How to use
OpenAI API Platform.

1. 01

   Start at https://platform.openai.com/ and confirm the domain before entering account or payment information.

2. 02

   Availability: The OpenAI API Platform is managed through a browser dashboard and accessed from server applications through REST APIs and official SDKs; it is distinct from the ChatGPT consumer application.

3. 03

   An OpenAI API organization and project, server-side project credentials, billing and rate limits, approved data controls, a versioned model and prompt strategy, representative evals, safety controls, observability, and incident ownership.

4. 04

   Sign in with the account you intend to keep using, then review plan, data, notification, and permission settings.

5. 05

   Run one low-risk test task before connecting sensitive files, repositories, or workspace data.

• Use official download pages.
• Review permissions during setup.
• Keep installers and applications updated.

1. 01

   Define the user task, data classes, modalities, quality and safety metrics, latency, throughput, tools, retention, residency, cost, approvals, and rollback requirements.

2. 02

   Create a dedicated project and server-side key, review endpoint-specific data controls, choose a current model by measured task fit, and use the Responses API for new tool-using or multi-turn workflows.

3. 03

   Build a frozen eval set and run a bounded prototype with explicit model, instructions, output schema, storage choice, timeouts, retries, rate and token budgets, moderation, and request tracing.

4. 04

   Review evals, safety, tool authorization, privacy, failure behavior, latency, rate limits, and total task cost, then pin a snapshot where stability matters and canary with a tested fallback.

• State the outcome before the background.
• Provide the real source material.
• Review the result before expanding the task.

1. 01

   Restate the intended behaviour and the acceptance criteria before reading a single generated line.

2. 02

   Read the diff rather than the chat summary; the summary describes intent, the diff describes what actually changed.

3. 03

   Run the test suite, then write a test that would fail if the change were wrong, and confirm it passes for the right reason.

4. 04

   Check the edges the model tends to skip: error paths, null and empty cases, concurrency, and migration or rollback behaviour.

5. 05

   Trace every new dependency, network call, and file write, and confirm each one is genuinely required.

• Review the diff, never the description of the diff.
• A passing test suite proves the tests pass, not that the change is correct.
• Keep changes small enough that a human can actually review them.

1. 01

   Decide what the tool may read and what it may write before connecting a repository.

2. 02

   Scope tokens and integrations to the narrowest repository, branch, and permission set that still works.

3. 03

   Keep secrets out of the context window: use environment variables and secret stores, never inline credentials.

4. 04

   Require review before generated code touches authentication, payments, permissions, migrations, or deletion paths.

5. 05

   Audit what the integration retained after the session, and revoke access that is no longer needed.

• API data is not used for training by default unless the customer opts in, but abuse-monitoring logs and feature-specific application state may still be retained; endpoint eligibility differs for Zero Data Retention, residency, background mode, files, audio, video, search, and other tools. Keep keys server-side, separate projects, minimize and classify data, set store deliberately, pin and evaluate models, authorize tools outside the model, moderate inputs and outputs, log request IDs without content, and require approval for consequential actions.
• Follow your organisation's approved-use policy.
• Never treat fluent output as authorization to act.

• OpenAI developer quickstart ↗
• OpenAI model guidance ↗
• OpenAI data controls ↗
• OpenAI Evals API ↗

Working on something like this? See how we handle product engineering, or book a call.