Prompts & Graders

Manage AI prompts and graders in Statsig to evaluate, version, and roll out prompts in production without deploying code, similar to dynamic configs.

What is a prompt in Statsig?

A Prompt represents an LLM prompt or task in Statsig, along with its config. Prompts are similar to Dynamic Configs and let you evaluate and roll out prompts in production without deploying code. Use the Statsig Node or Python Server Core SDKs to retrieve a prompt within your app at runtime.

With Prompts, you can:

Manage prompt configuration outside of your application code. You can update the model, configuration, or prompt at runtime.
Allow teammates with access to Statsig to collaborate and iterate on prompts, benefiting from Statsig's production change control processes and versioning.
Add configuration for a new model or model provider and progressively shift production traffic to it while comparing costs, user satisfaction, or any metric of interest.
Support advanced use cases such as retrieval-augmented generation (RAG) and evaluation in production.

Prompt creation screen showing model selection and message list — Creating a prompt

Code example calling statsigAI.getPrompt to fetch live prompt version — Code snippet to retrieve the Live version of the prompt

Prompt results page summarizing grader scores per version — Looking at the scores for a prompt version

What is a grader?

A grader is the evaluation component that scores or judges the output of an AI system against a target standard.

The grader is the core evaluation unit in the workflow:

Inputs: The grader takes in the AI model’s response and, when available, the ideal or ground-truth answer.
Process: The grader applies a scoring method. This can be rule-based (exact string match, regex check, cosine similarity) or LLM-as-a-judge (using another model to evaluate correctness, relevance, style, or safety).
Outputs: The grader produces a score, ideally 0 (Fail) or 1 (Pass). This score feeds into the Statsig experiment or eval framework to determine performance across datasets, experiments, or model versions.

What is a critical grader?

A critical grader is a must-pass evaluation in Statsig AI Evals. If the AI output fails this grader, the entire run is marked as failed. A critical grader enforces non-negotiable requirements, acting as a hard gate before results are considered valid. When it doesn't fail, it acts like a normal grader.

Use Case

For example, in a financial support chatbot, a critical grader could check that the model never fabricates account balances. Even if the response is otherwise helpful, a single failure blocks the model from being promoted.

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