We’ve spent decades acting as “human compilers,” translating vague “vibes” from stakeholders into working code. Now, the hype around tools like OpenClaw is proving a hilarious point: AI doesn’t have a “coding problem,” it has a “human requirement problem.” I’ve been deep in the trenches with OpenClaw lately. It’s brilliant, but it’s also a mirror. If you give it a vague prompt, it just hallucinatingly burns through your resources. It’s only as good as the logic you feed it. AI is an incredible co-pilot, but it’s still just a machine that does exactly what it’s told—and humans are notoriously bad at telling machines what to do. The real shift isn’t that AI “knows” more; it’s that for the first time in history, clients and managers are being forced to be precise. If they can’t describe the logic to a GPT, they realize they don’t actually understand their own business process. The catch? This “precision” is expensive. OpenClaw is a token-hungry beast. To get anything meaningful done without hitting a wall, I’ve had to cycle through ChatGPT, Gemini, and Claude simultaneously just to keep the workflow moving. It’s a massive subscription drain. At the end of the day, we aren’t being replaced by “Silicon Brains.” We’re being replaced by the realization that 60% of our old jobs were just “professional mind-reading.” Now that the mind-reading has to be written down as a prompt, the theater is over. submitted by /u/Great-zh055
Originally posted by u/Great-zh055 on r/ArtificialInteligence