I think it is an interesting question of what makes someone effective at using AI, which changes in what context you're in.

If you're at a small start-up and effective ai user looks different than one at an enterprise company, or hyper-scaler with infinite resources.

For me being effective at using AI, is as much the harness and workflows I built up alongside the services to support it, good ci, good tests, deployment pipelines and more. This allows us to streamline development and let the AI agents work much more autonomously, and in some cases even do automatic development and triaging.

Does that put me in 0.01% of spend, nope, but it makes me effective at my company and for personal development.

Depends on your use case, are you using it for building projects, research, or automation. But all of those fall into how you harness them and use efficiently without wasting millions of tokens, if you manage to do that while having quality outputs, as well as have it review things it makes, than you are doing good already.