Slides: Evals 101 — Doug Guthrie, Braintrust
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Evals 101 — Doug Guthrie, Braintrust
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Extracted Slides

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Why evals? Evals help answer questions
Model selection How Gets Al Cost efficiency
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How evals can help your business
Cut dev time Rapid heraton cycies & local tested on multiple LLMs seamlessly
Reduce costs Autontated evals replace manuel review alowing faster eration ¢ release
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What is an Eval?
Definition: An Eval (short for evaluation) is a
structured test that checks how well your Al
system performs. It helps you measure
quality, reliability, and correctness across
scenarios.
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3 Ingredients in an Eval
DATASET SCORER
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Datasets - Tips
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BRAINTRUST.DEV
Scorer Types
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LLM-as-a-judgescorers
Exactorbinaryconditions
Subjectiveorcontextualfeedback
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Scorer Tips
Use a higher-quality model for scoring, even if the prompt uses a cheaper
model. Scorers benefit from better reasoning and nuance.
Treat scorers like judges: evaluate intent match, style accuracy, and
overall output quality: -not just correctness.
Break scoring into multiple focused scorers (e.g., accuracy, Creativity,
formatting) to pinpoint issues.
Test scorer prompts in the Playground before use. Try strong and weak
outputs to refine scoring reliability.
Avoid overloading the scorer prompt with context. Focus if on the relevant
input and output for fair, consistent evaluation.
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BRAINTRUST.DEV
Playgrounds
Experiments
Evaluations
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OCR text:
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app
choicescores:
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generate
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globals.css
ayout.tx
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page.tsx
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description: “Evaluates theaccuracy of a generatedcha
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content:
You are evaluating the accuracy of a changelog gemerated from aList of git commits.
Tsutils.ts
*TaskelRate how accurately the changelog represents the actual changes described in the conmits.
pubic
ProblemsOutputDebug ConsoleTerminalPorts
scripts
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env.localexample
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