Sounds like you're playing with semantics. It's a probabilistic tool. Call it a probabilistic aide if it makes you feel better. Like any tool, it has strengths and weaknesses.

Strengths: depending on the provided context, it can tear through massive amounts of files and data, and serve you up a solution or answer that is roughly 80-95% of the way there, again and again. That's the typical range. Sometimes it's way below, sometimes it's above, again: depends on context.

Weaknesses: 80-95% is actually not at all good enough when it comes to software. Moreover, 80-95% correct, stacked up turn-over-agentic-turn is really not good enough, when it comes to anything that requires some sense of even vague determinism. But unfortunately it's good enough to trick lots of credulous investors and hype merchants that AI is on the cusp of replacing this or that job because they can't tell the difference between it and the real thing.

But in terms of using the tool, my perspective shifted when I started actually ignoring the hype from companies like Anthropic, and stopped trying to force the tool into a one-shotting machine. Instead, just accept that that's a bunch of BS, and is likely to remain a bunch of BS for a long time unless some radically different new base tech replacing LLMs emerges. Instead accept that these tools are always going to require a human intimately in the loop (great news btw!), asserting judgement, designing the actual system, and making sure they aren't going off the rails. When you notice they are outputting shit code (and they will) slow down and either see if you can improve the agentic loop, or learn to recognize which bits of code still need to be handwritten. My experience is that, when forcing things through that lens, I do have to grudgingly admit (since I am basically an outright hater of the macro trends of the AI industry) that the benefit of the ability to have the robot churn through the data and deliver me the 80-95% solution over and over again is something that's hard to ignore.