It could have taken you years to realize that "oh I'm just exploring stuff and have no output".

Set an ambitious goal that is achievable using Claude Code, and focus on delivering it. Even if it doesn't turn out to be a hit, the experience of releasing it and using AI to accelerate it, will be a talking point to your 10-year-older self.

SKG is an initiative that will force game publishers to keep a game online, provided that people have paid for it, and the publisher is not bankrupt? Is that right? What does it have to do with democracy?

Again maybe you are aware, but it wasn't clear from your post.

If you’re writing novel algorithms all day, then I get your point. But are you? Or have you ever delegated work? If you find the AI losing its train of thought all it takes is to try again with better high level instructions.

So the options are to 1. Code React all day and be happy with it. 2. Come up with reasons why it's bad.

There are many talented and intellectually curious people in the field which lean towards 2.

It is this rather than docs. I think you're absolutely right about our lack of documentation handicapping AI agents.

For personal projects on the other hand, it has expedited me what? 10x, 30x? It's not measurable. My output has been so much more than what would have been possible earlier, that there is no benchmark because these level of projects would not have been getting completed in the first place.

Back to using at work: I think it's a skill issue. Both on my end and yours. We haven't found a way to encode our domain knowledge into AI and transcend into orchestrators of that AI.

:)

The issue is that you're not acknowledging or replying to people's explanations for _why_ they see this as exponential growth. It's almost as if you skimmed through the meat of the comment and then just re-phrased your original idea.

> When Fernando Alonso (best rookie btw) goes from 0-60 in 2.4 seconds in his Aston Martin, is it reasonable to assume he will near the speed of light in 20 seconds?

This comparison doesn't make sense because we know the limits of cars but we don't yet know the limits of LLMs. It's an open question. Whether or not an F1 engine can make it the speed of light in 20 seconds is not an open question.

Introduction to quantitative finance and to learn what strategies are used by firms who are supposed to beat the market.

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Deep dive into ML techniques if you want to start making money from data and math.