Small Models, Clearer Products
The race for scale obscured a more useful question: how little intelligence does a great product actually need?
Scale is not a product strategy
The largest model is often the easiest choice to explain and the hardest one to sustain. Cost, latency, privacy, and reliability become product constraints long before a benchmark score becomes visible to a customer.
Designing around a narrow promise
Smaller models thrive when the job is explicit. Classification, extraction, routing, and constrained generation reward careful context more than unlimited parameters.
Evaluation is the real interface
A clear evaluation suite forces a team to define what good means. That definition becomes the product boundary—and often its greatest competitive advantage.
Intelligence should feel proportional
The future may belong to dozens of modest systems, each reliable enough to disappear into the work.
About the author
Theo Martins
Theo is a systems engineer interested in resilient infrastructure and humane tooling.
Staff Engineer
@theomartins
