Claude Code Workshop for Development Teams: A Practical Guide

By the UXreviewer.io team4 min read

A Claude Code workshop for development teams teaches engineers to use Anthropic's terminal-based coding agent on their real codebase: configuring permissions, writing a shared CLAUDE.md, planning before editing, and reviewing agent changes with tests. The goal is a consistent team workflow, not individual tricks.

Claude Code is powerful because it can read your repository, run commands and change many files in one go. That same power creates new failure modes when a team uses it without shared rules. Below is what a team-focused workshop should cover, module by module, and how to keep the benefits after the session ends.

Why train a whole team instead of individual developers?

Individual developers can learn Claude Code on their own, and many do. The problem appears at team level: five people with five different prompting styles, permission settings and review standards produce inconsistent pull requests, and reviewers cannot tell how much of a change was checked by a human.

A team workshop aligns those habits. Everyone learns the same planning routine, the project instructions live in the repository instead of in personal notes, and reviewers know what to expect from an agent-assisted pull request. This is also where you decide which tasks are a good fit and which stay manual. For the general format, see what to expect from an agentic coding workshop.

Module 1: Setup, permissions and safe defaults

The first module gets Claude Code running on every machine with settings the team agrees on. As of late 2026, Claude Code offers permission modes and allow or deny rules for tools and commands, which can be checked into the repository as project settings.

Workshop exercises here include deciding which shell commands the agent may run without asking, keeping secrets out of the working directory, and choosing when to run the agent in a sandbox or container. Teams that skip this step often swing between two bad extremes: approving every single command manually, or allowing everything.

A shared workflow also makes onboarding easier. New team members inherit a working configuration, a project memory file and documented conventions on day one, instead of discovering them through trial and error or through review comments on their first pull requests.

• Agree on a shared project settings file and keep personal overrides local.
• Allow read-only and test commands; require confirmation for deploys, migrations and destructive operations.
• Never store credentials in files the agent reads by default.

Module 2: CLAUDE.md as shared team memory

CLAUDE.md is the file Claude Code loads automatically to understand your project. In the workshop, the team drafts it together: build and test commands, architecture overview, naming conventions, folders the agent should not touch and known pitfalls.

The key lesson is brevity and maintenance. A focused file that the team updates whenever the agent makes the same mistake twice beats a long wiki copy. We cover structure and examples in detail in our article on CLAUDE.md and AGENTS.md project instructions.

Module 3: Plan first, then edit

The most valuable habit for Claude Code is separating planning from execution. Participants practise asking the agent to explore the relevant code and propose a plan, reviewing that plan, and only then letting it edit files. This catches misunderstandings while they are cheap.

A typical exercise sequence on a real ticket looks like this:

1. Ask the agent to read the relevant files and summarize how the feature currently works.
2. Request a step-by-step plan, including which tests will prove the change.
3. Correct the plan where it misreads requirements or architecture.
4. Let the agent implement in small commits and run the tests after each step.
5. Review the diff as a human, then open a pull request with a short note on what was agent-generated.

Module 4: Extending Claude Code with commands, hooks and MCP

Once the basics work, teams benefit from automating repetitive patterns. Custom slash commands capture recurring prompts such as "write tests for this module" or "prepare a release note". Hooks can run formatters or linters automatically after edits, so style issues never reach review.

The Model Context Protocol (MCP) lets Claude Code connect to external systems like issue trackers or databases. The workshop covers when that is useful and when it widens the attack surface too much. Every new connection should have a clear owner and minimal permissions.

Module 5: Review, testing and the road after the workshop

Agent output must pass the same quality bar as human code. Participants practise reading agent diffs for scope creep, invented APIs, weakened tests and silent error handling. Test-first prompting is especially effective: ask for a failing test that reproduces the bug before asking for a fix. Our guide to testing strategies for AI-generated code goes deeper.

After the session, a short follow-up helps the team refine CLAUDE.md and settings based on real use. The UXreviewer.io team behind these workshops uses Claude Code in client work, from AI app rescue to App Store releases, and can tailor modules to your stack. Book a call for free to discuss your team's starting point.

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