Greg Isenberg frames agent-first software as a shift from selling a tool to selling a completed job. His starting point is a frequent, costly workflow with a clear finish line, existing software access, learnable exceptions and a buyer who already feels the loss when the work is missed.
Before building, Isenberg recommends observing a human across real cases and recording the trigger, required context, available tools, permitted actions, approval points, escalation rules and success condition. He argues that the detail inside edge cases is part of the product, not incidental implementation work.
The first version should remain bounded: draft and approve, triage, coordinate, or take one action under explicit rules. Logs, approvals, handoffs and a test set built from real examples create the control layer that lets customers evaluate the agent and lets the builder add autonomy only when results justify it.
Isenberg then proposes selling a narrow pilot to several customers in the same niche, learning where the workflow breaks and productizing only the repeated pattern. His pricing suggestions, distribution tactics and promotional references are presented as the creator's business advice rather than verified market forecasts, and the closing self-promotion is omitted.
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