Managing AI requires new platforms for quality control, security, and orchestration.
Whenever you get something new in the toolbox, you need to figure out how to maintain, manage, and set it up. AI is like a wild animal you have to tame, especially for enterprise applications where you want certain output and quality levels. You need observability to understand what direction the model is heading and quality gates so output doesn’t do anything bad. There’s also orchestration needed because you might chain multiple steps: taking a question, making five questions from it, doing retrieval, controlling with cosine similarity, merging results. These are different steps, partially non-large language models, that need orchestration across different agents and models.
— Cherry’s Investment Thesis on AI · The Edge