I see a decent number of people on social media who won't stop posting about how great it is and how much of a moron every person is for not using it. Oddly enough, rarely, if ever do they say what specific things they're using it for and how it's saving them time. I remain interested in it, however, I've still awaiting an actual use case that can't be handled by some other tool/service that does it better/faster.
Could this be a bit of a Dropbox moment? What it adds is making this kind of thing easy for normies , even if it's neither the best way to do things nor very difficult for hobbyists to do using existing tech. Maybe it's the wrong approach, maybe what people really want is more deterministic software that they use agents to help write. But this kind of thing can maybe serve as a prototyping phase for that. Perhaps in…
My immediate reaction to anything someone says they're using OpenClaw for is "That's great, but it would have taken the same amount of effort to ask your LLM to write a script to do the same thing, which would be better in every possible way."
My approach to automation projects is just about the polar opposite of something like OpenClaw. How can I take this messy real-world thing and turn it into structured data? How can I build an API for the thing that doesn't have one? How can I define rules and configuration in a way that I can understand more about how something is working instead of less? How can I build a dashboard or other interface so I can see exactly the information I want to see instead of having to read a bunch of text?
It wasn't really until people started building things with coding assistants that I even saw the value in LLMs, because I realized they could speed up the rate at which I can build tools for my team to get things OUT of chat and INTO structured data with clean interfaces and deterministic behavior.