Mastery: connect the pieces

1. Idea — Temperature reshapes how sharply a model samples next tokens. It does not add knowledge or guarantee truth.…
2. Mechanism — For logits z and temperature T, sampling uses softmax(z/T). Lower T concentrates on peaks; higher T admits tails; optional top-p/top-k truncate first.…
3. Controls — temperature, top-p, top-k, seed, n candidates, max tokens, schemas
4. Tradeoff — Low temperature improves consistency but can repeat bland or systematically wrong answers. High temperature produces diverse candidates but raises variance and …
5. Failures — Sticky wrong peak; Chaotic tails
6. Metrics — schema-valid rate, unique-acceptable names/20, review minutes, $/accepted output
7. Ship rule — T=0.2+schema for codes; T=0.8 n=20+lexicon for names; no shared creativity default.

Neighboring layers (retrieval, serving, policy, human review) still own what temperature sampling cannot on the country-code extraction and app-name ideation. Do not ask this chapter’s dial to replace permissions or source truth.

Mastery is transfer: take temperature sampling into a second scenario that is not the country-code extraction and app-name ideation and rebuild the checklist without copying sentences. If you can only recite this chapter’s examples for temperature sampling, you have memorized a story, not a model.

Also pin one numeric memory from this temperature sampling chapter: with logits [2,1], T=1 gives probabilities about [0.73,0.27]; T=0.5 gives [0.88,0.12], showing concentration rather than a linear creativity dial That number is not decoration; it is a template for how claims about temperature sampling on the country-code extraction and app-name ideation should look in design docs. Scoped specifically to temperature sampling / country-code extraction and app-name ideation / mastery-connect.

People confuse temperature sampling with neighboring buzzwords when debugging the country-code extraction and app-name ideation. Before changing prompts, ask whether the broken stage was evidence gathering, the temperature sampling judgment itself, validation, or the product action. Fixing the wrong stage creates folklore (“we tried temperature sampling and it failed”) that blocks the next team on the country-code extraction and app-name ideation. Scoped specifically to temperature sampling / country-code extraction and app-name ideation / mastery-connect.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to temperature creativity rather than generic AI advice.

Write a five-line artifact for this page: goal, inputs, check, owner, stop rule. Invent one fluent failure that the check would catch. Keep details specific to temperature creativity rather than generic AI advice.