Claude Code for QA

Automate testing with Anthropic's agentic AI coding assistant, right inside your terminal.

Course Summary

Learn to use Claude Code as your AI pair-tester: generate and refactor test automation, debug failing suites, and drive end-to-end QA workflows straight from the terminal. Hands-on for QA engineers and SDETs who want to ship faster with agentic AI across Playwright, Selenium, Pytest, and API testing. Includes real projects, prompt patterns, and reusable workflows.

The Complete Picture

Everything you learn, end to end

From installing Claude Code in your terminal to shipping an AI-assisted test suite that runs on every pull request. Below is the full map of the workflow, the architecture, the modules, and the outcomes.

Terminal-firstPlaywright & SeleniumPytest & API testingSkills & subagentsMCP serversCI/CD on every PR
Figure 1 — The end-to-end QA workflow you will run in this courseYOU · set the intent, review the plan, approve the diff, own the quality call1UnderstandRead the story, codeand acceptance criteria2DesignRisk-based test cases,coverage matrix, data3BuildPlaywright, Selenium,Pytest, API suites4RunExecute, debug, fixflaky and failing tests5TriageRoot cause, screenshots,file the bug in Jira6ShipCI pipeline, reports,dashboards on every PRCLAUDE CODE · reads the repo, writes the tests, runs the suite, reads the trace, opens the PRone agent loop, in your terminal, with your files
Figure 2 — What Claude Code actually is, and how a request flows through itYOUplain-English intenttyped in the terminal“test the login flow”CLAUDE CODE (CLI agent)Context & memoryCLAUDE.md, open files, historyPlannerbreaks intent into ordered stepsTool executorpicks and calls the right toolPermission gateyou approve edits and commandsVerifierre-runs until the test really passesTOOL BELTRead / Write / Edittouch any file in the repoBashnpm test, pytest, git, dockerGrep / Globfind code across the monorepoWebFetchpull docs, specs, API contractsTask / subagentsspawn focused helper agentsYOUR ENVIRONMENTThe repositoryapp code + test code togetherTest suitesPlaywright, Selenium, PytestThe browserdriven live via Playwright MCPJira / GitHubtickets, PRs, comments via MCPCI runnerGitHub Actions, Jenkins, GitLabresults, traces, screenshots and failures flow back — the loop repeats until it is green
Figure 3 — The four-phase journey, from first install to a running AI test factoryPHASE 1FoundationsInstall and configure the CLISlash commands and core toolsCLAUDE.md project memoryYour first generated testPHASE 2AutomationPlaywright end-to-end suitesSelenium and Pytest refactorsAPI testing and contract checksDebugging and de-flakingPHASE 3ScaleSkills you install once, reuseSubagents and agent teamsMCP servers: browser, Jira, DBHooks and guardrailsPHASE 4ShipCI on every pull requestAutomated code reviewReports, metrics, dashboardsCapstone: your QA portfolioWeek 1 · foundationsWeek 4 · running in production
Step zero

Install it in under two minutes

Claude Code is a command-line agent. There is no IDE to learn and no plugin to configure — you install it once, point it at a repository, and start talking to it.

bash
# 1. install the CLI (Node 18+) npm install -g @anthropic-ai/claude-code # 2. open your test repository and start cd ~/work/my-automation-suite claude # 3. let it learn the project, then verify > /init > /doctor
/init
writes a CLAUDE.md that teaches Claude your project
/doctor
checks install, auth, Node version and permissions
/model
switch between fast and deep reasoning modes
/clear
reset context between unrelated tasks
What we teach

Module by module — the full syllabus

Nine modules. Every one of them ends with something running on your machine, not a slide you nod along to.

01Claude Code fundamentals

Install, auth, models, the REPL loop, slash commands, permission modes, plan mode, git worktrees and when to reach for each one.

You walk out with: A working setup and your first AI-written test
02Project memory and QA prompting

CLAUDE.md at global, project and local level; writing rules that stop hallucinated selectors; prompt patterns that produce reviewable diffs instead of walls of code.

You walk out with: A CLAUDE.md your whole QA team can share
03Manual QA, accelerated

Turn a user story into risk-based test cases, boundary and negative sets, test data, and a traceability matrix — then export straight into your test management tool.

You walk out with: A full test case pack generated and reviewed in minutes
04Web automation with Playwright

Page objects, fixtures, locators that survive redesigns, parallel runs, visual checks, trace viewer debugging, and driving a real browser through the Playwright MCP server.

You walk out with: A green Playwright suite for a real application
05Selenium, Pytest and legacy migration

Refactor brittle Selenium code, port suites to Playwright or Pytest, remove hard waits, deduplicate helpers, and modernise a suite you inherited without breaking it.

You walk out with: A migration playbook you can run on your own repo
06API, contract and data testing

Generate request collections from an OpenAPI spec, assert schemas, chain auth flows, seed and clean test data, and catch contract drift before the UI ever sees it.

You walk out with: An API regression pack wired to your spec
07Skills, subagents and MCP

Package a repeatable job as an installable skill, split work across focused subagents, wire MCP servers for the browser, Jira and your database, and add hooks as guardrails.

