A lot of AI features ship because AI is expected, not because the job needs it, and the cost and complexity follow. The fix is to treat AI as a tool for a specific outcome, prove it earns its place, and scope the spend before you build.
Speculative vs strategic AI
Speculative AI is added to a roadmap to look modern. Strategic AI solves a defined user problem better than the alternative. Only the second kind is worth the ongoing token cost and maintenance.
Prove it before you commit
Test the prompt and model on real examples and estimate per-request cost at realistic volume before wiring it into production. Often a smaller model or a non-AI approach wins. Our AI build approach starts here.
Scope the cost, not just the feature
Estimate tokens, add caching and limits, and choose the model tier per task. Scoping cost as deliberately as functionality is what keeps an AI feature profitable at scale.