Where Humans Belong In Agent Workflows
AI agents should not be supervised everywhere or trusted nowhere. The useful pattern is human checkpoints: clear places where judgment, risk, and publication decisions stay with you.
I write and teach how to build AI systems that expand human intelligence, creativity, and agency: memory, skills, workflows, and creative strategy.
AI agents should not be supervised everywhere or trusted nowhere. The useful pattern is human checkpoints: clear places where judgment, risk, and publication decisions stay with you.
A practical checkpoint model for agentic work: where to let agents run, where to stop them, and where human approval protects the whole workflow.
Readable AI text is not the same as good writing. The simplest fix is to separate the writer from the reviewer and let human judgment decide what survives.
A practical workflow for using AI as writer, reviewer, editor, and fact-checker without letting the whole process collapse into one generic draft.
A practical first step into agent workflows: create one focused Claude Project, give it clear instructions, and make it useful before adding more agents.
AI becomes more useful when it stops being one vague chatbot and starts becoming a set of clear roles, tools, and boundaries around your judgment.