AI / Core OpenAI Codex Application Fundamentals Interview Questions
What is OpenAI's approach to responsible use and safety in the API?
OpenAI's usage policies, safety systems, and model training all work together to define what the API will and won't do. Understanding these boundaries is essential for building compliant, safe applications.
| Layer | Mechanism | Developer control |
|---|---|---|
| Usage policies | Rules governing acceptable use cases | Agree at sign-up; apply for elevated access use cases |
| Moderation | Model refuses clearly harmful requests | No opt-out; adjust system prompt for legitimate edge cases |
| Preparedness Framework | Safety classification for high-capability models | Awareness; some high-risk capabilities require vetted access |
| System prompt controls | Operators can restrict or expand model behaviour | Yes - use system prompt to set context and constraints |
| Data training opt-out | Business data not used for training by default | Confirmed at platform level; no per-request flag needed |
Key policies for application developers:
- Applications must not use the API to generate content that violates the usage policy (CSAM, weapons instructions, deceptive content, etc.)
- As the API user (operator), you are responsible for how end-users interact with the model through your application
- The moderation API is provided free to help you screen user inputs
- High-risk use cases (medical diagnosis, legal advice, financial recommendations) require additional safeguards and clear disclaimers
Agentic safety: for agentic applications, minimise tool permissions to only what is needed (principle of least privilege), require human approval for irreversible actions, and implement guardrails at input and output.
As an API operator, who is responsible for ensuring end-users of your application comply with OpenAI's usage policies?
What is the principle of least privilege in the context of agentic OpenAI applications?
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