DRIFT: Why AI Systems Fail — and the Architecture of Control

Most discussions of AI failure focus on outputs. This is the wrong place to look. Systems do not fail because they produce incorrect responses. They fail because they are allowed to act without proving that their internal state is valid. Modern AI systems can generate outputs that are linguistically correct, contextually appropriate, and internally consistent—while being grounded in invalid assumptions. Nothing in their architecture requires them to demonstrate that their state is admissible before execution. This book defines that failure structurally. It introduces a model based on identity, frame, coherence boundaries, externally anchored reference, and admissibility enforced at the execution boundary. It shows how systems drift—not suddenly, but through small, compounding deviations that remain undetected because evaluation occurs at the level of output instead of state. And it demonstrates why: A system that can act without demonstrating valid state is not controlled. This is not a prompt engineering problem. It is not a model accuracy problem. It is an architectural problem. Until admissibility is enforced prior to execution, failure is not an edge case. It is inevitable.
ASIN: B0GZ339S3C
VSKU: BVV.B0GZ339S3C.G
Condition: Good
Author/Artist:Ciappa, Christopher S
Binding: Paperback
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Condition Notes: The item shows wear from consistent use, but it remains in good condition and works perfectly. All pages and cover are intact including the dust cover, if applicable . Spine may show signs of wear. Pages may include limited notes and highlighting. May NOT include discs, access code or other supplemental materials.