Slides: How to build world-class AI products — Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust)

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How to build world-class AI products — Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust)

Relationship To World's Fair 2026

These slides are extracted from a public AI Engineer YouTube video connected to World's Fair 2026. Speaker-matched clips are supporting context unless later confirmed as exact session recordings; official livestream recordings are day-level/event-level source material.

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With Braintrust

1. Decide on an improvement

2. Curate targeted datasets (logs + handcrafted examples)

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Fast feedback for fast development

Modular stack enables rapid iteration and

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What is an Eval?

Definition: An Eval (short for evaluation) is a

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quality, reliability, and correctness across

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3 Ingredients in an Eval

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Datasets - Tips

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focus on building a feedback loop rather than

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Use Logs to capture more edge cases and

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use human review to establish ground truth

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Scorer Types

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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 it on the relevant

input and output for fair, consistent evaluation.

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