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by unnouinceput
240 days ago
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Did you played Assassin's Creed Valhalla? In it there is a board game called Orlog. Go and make that game to be multiplayer so you can play with your spouse/son/friend. Come back to me once you're done and we see then how much time it took you. Or remake the Gwent board game that is in Witcher 3. Make either of that mobile game so you can enjoy in the same room with the person you love. Also make sure you can make multiple decks (for Gwent) / multiple starting God (for Orlog) and you just select the start and hit "ready to play" (or whatever). You'll know what I mean once you understand either of these games. Good luck with having any of them made in one session and not breaking the big picture in million of pieces and you keep the big picture in your head. |
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It sounds like you believe the hard part is decomposing problems - breaking them into subproblems, managing the "big picture," keeping the architecture in your head. That this is where experience and skill matter.
My mental model is the opposite: I see problem decomposition as the easy part - that's just reasoning about structure. You just keep peeling the onion until you hit algorithmically irreducible units. The hard part was always at the leaf nodes of that tree.
Why I think decomposition is straightforward:
People switch jobs and industries constantly. You move from one company to another, one domain to another, and you're productive quickly. How is that possible if decomposition requires deep domain expertise?
I think it's because decomposition is just observing how things fit together in reality. The structure reveals itself when you look at the problem.
Where I think the actual skill lived:
The leaf nodes. Not chipping away until you are left with "this is a min-cut problem" - anyone off the street can do that. The hard part was:
- Searching for the right algorithm/approach for your specific constraints
- Translating that solution into your project's specific variables, coordinate system, and bookkeeping
Those two things - search and translation - are precisely what AI excels at.
What I think AI changed:
I could walk into any building on Stanford campus right now, tap a random person (no CS required!) on the shoulder, and they could solve those leaf problems using AI tools. It no longer requires years of experience and learned skills.
I think this explains our different views: If you believe the skill is in decomposition (reasoning about structure), then AI hasn't changed much. But if the skill was always in search and translation at the leaf nodes (my view), then AI has eliminated the core barrier that required job-specific expertise.
Does this capture where we disagree? Am I understanding your position correctly?