For ChatGPT-style development on OpenAI, the current platform centers on the Responses API. The basic workflow is straightforward: pick the right model, send the input, include clear instructions, and control the type of output you want back. That gives you a simpler starting point than trying to design a complex orchestration layer too early.
The best way to get started is to build one narrow flow first. Choose one task, one prompt pattern, and one output format. Once that works, expand into multi-turn behavior, tool use, or richer application features. Small starts make it easier to understand where formatting problems, prompt drift, or output handling issues are actually coming from.
If your API output will be pasted into email, docs, notes, forms, or another system, ask for that structure in the prompt. Plain text, short paragraphs, and minimal formatting are often easier to use downstream than highly structured output. The prompt should match the destination just as much as the task itself.
Return plain text with short paragraphs. No markdown, no bullets, and no extra headings. Keep the response easy to store, edit, or paste into another app.
Even with a clean API response, formatting still matters. The text may be correct but awkward once it moves into a ticket, spreadsheet, CMS field, or email editor. That is why output cleanup still belongs in the workflow, especially when generated content is reused across systems or copied by humans after generation.
Current OpenAI docs emphasize using the Responses API for modern multi-turn interactions, selecting a model that matches the task, and adding tools only when needed. The platform also supports richer response handling, but most developers still benefit from starting with a narrow text workflow first and growing from there.
OpenAI’s current platform centers on the Responses API for multi-turn model interactions and tool use. Developers choose a model, send input, and shape the response with instructions and output settings.
Start with a simple request, a clear prompt, a model choice that fits the task, and the output format you want back. Keep the first integration small before adding more complexity.
API output can still inherit formatting choices from prompts or downstream workflows. If the generated text is going into docs, forms, tickets, or email, cleanup can help remove line breaks, bullets, or formatting noise before final use.