Most AI API onboarding advice starts with model choice: pick a cheap model, pick a fast model, pick the newest model.
That is useful, but it skips the thing that actually proves your integration exists: can a brand-new project key make one boring request and leave an auditable log?
A practical first test looks like this:
- Create a project-scoped API key.
- Set only the base URL, key, and one model id.
- Send a tiny cURL request before touching your SDK, agent framework, or production app.
- Check the request log for the actual model, status, latency, token usage, and cost.
- Only then decide whether to test a paid model or move the same config into code.
This catches the unglamorous failures early: wrong Bearer header, old key from another gateway, copied model alias, missing /v1, client-side key exposure, or a request that returned HTTP 200 but was not actually usable.
At TackleKey we just tightened the first-run path around this exact step: after signup, the product now pushes new users toward creating a project key first, then running the current free first-call path before any larger payment decision.
If you are evaluating any OpenAI-compatible gateway, do not start with a spreadsheet of every model. Start with one project key and one observable request.
Try the 3-minute first-call path:
+https://tacklekey.com/start?utm_source=devto&utm_medium=content&utm_campaign=tacklekey-growth&utm_content=api-key-first-integration-test-20260706-v2
