"Wrapper apps build a custom software experience around an AI model(s). Think of these as traditional applications that use AI as their primary processing engine for most core tasks. These apps have a familiar user interface but their features use one or more AI models for processing user input, information retrieval, generating output, and more. With wrapper apps, you need to build the application's input and output capabilities, integrations, user interface, and how all these pieces and parts work with AI models."
"Embedded AI apps operate within existing AI clients like Claude.ai or ChatGPT. Rather than building a standalone experience, these apps leverage the host client for input, output, and tool capabilities, alongside a constantly growing list of integrations. To use concrete examples, if ChatGPT lets people to turn their conversation results into a podcast, your app's results can be turned into a podcast. With a wrapper app, you'd be building that capability yourself."
Two primary approaches to building AI applications exist: wrapper apps and embedded apps. Wrapper apps create a bespoke application interface that uses one or more AI models for core processing, requiring developers to implement input/output, integrations, and UI while enabling tailored experiences and visibility into user interactions. Embedded apps run inside host AI clients such as Claude.ai or ChatGPT and leverage the host's input/output, tools, and integrations, reducing the need to build features like podcast export or Google Drive access. Embedded apps trade custom control for faster access to host-provided capabilities.
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