Claude Code Crash Course: How to Master Claude Code for QA Engineering

Claude Code is an agentic coding system that reads your codebase, makes changes across files, runs tests and delivers committed code. I recently presented a webinar, Mastering Claude Code for QA Engineering, with Applause’s Senior Director and Automation Practice Lead, Adonis Celestine. This session focused on foundational agentic automation with Claude Code and on maintaining essential human-led digital quality. Continue reading for key takeaways from the session and to find out how you can unlock the potential of Claude Code for QA engineering.

How to install Claude Code 

To be installed on your computer, Claude Code requires Node.js, which is a JavaScript framework. Some minimum hardware setup is required to provide enough gigabytes of RAM, but it is completely OS-agnostic. It will also provide you with a node package manager (NPM) command in your system. Claude is not an open source tool, so you need to obtain an Anthropic API key through Claude Pro or Max. Once your NPM command is installed, the Claude command should appear in your terminal. Simply running Claude command will walk you through the login procedure, where you can provide your API key or your Claude license. 

Claude Code core concepts and terminology

Claude Code supports a variety of configurations that make communication with LLMs much more powerful. One such configuration is a mode called Hooks, which enables you to execute a specific command before, during or after a designated event occurs. The interface for Hooks configuration is a JSON-based configuration where you can provide the Hook for the particular event. Essentially, you can leverage Hooks to achieve timely executions based on a certain event.

The next core concept of Claude Code is called .md files. These files store passive intelligence that is loaded into Claude’s system prompt at each session. The .md files fall into four buckets:

• ~/.claude/CLAUDE.md: Global user preferences, including your personal coding style, preferred tools and global conventions.
• CLAUDE.md (root): Team instructions committed to Git. Architecture decisions, test standards and coding conventions.

• .claude/rules/: Path-scoped rules that are loaded only when matching files are accessed (E.g. src/**/*.ts rules for TypeScript files).
• .claude/docs/: On-demand knowledge in the form of reference docs that are pulled when explicitly needed, such as API schemas and test plan templates.

Then there is a concept called Skills, which is a feature that supports active, reusable workflows triggered by slash commands or autonomously. Slash commands are one Skill, and they map complex test workflows to simple triggers. Model overrides are another, and they route simpler validation tasks to cheaper models. Meanwhile, tool restrictions explicitly define which tools the Skill can access. The magic of Claude Code is that if you don't know how to configure something, you can ask Claude Code itself. You can say, “Please configure a Skill. Please create a new skill for me.”

Planning and thinking approaches are the next concept to know. In extended thinking mode, Claude traces complex logic, debugs silently, and evaluates testing tradeoffs internally before emitting an actionable tool call. In planning mode, Claude describes changes, renders a plan, and waits for explicit approval before executing any tool. This mode is ideal for architect-review workflows before committing test framework changes.

Auto-memory and the .remember folder are more key terms. Claude Code needs to remember your conversations. It needs to remember the context window, especially if you have lots of projects. It needs to somehow differentiate between them. That's where auto-memory comes into play, quietly observing your coding sessions and taking notes to better understand your codebase and prevent repeat errors. Auto-memory loads the first 200 lines of memory into the system prompt at startup. The .remember folder, on the other hand, uses semantic retrieval to look for relevant notes, allowing you to store much more information and receive only what is relevant to the current task.

How to set up a test automation project from scratch

Setting up a test automation project from scratch can be broken down into six steps.

1. Bootstrap CLAUDE.md

Define stack, folder structure, naming conventions and test standards. Claude reads this on every session. 

2. Architecture planning session

Ask Claude to think step by step and propose a test framework architecture. Don’t write code yet – just the plan. Then, review and approve.

3. Scaffold with Skills

Create Skills for /gen-e2e, /gen-unit, /gen-api. Each Skill knows the framework conventions and test patterns.

4. Configure Hooks

PreToolUse: block schema-breaking changes. PostToolUse: auto-run tests, lint. SessionStart: inject last session summary.

5. Iterate with /compact

Keep sessions focused. After each major milestone, /compact or start fresh session – reload CLAUDE.md context.

6. MCP + Playwright setup

Install Playwright MCP server. Claude can now browse, interact, and assert against real browser state during test gen.

Previously, you needed to at least have some test automation experience, understanding what you are doing and how you are going to achieve that result. But now with Claude Code, things are much simpler.

Playwright MCP versus Agents

Playwright MCP (Model Context Protocol) is an open standard that lets Claude connect to external tools, services and data sources through a structured interface. For example, you want to have an LLM to be able to communicate with Slack, Google Drive, Jira, with some SQL database. For all this there are different model context-based protocol tools. Playwright MCP is ideal for test generation, exploration and live debugging with Claude.

Playwright Agents, on the other hand, are Playwright’s built-in AI-driven test approach where the test instructs an AI model at runtime to accomplish certain goals – without specifying every selector or action. They are non-deterministic, so the AI figures out how to navigate the page. Playwright Agents are excellent for runtime-resilient execution in continuous integration. They also pair nicely with MCP: You can use Playwright MCP to explore page structure, then Claude writes Agents-style tests from that context.

Key takeaways for QA engineers

• Start with structure: CLAUDE.md + Skills + Hooks = a self-guiding test automation agent that stays aligned with your standards.

• Memory over repetition: Persist decisions in CLAUDE.md. Use /compact aggressively. Run one focused session per feature.

• MCP unlocks real browser power: Playwright MCP lets Claude see and interact with your live app – meaning tests are generated from reality, not assumptions.

• Agents vs. MCP is not either/or: MCP is for exploration & generation; Playwright Agents excel in resilient runtime execution. They complement each other.

• Bedrock for enterprise: AWS IAM, data residency, consolidated billing – use Bedrock when your org requires it; Anthropic direct otherwise.
• Plan before you code: Always use planning mode for new frameworks. Agree on architecture first, then let Claude implement incrementally.

By following the steps and practices outlined in this blog, QA engineers can safely use Claude Code to implement AI tools and skills that accelerate their testing lifecycle. To gain a deeper understanding of agentic automation with Claude Code, don’t forget to check out the webinar, Mastering Claude Code for QA Engineering.