Latest Issue
Agents Are Only as Good as the User
Most bad agent output does not start with the model. A lot of it starts with unclear work: vague jobs, missing context, no rules, no approval point, and no definition of done.
FlowState Notes · Practical AI Workflows
Notes on Useful AI
A short, operator-written newsletter about where AI belongs, where it does not, and how agentic workflows move real work from open loop to closed loop.
Education first
Hype last
Published by FlowState
Hype last
Published by FlowState
Clear Opinions
Plain-English judgment on what agentic AI is actually good for, without pretending every business problem needs an agent.
Useful Examples
Real operating loops: follow-up, intake, scheduling, reporting, research, QA, CRM cleanup, and the handoffs people keep dropping.
Healthy Skepticism
Sources, counterpoints, and reminders that good AI systems need context, tools, review, fallback paths, and ownership.
Archive
Agents Are Only as Good as the User
A practical check on why agents need clear jobs, context, boundaries, approval gates, and a definition of done.
Chatbot Does Not Equal Agentic AI
A practical reset on why a chatbot answer is not the same as a workflow that closes the loop.