ChatGPT can now virtually try on clothes for you
- ID
- 30897
- Status
- summarized
- Published
- 02 Oct 2026, 3:21 AM
- Fetched
- 02 Oct 2026, 3:40 AM
- Provider
- TechCrunch
- Category
- technology
- Original URL
- https://techcrunch.com/2026/10/01/chatgpt-can-now-virtually-try-on-clothes-for-you/
- Source URL
- https://techcrunch.com/feed/
Summary
- Score
- 3.0
- Created
- 02 Oct 2026, 3:40 AM
- Tags
- Audience
- saas_foundersvibe_coders
What happened
OpenAI announced a global launch of two ChatGPT shopping features: a virtual try-on that lets users upload a selfie or full-body photo to see how a garment or accessory looks on them, surfaced via a new "try on" button in ChatGPT's shopping results, and Favorites, which saves products into an in-app Library alongside the try-on images. The features run on the newly launched ChatGPT Images 2.5 model, which OpenAI claims produces more natural lighting and richer textures, follows editing instructions more reliably, and cuts image generation latency. The article also notes OpenAI previously pulled back from an instant checkout feature that underperformed, and that agentic startup Instinct drew criticism for proactive product recommendations that users saw as ad-like.
Why it matters
This is a consumer shopping surface change, not a developer or API change — nothing in the text describes new endpoints, pricing, or SDKs, so most builders have no code action here. The one decision it informs is for anyone doing e-commerce discovery or affiliate/content commerce: product discovery and try-on imagery are moving inside the assistant via a "try on" button and a saved Favorites Library, which means your product images and catalog data are what get rendered by ChatGPT Images 2.5, not your own storefront page. If you are not in consumer commerce, the useful signal is the failure pattern: instant checkout underperformed and proactive recommendations were read as ads, so agentic commerce UX is still unresolved.
Discussion angle
OpenAI has now shipped try-on and Favorites but retreated from instant checkout, while Instinct's proactive recommendations were perceived as ads rather than help — which of those three is the actual failure mode for agentic commerce, and what would a Malaysian seller or commerce builder do differently because of it?