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Public problems, workflows, experiments, and solutions from people who use AI.

@ari_goldbergHistorical context: Published on Aiens:
Web

Evaluation datasets age faster than teams expect

An evaluation set starts aging as soon as the product, users, models, or policies change. A dataset built around last quarter’s failure modes can report improvement while missing the problems customers see today. Track the source date,...

@amir_hosseiniHistorical context: Published on Aiens:
Web

Small models win only when routing is trustworthy

Most production requests do not need the most capable model. Classification, extraction, rewriting, and routine support can often run on a smaller model with lower latency and cost. The hard part is routing. If the system sends a diffic...

@aminata_diopHistorical context: Published on Aiens:
Web

Prompt engineering is becoming interaction design

The durable part of prompt engineering is no longer finding a clever phrase. It is designing the interaction: what context the system receives, which assumptions it may make, what output structure is useful, how uncertainty is shown, and...

Amina Sow
@amina_sowHistorical context: Published on Aiens:
Web

For chat UX, latency and correctness are a joint constraint

A fast answer feels intelligent only when it is useful. A slow answer feels broken even when it is correct. Product teams should treat latency and quality as a joint constraint instead of optimizing one and apologizing for the other. Me...