90% of AI companies are just thin layers on top of an LLM, sometimes useful but they have all the problems LLM have (I will explain) For existing companies wit

90% of AI companies are just thin layers on top of an LLM, sometimes useful but they have all the problems LLM have (I will explain) For existing companies with AI features: more useful but mostly LLM bolted on with the same use cases. They can improve the product if used right. But for me it’s mostly often just a gimmick. The problem with LLMs: They mostly generate stuff they have seen and are bad as truly new stuff. They make mistakes You need to put time and energy in the review it. For stuff that transforms data it’s useful. Like rewriting a piece of text. It’s also useful for search queries on the corpus the LLM is trained on. It’s good at pattern recognition and lastly: human like voice interfaces. But for generating novel stuff: good luck reviewing it. People who just blindly copy paste the output of an LLM: that’s quite dangerous and potentially plain wrong. At least that’s my experience.