review, you merge.

Claude reads images, not just text. Feed it a screenshot of   a broken UI, a design mockup, or an architecture diagram and turn pixels into code and fixes. Learn when a picture is worth a thousand tokens — and how to pair an image with a precise prompt for the best result.

Refactor with a safety net. Use your test suite as a guardrail while Claude restructures messy code, then have it generate accurate docstrings and READMEs from the real implementation — documentation that matches the code instead of drifting from it.

Stop re-typing the same multi-step prompt. Package a proven workflow into a reusable Claude Code skill (a slash command), so a complex task becomes a single repeatable invocation you and your team can run on demand.

Give Claude hands beyond your repo. Connect the GitHub MCP (Model Context Protocol) server so Claude can read issues, open PRs, and act on real project data — safely and within the permissions you grant.

Wire shell commands to Claude Code lifecycle events. Use hooks to enforce formatting, run tests, or block risky actions automatically — turning your standards into guardrails that fire without you remembering to ask.

Bring it all together with a production-readiness checklist: tests, docs, security, reviews, and the loop you've practiced all course. Learn what "done" really means before AI-assisted code ships.

Recap the whole journey, tackle the most common questions,  and map your next moves — how to take the Plan → Implement → Test → Review →  Commit loop into your daily work and keep leveling up.