Hiren Shah | Activities
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AI Chapter
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Everyday AI Coding: Skills & Plugins in a Tester's Workflow
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Software Factories, Light and Dark Loops, harnesses, factories and why engineers need to own the outer loop - by Addy Osmani
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Microservices Testing Challenges & Strategies
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Joined MoT San Francisco chapter
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MoT San Francisco
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The MoTaverse exists to advance the quality engineering and software testing industry in a fun, safe, professional and forward-thinking way.
MoT San Francisco Chapter events exist as a way to bring people together to gather and learn about all things quality.
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Is AI Making Us More Productive or Just Busier?
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Designing self‑explaining test automation for fast root‑cause diagnosis
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The product-led approach to Quality: What I learnt working side-by-side with testers and engineers
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Stop treating quality as a final gate and start using these practical, field-tested rituals to bake reliability into your product from the very first idea.
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Why AI Agents Need a Test Harness
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Joined AI Chapter chapter
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awarded Rahul Parwal for:
A tester’s guide to AI guardrails
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A tester’s guide to AI guardrails
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A tester’s guide to AI guardrails
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AI-driven testing in practice: from requirements to reliable automation
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See where AI genuinely helps, where it doesn’t, and how testers can stay firmly in control
awarded Damian Pereira for:
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Evals in practice for an AI coding agent
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Welcome to the MoTaverse 🎉
awarded Rahul Parwal for:
1.0.0 of A tester’s role in continuous quality
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1.0.0 of A tester’s role in continuous quality
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The Harness Era of QA Has Started
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Prompt engineering isn't the bottleneck anymore. Observability is.
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You're Not Ready For Quality Engineering with Callum Akehurst-Ryan
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Designing self‑explaining test automation for fast root‑cause diagnosis
registered for:
Learn how to get faster feedback, fewer blocked merges and better trust in automation.
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A tester’s guide to AI guardrails
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Identify, test and improve AI guardrails through a structured, scenario-based framework that addresses common implementation failures and attack patterns.
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Evals in practice for an AI coding agent
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Master this practical framework for building a layered evaluation strategy to systematically verify, secure, and improve the output quality of AI coding agents using both deterministic and model-grade
awarded Suryakanta Mohapatra for:
Vibe Coding for QA: Build a PRD-to-Test-Case Generator
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Vibe Coding for QA: Build a PRD-to-Test-Case Generator
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Hiren Shah
Team Lead
