---
variant: detail
kind: inputs
slug: openai-evaluation-best-practices
url: /inputs/openai-evaluation-best-practices
title: Evaluation best practices
source_path: content/inputs/openai-evaluation-best-practices.md
frontmatter:
  title: Evaluation best practices
  url: 'https://developers.openai.com/api/docs/guides/evaluation-best-practices'
  source: OpenAI
  consumed: '2026-07-01T00:00:00.000Z'
  note: >-
    OpenAI's evaluation guidance emphasizes defining objectives, collecting
    task-relevant datasets, defining metrics, comparing runs, and continuously
    evaluating instead of relying on vibe-based assessment.
  tags:
    - openai
    - ai
    - evals
    - verification
agent_metadata:
  source_path: content/inputs/openai-evaluation-best-practices.md
  html_url: /inputs/openai-evaluation-best-practices
  markdown_url: /inputs/openai-evaluation-best-practices.md
  source_url: >-
    https://github.com/flaming-codes/thinkinglabs/blob/main/content/inputs/openai-evaluation-best-practices.md
  summary: >-
    The useful phrase for prompting disciplines is not in the wording of a
    prompt but in the discipline around it: success criteria, representative
    data, metrics, comparison, and continuous evaluation. That is the opposite
    of asking once and...
  word_count: 113
  approx_token_count: 239
  token_estimate: chars/4
---
The useful phrase for prompting disciplines is not in the wording of a prompt but in the discipline around it: success criteria, representative data, metrics, comparison, and continuous evaluation. That is the opposite of asking once and trusting the fluent answer.