Jev: 8 real use cases for the fastest, cheapest model I’ve ever used | John Lindquist

Founder takeaway

A major drop in AI cost and latency can make previously uneconomic product ideas viable. Revisit workflows such as real-time classification, deduplication, and agent routing, then test whether faster, cheaper inference creates meaningful customer value rather than merely a novel demo.

Why it matters

Model economics shape product strategy. Lower per-task costs can support higher-frequency usage, real-time experiences, and experiments that were previously too expensive—potentially changing what you can offer and how you price it.

Relevant guides

Put it to work

List three customer workflows you previously rejected because AI was too slow or costly. For each, define a one-week prototype, the customer outcome it must improve, and the maximum inference cost that would support a sustainable margin.