How to Add AI to Your Product Without Wasting Budget
Treat AI as a feature with a job, not a slide. Where it pays off — and where it is theatre.
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Start with a boring job
The AI features that survive contact with users are rarely “chat with our brand.” They classify tickets, extract fields from documents, draft a first response, or rank what a human should look at next. Pick a repetitive, measurable task. Then wrap a model around it with a human in the loop.
If you cannot name the user, the input, and the decision the model helps with, you are not building AI. You are decorating a roadmap.
/ Dimitriy Caliber
Budget the unsexy parts
Model calls are not the expensive part. Prompt iteration, evaluation, fallbacks, logging, and the UI that lets a user correct a bad answer — that is the work. Plan for a thin slice in production, not a lab demo. If you cannot measure precision on real data in week two, pause the spend.
Keep the product honest
Do not ship medical, legal, or financial claims from a model without a review path. Users forgive a slow feature. They do not forgive confident nonsense. For health and regulated products, AI should assist a specialist, not impersonate one.
- What happens when the model is wrong?
- Who can override the output?
- Where is user data stored and for how long?
Ship a wedge, then expand
One reliable copilot inside an existing workflow beats a new “AI product” with no users. Once the wedge works, you have data, prompts, and trust. That is when a broader assistant becomes rational — not before.
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