LLM wrappers are essentially startups that wrap existing large language models, like Claude, GPT, or Gemini, with a product or UX layer to solve a specific problem. An example would be a startup that uses AI to helps students study. 'If you're really just counting on the back end model to do all the work and you're almost white-labeling that model, the industry doesn't have a lot of patience for that anymore,' Mowry said on this week's episode of Equity. 'You've got to have deep, wide moats that are either horizontally differentiated or something really specific to a vertical market' for a startup to 'progress and grow,' he said. Examples of the deep moat LLM wrapper type include Cursor, a GPT-powered coding assistant, or Harvey AI, a legal AI assistant. In other words, startups can no longer expect to slap a UI on top of a GPT and get traction on their product, like they could, perhaps, in mid-2024 when OpenAI launched its ChatGPT store. The challenge now is to build sustainable...
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