The short answer
Latency shapes product behavior, user trust, and cost, so model selection should optimize for completed work rather than quality in isolation.
Every extra second changes what people do next. They abandon, retry, or stop trusting the system to be part of a fast workflow.
Quality matters, but so does the time from request to useful outcome. Smaller models, streaming, caching, and staged generation can all improve the loop.
A fast answer that needs heavy correction is not fast. Track time to accepted result, not only time to first token.
A useful note, once a week
Make room for better signal.
About the author
Rowan studies software tools and the operating habits that make them useful.
More from Rowan Singh →
A faster model can change the economics of a product. It does not, by itself, create a product people keep.
Memory is useful when it helps an agent make fewer repeated decisions without becoming impossible to inspect.
Model launches are becoming less like events and more like continuous product operations.
Keep the good stuff coming
One thoughtful note on AI, agents, and AGI. No noise.
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