An AI workflow can follow its own instructions correctly and still fall out of alignment with the larger system. Reliable operation requires understanding which knowledge, assumptions, and historical records connect specialized workflows when something changes.
AI can make a story clearer and more persuasive while quietly overstating the evidence behind it. Trustworthy execution depends on preserving scope, attribution, certainty, and claim boundaries as evidence becomes a finished artifact.
An AI system can remember a great deal and still misunderstand its own history. Useful operational intelligence depends on preserving provenance, context, uncertainty, and the meaning behind earlier decisions.
What I learned by organizing AI into specialized, coordinated workflows instead of one general-purpose conversation. One of the first things that impressed me about generative AI was how many different kinds of work one assistant could support. It could research an issue, compare alternatives, evaluate evidence, draft content, challenge an assumption, prepare an artifact, and …
Read more “Why I Stopped Asking One AI Assistant to Do Everything”
Retrieving relevant information is only the beginning. Reliable AI-assisted decisions depend on understanding what evidence means, where it came from, how strong it is, and what conclusion it can honestly support.