I have been seeing this a lot in AI communities — someone asks about building something and the response is either just prompt ChatGPT or just use the API and build it properly. like those are the only two options.been building stuff seriously for about a year and I think there’s a genuinely underappreciated middle layer that’s gotten good enough to matter.was working on something recently that needed multi-step processing — basically intake, classification, contextual retrieval, then generation with specific formatting rules depending on what the classification step returned. the kind of conditional logic that breaks immediately if you try to do it in one prompt but also felt like overkill to spin up a whole dev environment for.built it in MindStudio. the workflow has like 8 steps, different models handling different parts of it, conditional branching based on outputs. it’s been running reliably for a couple months now. if I’d waited until I had the bandwidth to build it properly in code it still wouldn’t exist.the part that actually interests me is what this means for how AI capabilities get applied in the real world. a lot of the most interesting use cases aren’t going to be built by ML engineers. they’re going to be built by people who understand a specific domain really well and need tooling that lets them express logic without a CS background being the bottleneck.feels like we’re pretty early in figuring out what that layer actually looks like and what its real limits are. curious what others think — is the no-code AI builder category actually maturing into something serious or is it a stepping stone that gets abandoned once someone learns to code submitted by /u/ermwhatthesigma_10
Originally posted by u/ermwhatthesigma_10 on r/ArtificialInteligence