Using lazy-loading for data in ChatGPT apps
Aggressively front-load data in ChatGPT apps instead of using traditional lazy-loading techniques.
Front-load aggressively by sending as much data as possible into the initial tool response and hydrating the widget via window.openai.toolOutput. This usually results in a faster, more responsive experience.
Defaulting to lazy-loading (fetching data when the user clicks, loading details on demand) in ChatGPT apps.
Tool calls in ChatGPT can involve delays of several seconds due to sandboxing and model reasoning. Front-loading data minimizes these delays by providing necessary information upfront.
Reverse the traditional lazy-loading paradigm in ChatGPT apps. Aggressively front-load data into the initial tool response and hydrate widgets directly, as tool calls can introduce significant delays.
- 15 lessons learned building ChatGPT Apps ↗OpenAI Developers Blog · OpenAI Developers Blog · Sep 3, 2026 · paraphrased
First seen on Subvolts Sep 3, 2026. Updated Sep 11, 2026. Spotted a problem? Tell us.
- 15 lessons learned building ChatGPT AppsOpenAI · OpenAI Developers Blog · Sep 3, 2026
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
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Questions people ask
- Which AI tools does this work with?
- The sources used it with ChatGPT.
- Where did this come from?
- OpenAI Developers Blog (OpenAI Developers Blog). Subvolts collected, normalized and credited it; the link above opens the original.