GPT API Quickstart: Build a Reliable Minimum Loop with OpenAI's Guide
Do not start with a complex agent. Secure the key, call the Responses API, handle failures, then add structured outputs and tools one layer at a time.
Open the official tutorialClose the request loop first
The value of OpenAI's quickstart is that it gets a model call working with very little code. The engineering rules are more important than the snippet: keep the key on the server, add timeouts and error handling, observe cost, and attach every request to a business operation.
```ts import OpenAI from "openai";
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY }); const response = await client.responses.create({ model: "gpt-4.1-mini", input: "Classify this buyer inquiry: Can you quote 500 units?", }); console.log(response.output_text); ```
Model IDs and SDK versions change, so follow the current OpenAI documentation when deploying.
From prose to a business output
Define a contract before giving the model freedom: for example intent, language, urgency, and draft_reply. Validate the result on the server. Structured output is not about pretty JSON; it makes downstream automation safe. A validation failure should go to review, not be sent automatically.
A maintainable prompt
Keep role and boundaries, task and input, output format, and failure behavior explicit. Put changing prices and policies in retrieval or a database instead of a permanent prompt.
Production checklist
- Keep keys, model configuration, and secrets out of browser code.
- Limit input length, sensitive data, and concurrency.
- Track latency, token usage, failures, and human edit rate.
- Route low-confidence or factual answers to review.
- Maintain a fixed evaluation set before changing models.
Official source: OpenAI Quickstart. This article is a learning path; current models, fields, and pricing belong to the official documentation.