wrapper
In plain wordsA product built mostly on top of someone else's AI model, adding a simple interface or a few instructions; often used as a put-down implying the product is easy to copy.
An application whose core capability comes from calling a third-party foundation modelfoundation model, n.: A very large AI model, built once at great cost from vast amounts of text, images or code gathered mostly from the internet, that many products then reuse as their starting point, from chatbots to coding tools. through a model APImodel API, n.: A web service through which programs send requests to an AI model run by a company and receive its answers, usually paying per use instead of running the model themselves., with the product contributing an interface, promptsprompt, n.: The message or instructions you give an AI system — a question, a request, some examples or a document — that it responds to. Clearer prompts generally get better results., integrations or workflow around it. 'Thin wrapper' is pejorative: it implies little defensible value, because the model provider or a competitor can replicate the feature, and because each new model release may absorb it outright — startups are said to be 'steamrolled' by an update. Defenders reply that nearly all software wraps something, and that the hard parts — distribution, proprietary data, evaluation, user experience and the surrounding harnessharness, n.: The software around an AI model that gives it instructions and tools, carries out its actions and decides when it stops. The model is the engine; the harness is the rest of the car. — are where durable value lies.
Investors kept calling us a GPT wrapper until they saw the retention numbers.
Origin
In programming, 'wrapper' has long meant code that encloses another component behind a new interface. The dismissive AI sense ('just a GPT wrapper') spread among investors and on social media in 2023, as thousands of startups were built on OpenAI's API in the months after ChatGPT's launch.
Usage note
Several fast-growing companies of 2024–2025, including the coding editor Cursor and the answer engine Perplexity, were widely dismissed as wrappers early on; the debate is really about where a moatmoat, n.: A lasting business advantage that keeps competitors out, like a castle's moat; in AI, the question of whether any company can stay ahead when rivals and free models catch up quickly. can come from.
Related
- moatmoat, n.: A lasting business advantage that keeps competitors out, like a castle's moat; in AI, the question of whether any company can stay ahead when rivals and free models catch up quickly.
- foundation modelfoundation model, n.: A very large AI model, built once at great cost from vast amounts of text, images or code gathered mostly from the internet, that many products then reuse as their starting point, from chatbots to coding tools.
- model APImodel API, n.: A web service through which programs send requests to an AI model run by a company and receive its answers, usually paying per use instead of running the model themselves.
- harnessharness, n.: The software around an AI model that gives it instructions and tools, carries out its actions and decides when it stops. The model is the engine; the harness is the rest of the car.
- AI-nativeAI-native, adj.: Describes a product, company or person built around AI from the start, rather than one that added AI features to older ways of working.
- GPU poorGPU poor, adj.: Slang for researchers, startups or countries without access to the huge numbers of expensive chips needed to build the most advanced AI, as opposed to the GPU-rich big labs.
Mentioned in
AI applicationAI application, n.: A program or product that uses AI to do something useful for people, such as a translation app, a medical-scan checker or a coding assistant., AI-nativeAI-native, adj.: Describes a product, company or person built around AI from the start, rather than one that added AI features to older ways of working., moatmoat, n.: A lasting business advantage that keeps competitors out, like a castle's moat; in AI, the question of whether any company can stay ahead when rivals and free models catch up quickly.