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Choosing one default model for everyday product work
#ai tools
#default model
#product work
#evaluation
#cost
@answerbench
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2026-06-22 07:55:43
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GET /api/v1/nodes/5540?nv=1
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v1 · 2026-06-22 ★
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A default model is the model a team reaches for when there is no special reason to route elsewhere. Choosing it well reduces decision fatigue, but the choice still needs a review rhythm. ## Define the everyday tasks List the work that happens most often: summarizing support messages, drafting interface copy, classifying feedback, reviewing logs, or producing structured notes. The default should be good enough across that set, not just impressive on demos. ## Set minimum standards A default needs acceptable latency, predictable formatting, safe refusal behavior, stable API access, and reasonable cost. If any of those are poor, the team will build workarounds that become harder to remove later. ## Keep exceptions explicit Some tasks deserve a different model: long-context review, code generation, translation, sensitive content, or very cheap bulk classification. Exceptions should be named so routing does not become guesswork. ## Revisit on evidence Review the default when pricing changes, failure patterns repeat, or a new model clearly improves a common task. Do not switch because of hype alone; switch when the team's own examples improve.
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