I think I agree. I guess I don't know enough about chess to be sure, but the idea seems to be that although to novices a blindfolded player must reconstruct the board in his mind, that is not actually what is done by the expert.
That is something I can agree with, having spent a heck of a long time coding in the trading domain.
I've managed to vibe code a trading system. It's a hobby project directed on my phone on my commute, but it does do all the things I find important about trading systems. I can connect to external exchanges and see that I have sent valid orders, I get fills, and I can see debug logs of the timestamps. It doesn't allocate memory on the hot path, cores can be pinned, and so on. There are benchmarks that say how fast the code is parsing messages. It works.
So I've somehow built a thing that I've barely examined in the traditional sense, which nonetheless satisfies certain business needs for this hobby project.
How could that be? If you transported me back two years, I would know exactly where to make whatever changes you desired. I had the IDE open all the time, and I knew where things were. Now, I don't even know what the internal structure is like, I just know whether consideration has been made for some aspect of the system.
And I think this is what seems so baffling to a lot of people. How are software developers getting such different experiences with LLMs? Some people genuinely are producing things with incredible pace, while others find the AI just produces slop for them.
Some people are ready for the blindfold, but many are not. It's incredibly frustrating, especially if you are reasonably advanced but not yet at that overview stage.
That is something I can agree with, having spent a heck of a long time coding in the trading domain.
I've managed to vibe code a trading system. It's a hobby project directed on my phone on my commute, but it does do all the things I find important about trading systems. I can connect to external exchanges and see that I have sent valid orders, I get fills, and I can see debug logs of the timestamps. It doesn't allocate memory on the hot path, cores can be pinned, and so on. There are benchmarks that say how fast the code is parsing messages. It works.
So I've somehow built a thing that I've barely examined in the traditional sense, which nonetheless satisfies certain business needs for this hobby project.
How could that be? If you transported me back two years, I would know exactly where to make whatever changes you desired. I had the IDE open all the time, and I knew where things were. Now, I don't even know what the internal structure is like, I just know whether consideration has been made for some aspect of the system.
And I think this is what seems so baffling to a lot of people. How are software developers getting such different experiences with LLMs? Some people genuinely are producing things with incredible pace, while others find the AI just produces slop for them.
Some people are ready for the blindfold, but many are not. It's incredibly frustrating, especially if you are reasonably advanced but not yet at that overview stage.