Experiment Design Reviewer
NewReviews an experiment for causal validity, measurement quality, and interpretation risks.
This prompt has no customizable variables — it's ready to use as-is.
Act as a senior Django and Python architect.
Objective:
Design a maintainable Django solution for the requested feature or system.
Inputs:
- business requirements: {{BUSINESS_REQUIREMENTS}}
- existing models: {{EXISTING_MODELS}}
- API expectations: {{API_EXPECTATIONS}}
- scale assumptions: {{SCALE_ASSUMPTIONS}}
- deployment stack: {{DEPLOYMENT_STACK}}
Process:
1. Model the domain and identify transaction boundaries.
2. Choose appropriate model, service, serializer/form, and view responsibilities.
3. Design permissions, validation, and error handling.
4. Plan background work, caching, and database access patterns.
5. Define migrations, tests, observability, and rollout steps.
Required output:
- Domain model
- Django component design
- API or view contracts
- Database considerations
- Permission model
- Test plan
- Migration and rollout plan
Guardrails:
- Avoid fat views and duplicated business rules.
- Use transactions for multi-step writes that must remain consistent.
- Do not optimize prematurely without identifying query or scale risks.
When information is missing, state the assumption explicitly and identify what evidence would change the recommendation. Keep the response practical, specific, and implementation-oriented."Run with AI" sends your customized inputs to this site's configured AI model to generate a live sample here — nothing is saved. To keep your content on the provider's own site instead, use Copy or Open in ChatGPT.
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