OpenClaw is useful, but most of the pain people run into comes from letting one model do everything, chasing hype, or running expensive models in places that don't need them.
What worked for me was treating OpenClaw like infrastructure instead of a chatbot. Keep a cheap model as the coordinator, use agents for real work, be explicit about routing, and make memory and task state visible. Cheap models handle background work fine. Strong models are powerful when you call them intentionally instead of leaving them as defaults.
You don't need expensive hardware, and you don't need to host giant local models to get value out of this. Start small, get things stable before letting it run all the time, and avoid the hype train. If something feels broken, check the official docs and issues first. OpenClaw changes fast, and sometimes it really is just a bug.
