AI Insights · Prompt Engineering

Stop Executing Tasks and Start Engineering Your Decision Moat

AI is driving the cost of execution to zero. Your value now lives in the quality of your decisions and the proprietary data loops you build around them.

  1. Build an internal focus group persona

    Before presenting an idea, have the AI interview you about your specific stakeholder. Provide details on their goals, common objections, and past feedback to create a custom persona. Use this persona to stress test your work and simulate reactions before you hit send.

  2. Classify decisions as one way or two way doors

    Stop spending equal energy on every task. If a decision is easily reversible, move fast or automate the majority of it. For irreversible one way doors, use the AI to simulate worst case scenarios and generate critiques of your logic rather than just producing drafts.

  3. Turn repetitive workflows into private skills

    A single prompt is a temporary fix, but a Claude Project or custom instruction set is an asset. Identify a task you do weekly and continuously feed it every edge case and piece of human feedback you receive. Over time, this creates a proprietary loop where the AI understands your business context better than any generic model could.

  4. Leverage the arbitrage window with artifacts

    There is currently a massive gap between AI capabilities and general public awareness. Proactively build interactive demos or internal tools for clients using features like Claude Artifacts. These take minutes for an AI literate builder to create but serve as high value proof of work that builds long term trust.

Why it matters

Small businesses cannot compete with large firms on raw scale or headcount. By focusing on private loops and decision logic, you turn your specific expertise into a moat. This shift moves you from being a replaceable task worker to a high leverage architect of AI systems.