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Since early this year, I've had the fortune of speaking with many founders working on LLM-related tools that I'll broadly call "Prompt-Ops" tools. These tools are targeted at devs building products on top of LLMs, and aim to do any of the following: The best known example of this class of tool is LangChain, which does many, but not all, of the above. There are dozens more startups and open-source libraries trying to offer similar value propositions. I haven't really found any of them appealing enough to adopt, let alone pay for. I'm not yet sure if this is because this space is nascent and the founders don't know what problem they're solving, or because the use cases most familiar to me (research and potential adoption at work) aren't the ones targeted by these products. I do feel that most offerings in this space are built for side project builders and tinkerers rather than people building products with real users. Regardless, for the benefit of anyone thinking about building tools in

the stream 2023/2/28 1:58 There are so many "Prompt-Ops" tools and I'm sold on none of them Since early this year, I've had the fortune of speaking with many founders working on LLM-related tools that I'll broadly call "Prompt-Ops" tools. These tools are targeted at devs building products on top of LLMs, and aim to do any of the following: Proxy, log, and cache requests to LLM inference providers for cost savings and observability Provide a better UI to iterate on prompts Provide a simpler technical framework (utility library, web API wrapper) to call prompt chains as "LLM microservices" Help

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