How I arrived here

To give some context to how I arrived at the experiment below: nowadays you’d be hard-pressed not to hear about the things AI is being used for — the most prominent in the recent news cycle being its applications in mathematics and decompilation. Hearing all this, I — like many others — thought something along the lines of: “If AI can do something as amazing as solving decades-old math problems or decompiling games in a day, it must be able to help me with [insert idea here]”, especially considering the alternative of just getting a job is seeming more and more questionable also due to the progress of AI. What then happens, at least in my experience, is that you try to implement your idea — hopefully a novel one — and find that AI seemingly isn’t as amazing as advertised, to the point you question how you have something that is simpler than a game or a centuries-old math problem, and yet the AI that does those amazing things can’t do the easy job you have for it. Which leaves you asking: what am I doing wrong? Is there some skill, harness or MCP I’m not aware of that makes these amazing things possible? But in your search for this golden bullet you will find that it doesn’t exist. You will eventually realize that if AI is not working for you, your task likely demands that AI work through its Achilles’ heels: novelty, ambiguity, memory, common sense, and most annoyingly, a severe propensity for dishonesty. And it makes sense: for a brute-forceable task like math or decompilation, none of those factor in — but for anyone who wants to use AI to “boost productivity” or do “real work”, these problems are everywhere.