Most QA engineers who use Claude plateau at the same place: pasting a requirement into a chat window and asking for test cases. It helps but it leaves most of the value on the table. Our upcoming BrowserStack meetup in Pune transforms this challenge into opportunity. Learn to leverage Claude as a true QA teammate, building robust, automated workflows and agents that elevate your team's efficiency and verification discipline. Reserve your spot today for actionable insights that will change how you approach AI in QA.
What will we cover
- The mindset shift: Why prompting alone plateaus, and what "delegating to a teammate" looks like in practice
- A QA day, mapped to Claude: The right Claude surface for requirements, test design, exploratory testing, test data analysis, and reporting
- Choosing the right model: The current Claude lineup and a practical guide to which model fits which QA task, and when to escalate
- The Claude Code toolkit for QA: Project context files, reusable skills, isolated reviewer agents, deterministic hooks, and connections to tools like Jira and test management systems
- Claude API for QA automation: Routing tasks to the right model, prompt caching, and batch processing for large, non-urgent jobs like nightly failure triage
- Building a QA agent with Claude: The Claude Agent SDK, built live: a failure-triage agent that reuses the same skills, hooks and context from earlier in the session
- Evaluating AI features and agents: Golden datasets, LLM-as-judge rubrics, and trajectory checks, applied live to the agent we just built
- Prompting patterns that work for QA: Ten patterns, shown live as before-and-after comparisons
- Trust, but verify: Real examples of AI output that looked correct but failed when run, and the QA discipline that catches it
Key takeaways
- A clear mental model for which Claude capability to reach for, and when
- A model-selection guide for common QA tasks
- A practical way to test AI features and agents, not just use them
- Ten prompting patterns they can use the next morning
- A starter kit repo with a QA project context template, three reusable QA skills, a test-review agent, safety hooks, and API automation examples
Why this matters: AI assistants are now part of most QA engineers’ toolkits, but usage is shallow and inconsistent across teams. This session gives attendees a structured, practical path from occasional prompting to reliable, team-wide workflows — with the verification discipline QA is uniquely positioned to bring.