The Quality Nervous System
The Quality Nervous System is a biologically inspired network where AI agents and humans operate symbiotically in a single adaptive system. AI agents continuously explore, learn, and execute in real time across software at machine speed, while humans provide the judgment, strategy, and purpose to assure outcomes align with user and business goals. AI partnering fundamentally changes how software is built. Humans now collaborate with systems that generate code, tests, insights, and behavior at unprecedented speed and volume. Continuous real-time results flood teams faster than they can interpret them, overwhelming quality engineers in a cycle that simply doesn’t scale. Fortunately, nature already solved this problem. Nervous systems handle massive sensory saturation through layered abstraction, specialization, and intelligent signal routing, all guided by intent. Software quality must adopt the same principles to stay effective in this new environment. This session explores how to design and orchestrate a Quality Nervous System in practice-applying abstraction to quality signals, directing AI agents by by domain and risk, preserving human intent at key decision points, and building feedback loops that respond at modern software speed. Attendees will leave with a practical mental model for building adaptive quality systems that evolve as quickly as the products they protect.
Kevin Pyles works for FamilySearch as an AI/ML SDET where he is testing test AI with AI. He has been in the QA industry now for over 18 years with project, product, and management roles throughout. Kevin worked previously for test.ai where he was the Head of Product. Kevin also served on the board for QA at the Point (a local testing meetup), and is an award-winning international speaker. Kevin enjoys golf, attending soccer games, and watching college football. He loves spending time with his family including his wife and 6 kids. He loves Brazilian food and pepperoni pizza, and can’t help himself when there is ice cream.