AI-Driven QA Lifecycle | 12th SF Bay Area Meetup
Details
AI-Driven QA Lifecycle | 12th SF Bay Area Meetup
What if AI could support quality before testing even begins?
The AI-Driven QA Lifecycle brings AI into every stage of software quality — from requirements analysis and test planning to test generation, automation, execution, failure analysis, and continuous improvement.
At The Test Tribe’s 12th SF Bay Area Meetup, Dilruba Malik will explore how AI-powered workflows and agents can help QA teams identify risks earlier, accelerate test creation, improve coverage, and move from reactive validation toward a more proactive and continuously learning Quality Engineering organization.
Event Details
- Date: 27 October 2026
- Time: 06:00 PM – 08:00 PM PDT
- Venue: 1631 N First St, San Jose, CA
Session – AI-Driven QA Lifecycle
Speaker: Dilruba Malik, Senior SQA Manager at Palo Alto Networks
The session explores how AI can connect traditionally separate stages of the QA lifecycle into a more intelligent quality ecosystem.
You’ll explore how AI can support:
- Requirements & Test Planning – Analyze product requirements and specifications to identify risks and generate relevant scenarios.
- Test Creation & Automation – Generate test cases and automation scripts using product knowledge, historical test data, and existing automation patterns.
- Execution & Failure Analysis – Use AI-powered agents to support execution, defect analysis, and root-cause investigation.
- Continuous Quality Improvement – Improve regression coverage and respond faster as products and requirements evolve.
How This Meetup Solves Your Problem
QA is still heavily reactive? Explore how AI can help identify quality risks earlier in the lifecycle.
Test creation takes too much time? See how AI can accelerate scenario, test-case, and automation generation.
Your tools and quality data are disconnected? Explore the idea of an AI-powered ecosystem connecting knowledge, automation, tools, and agents.
Regression and failure analysis consume too much effort? Learn how AI can support continuous coverage and faster investigation.
Why Show Up on 27 October?
- Because quality shouldn't begin when development is finished.
- Because AI can help QA teams move from reactive defect detection to proactive risk identification.
- Because the opportunity is bigger than AI-generated test cases - it’s about connecting the entire QA lifecycle.
- Because AI-powered agents can support testing work from planning through failure analysis and continuous improvement.
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About The Test Tribe
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