You walk out with: Your own reusable QA skill set
08CI/CD, code review and reporting

Run Claude in GitHub Actions on every pull request, auto-review test code, publish HTML reports and flake metrics, and gate merges on quality signals instead of vibes.

You walk out with: A pipeline that reviews and tests every PR
09Capstone: your QA portfolio

Take one real application from zero to a documented, automated, CI-backed test suite — the artifact you show in interviews and performance reviews.

You walk out with: A public portfolio project that proves the skill
Figure 4 — The five layers that turn a chat assistant into a QA systemHOOKSDeterministic guardrailsshell commands that fire before or after a tool runs — lint, format, block writes to protected pathsMCP SERVERSConnect the outside worldbrowser, Jira, database, Postman, filesystem — real systems Claude can query and act onAGENT TEAMSParallel specialistsseveral subagents working the same goal: one writes, one runs, one reviews, one reportsSUBAGENTSFocused single jobsa narrow agent with its own prompt and tool list, spawned for one task and then discardedSKILLSReusable proceduresa folder of instructions plus scripts that teaches Claude a job once and reuses it foreverCLAUDE.mdProject memorythe rules, stack, conventions and do-nots that load into context on every single turnmore leverage per engineerEvery layer is taught, built and committed during the course — you leave with the folder, not just the theory
Figure 5 — Where it all lands: the pull-request pipeline you build in Module 08ON YOUR MACHINEIN CONTINUOUS INTEGRATION1Describethe change orthe risk2Claude writestests, page objectsand fixtures3Run locallydebug, de-flake,trace failures4Open a PRcommit message andsummary generated5CI reviewsClaude reads the diffand comments6CI runsfull suite, headlessand in parallel7Merge gatereport, flake rate,coverage deltaevery failure returns as a reproducible bug with a trace, a screenshot and a suggested fixResult: regression that used to take a sprint runs on every commit, and the QA engineer moves from typing tests to designing them.That shift — from test writer to test system owner — is the whole point of this course.
Tools and coverage

The stack you will actually touch

AreaWhat you get hands-on with
AgentClaude Code CLI, plan mode, permission modes, git worktrees
Web automationPlaywright (TypeScript & Python), Selenium WebDriver
Test runnersPytest, Playwright Test, JUnit-style reporters
API testingREST, OpenAPI/Swagger, schema and contract assertions
ExtensibilitySkills, subagents, agent teams, hooks, custom slash commands
MCP serversPlaywright MCP, Jira, GitHub, filesystem, database
DeliveryGitHub Actions, PR review bots, HTML reports, flake metrics
Local modelsRunning an Ollama-backed workflow when data cannot leave the box
The shift

A QA week, before and after

Before
  • Write the same page object by hand for the fifth time
  • Spend Monday morning re-running a flaky suite
  • Copy a failure into Slack and hope someone reads it
  • Regression pack is “whatever we had time for”
  • Test data built by hand in a spreadsheet
After
  • Describe the flow, review the diff, commit
  • Agent reruns, isolates and fixes the flake first
  • Failure arrives as a filed ticket with a trace attached
  • Coverage is generated from risk, then reviewed
  • Data seeded and torn down by a reusable skill
Outcomes

What you can do the day you finish

✓Install, configure and drive Claude Code confidently from the terminal
✓Turn a user story into a reviewed, risk-based test case pack in minutes
✓Build and maintain a Playwright suite that survives a UI redesign
✓Migrate or rescue a legacy Selenium or Pytest suite without a rewrite
✓Generate an API regression pack directly from an OpenAPI spec
✓Write a reusable skill and hand it to the rest of your team
✓Wire MCP servers for the browser, Jira and your database
✓Run Claude as an automated reviewer on every pull request
✓Publish reports and flake metrics that leadership actually reads
✓Ship a public capstone project you can point at in an interview
Fit check

Who this is built for

Manual QA engineers
moving into automation without a year of syntax drills
SDETs and automation engineers
who want to multiply output, not hours
Test leads and managers
standardising how a team uses AI safely
Developers who own testing
in small teams with no dedicated QA
Prerequisites
Basic understanding of software testingComfort opening a terminalNode.js 18+ or Python 3.10+ installedNo prior AI or prompt-engineering experience needed
The Testing Academy

Stop writing tests one keystroke at a time

Nine modules, one capstone, and a terminal-first workflow you can use on Monday. Everything above is covered end to end, hands-on, with real repositories.

Enroll in Claude Code for QA

Course Curriculum

Pramod Dutta

Founder of The Testing Academy, a YouTube Channel with 95K subscribers where Pramod teaches about Software testing & Test Automation. With overall 10+ years of experience in Software Testing & Test Automation, he has mentored 10,000+ students in Software Testing, API Testing, Test Automation.

Pramod Dutta is working as SDET Manager at Tekion | Ex BrowserStack Employee & BrowserStack Champion & Certified Scrum Master. Pramod has a vast range of experience handling from Manual Testing, Mobile & Web Automation, Desktop & cloud services like AWS, GCP extra.

By joining this Automation Testing Course , you’ll have the opportunity to take control of your life, work in an exciting industry with infinite possibilities and live the life you want.

Course Pricing

Full Course

4999 INR

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