Activity
Rosie Sherry
CEO & Founder at Ministry of Testing
She/Her
I've been working in the software testing and quality engineering space since the year 2000 whilst also combining it with my love for education and community. It turns out quality, community and education go nicely hand in hand.
🎓 MoT-STEC qualified
thanked contributors on:
So there it is. My first full calendar year as a freelancer. Of course, the bulk of my work has been for the Ministry of Testing on first the Software Testing Essentials Certificate (STEC, STEC, ST...
earned:
2025 Review
awarded Ady Stokes for:
2025 Review
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Definitions of Behaviour Driven Development (BDD)
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The "So What" Test
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This Year In Quality - Amazing Episode
awarded Andy Hinds for:
Thanks for upgrading, Merry Christmas! 🎅
awarded Kat Obring for:
1.3.0 of Quality Coaching essentials
awarded Callum Akehurst-Ryan for:
1.3.0 of Quality Coaching essentials
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1.3.0 of Quality Coaching essentials
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Not continuous everything!
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Chasing Predictability
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The Test Automation Graveyard
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The Vibium waiting game
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The dirty secrets of agile
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Reaction: Ensuring quality for a peculiar piece of software
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Prioritization First, Principles Second: An Adaptive Interpretation of Helpful, Honest, and Harmless Principles
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How to train helpful, honest, and harmless AI Learn how to implement a helpful, honest, and harmless model that meets standards through human-generated data in order to meet the needs of users and enterprises.
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Harmless, Honest, and Helpful AI: Aligning AI the Right Way
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RLHF for harmless, honest, and helpful AI
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A Decision Tree for Responsible AI Implementation Using the Harmless - Helpful - Honest Framework
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We need an adaptive interpretation of helpful, honest and harmless principles
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Tailoring AI Behavior to Context: Adaptive HHH Alignment
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Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback
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Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
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3 Hs for AI: Helpful, Honest, and Harmless
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A General Language Assistant as a Laboratory for Alignment
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Too Helpful, Too Harmless, Too Honest or Just Right?
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‘Helpful, Honest, Harmless’ AI
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Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback
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Developing LLMs that are helpful, truthful, and harmless
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