Summary
Nate Herk, an AI automation consultant who left Goldman Sachs after graduating from the University of Iowa in 2024, presents a conference talk from the Workless AI event in Montenegro on the three most costly mistakes he made early in his AI agency — and how fixing them changed his business trajectory. The talk targets consultants, agency owners, and anyone building AI solutions for clients.
The three mistakes Herk identifies are: building solutions that don’t address the actual constraint in a client’s business (he built a viral personal assistant that wasn’t the bottleneck); failing to agree on a specific, measurable KPI before accepting payment; and guessing on pricing rather than tying fees to demonstrated, quantifiable value. His core framework shifts the consultant’s role from “ticket taker” (build what the client requests) to “diagnostician” (identify the real bottleneck) to “value prover” (show the business impact in numbers before collecting on long-term retainers).
The diagnostic method centers on two questions for business owners: for supply-constrained businesses, “If you had 10x the customers tomorrow, what would break first?” — and the inverse for demand-constrained ones. Herk argues that knowing when not to use AI is as strategically valuable as knowing when to use it, and that sustainable retainer relationships come from continuously identifying and solving the next constraint in a client’s business rather than delivering a single one-time automation build.
📺 Source: Nate Herk | AI Automation · Published August 25, 2026
🏷️ Format: Opinion Editorial
