Page 4 of 8~96 min topic

Evals and benchmarks

Weigh the tradeoffs

Bigger suites cost more and stabilize estimates. Model judges scale and inherit biases. Public benchmarks aid comparison and risk train-set overlap.

~12 min this pageTradeoffs

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The live tension

Bigger suites cost more and stabilize estimates. Model judges scale and inherit biases. Public benchmarks aid comparison and risk train-set overlap.

Translate into user impact on the coding copilot when tuning evals and benchmarks. Which error class costs more—missed catches, slower answers, higher spend, or privacy exposure? That ranking picks the default more honestly than a blog’s recommended settings for evals and benchmarks.

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Numbers that force honesty

80/100 pass on unit-test tasks with 95% CI roughly ±4 pts—do not call a +2 pt vendor demo a revolution. Scoped specifically to evals and benchmarks / coding copilot / tradeoffs.

If the aggressive evals and benchmarks setting wins the headline metric while breaking a protected slice or blowing the latency budget on the coding copilot, it is not a win. Record intended gain and tolerated regression together for evals and benchmarks.

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Make it operational

Revisit the evals and benchmarks tradeoff when traffic shape changes on the coding copilot. A setting that was right at low volume can fail when a new language segment or document length appears. Tradeoffs expire; re-measure on a calendar, not only on incidents.

Also pin one numeric memory from this evals and benchmarks chapter: 80/100 pass on unit-test tasks with 95% CI roughly ±4 pts—do not call a +2 pt vendor demo a revolution. That number is not decoration; it is a template for how claims about evals and benchmarks on the coding copilot should look in design docs. Scoped specifically to evals and benchmarks / coding copilot / tradeoffs.

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Common mix-ups

People confuse evals and benchmarks with neighboring buzzwords when debugging the coding copilot. Before changing prompts, ask whether the broken stage was evidence gathering, the evals and benchmarks judgment itself, validation, or the product action. Fixing the wrong stage creates folklore (“we tried evals and benchmarks and it failed”) that blocks the next team on the coding copilot. Scoped specifically to evals and benchmarks / coding copilot / tradeoffs.

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Rehearsal (eval-and-benchmarks/tradeoffs)

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 eval and benchmarks rather than generic AI advice.

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Rehearsal (eval-and-benchmarks/tradeoffs)

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 eval and benchmarks rather than generic AI advice.

Read

Rehearsal (eval-and-benchmarks/tradeoffs)

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 eval and benchmarks rather than generic AI advice.

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Why this matters

For the coding copilot, name one regression you will tolerate when pursuing the main benefit of evals and benchmarks, and one regression that is stop-ship.

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Page assessment

Answer from memory. Completion is saved from this evidence, not from opening the next page.

1. What is one idea from this page you would apply, and what evidence would you check?

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