Start a Human-in-the-Loop AI Design Consultancy

1. 1

   Anchor on the transferable lesson from tax AI

   The tax vertical proved a broadly useful principle: in high-liability professional work, the AI vendors that win (Byron and Juno are the cited examples) explicitly preserve the human as the final decision-maker rather than chasing full autonomy, because a wrong autonomous output on a filed return, a legal filing, or a diagnosis carries liability no vendor can absorb. That principle is your product. You sell the judgment of where a human must stay in control and how to design the system around that.

2. 2

   Define the domains where autonomy is a liability trap

   Focus on high-liability, high-complexity professional services: tax, legal, medical, financial advice, and similar fields where a confident wrong answer causes real harm and real liability. In these domains, the question is not 'can we automate this' but 'where must a qualified human own the decision, and how does the AI make that human faster without taking the decision away.' Being the specialist in that specific question, across regulated domains, is the positioning.

3. 3

   Build a design methodology, not opinions

   Your deliverable should be a repeatable method: how to map a workflow into what AI proposes versus what a human decides, where to insert review and escalation, how to surface the AI's reasoning so the human verifies rather than rubber-stamps, how to cross-verify (for example with multiple models), and how to build audit trails for liability. A documented methodology is more sellable and more defensible than case-by-case advice, and it compounds across engagements.

4. 4

   Sell to teams building AI in regulated fields

   Your clients are the companies and firms building or buying AI for high-liability domains: fintechs, legal-tech and health-tech teams, professional-services firms, and enterprises. They feel the liability risk but often lack the specific human-in-the-loop design expertise. Reach them through content that demonstrates the principle, referrals from the regulated industries you know, and a clear promise: an AI system that is genuinely useful and does not bet the business on autonomous output.

5. 5

   Price as premium expert advisory and carry insurance

   This is high-stakes design advice, so price it as premium expert consulting (retainers or project fees), not commodity hours. Because your guidance shapes systems that carry real liability, carry your own professional liability insurance and scope your engagements clearly in writing. The value you deliver, keeping a client on the right side of the liability line while still shipping useful AI, justifies premium rates and produces the referrals that grow the practice.

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