I totally agree with this. I have been arguing with folks that current Reactflow based agent workflow tools are destined to fail, and more importantly, missing the point. Stop forcing AI into structured work.
I do think AI "agents" (or blocks as I like to think of them) unlock the potential for solving unstructured but well-scoped tasks. But it is a block of unstructured work that is very unique to a problem, and you are very likely to not find another problem where that block fits. So, trying to productize these AI blocks as re-usable agents is not that great of a value prop. And building a node based workflow tool is even less of a value prop.
However, if you can flip it inside out and build an AI agent that takes a question and outputs a node based workflow. But the blocks in the workflow are structured pre-defined blocks with deterministic inputs and outputs, or a custom AI block that you yourself built, then that is something I can find value in. This is almost like the function calling capabilities of GPT.
Building these block reminds me of the early days of cloud computing. Back then the patterns for high availability were not well-established and people that were sold on the scalability aspects of cloud computing and got onboard without accounting for service failure/availability scenarios and the ephemeral nature of EC2 instances were left burned, complaining about the unfeasibility of cloud computing.
> AI agent that takes a question and outputs a node based workflow
That rings useful to me. I find it hard to trust an AI black box to output a good result, especially chained in a sequence of blocks. They may accumulate error.
But AIs are great recommender systems. If it can output a sequence of blocks that are fully deterministic, I can run the sequence once, see it outputs a good result and trust it to output a good result in the future given I more or less understand what each individual box does. There may still be edge cases, and maybe the AI can also suggest when the workflow breaks, but at least I know it outputs the same result given the same input.
I do think AI "agents" (or blocks as I like to think of them) unlock the potential for solving unstructured but well-scoped tasks. But it is a block of unstructured work that is very unique to a problem, and you are very likely to not find another problem where that block fits. So, trying to productize these AI blocks as re-usable agents is not that great of a value prop. And building a node based workflow tool is even less of a value prop.
However, if you can flip it inside out and build an AI agent that takes a question and outputs a node based workflow. But the blocks in the workflow are structured pre-defined blocks with deterministic inputs and outputs, or a custom AI block that you yourself built, then that is something I can find value in. This is almost like the function calling capabilities of GPT.
Building these block reminds me of the early days of cloud computing. Back then the patterns for high availability were not well-established and people that were sold on the scalability aspects of cloud computing and got onboard without accounting for service failure/availability scenarios and the ephemeral nature of EC2 instances were left burned, complaining about the unfeasibility of cloud computing.