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- Hacker News
- Is there anything new in this article? Yes, experts use AI better than non-experts for tasks in their domain. See LLMs reward expertise [1] and Terrance Taos conversation with LLM [2].
[1] https://www.seangoedecke.com/llms-reward-expertise/
[2] https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed...
by yellow_lead - If you can't look at the code, you need to trust interfaces to specify (and constrain) the implementation. The implementation needs to implement the entire interface and can't do anything not in the interface.
Otherwise, you're going to get bit by the Law of Leaky Abstractions.
The number of times I've been bit by systems not adhering to interfaces? Yeah, that's pretty frequent.
For example (from personal experience), the interface allows for race conditions, it's obvious they can happen (distributed systems), but the implementation didn't allow them, resulting in fun times.
by jpollock - Au contraire, playing blindfold is removing a tool, depending on nothing but your mind.
Vibe coding is the opposite, not just depending on the chessboard, but depending on a couple of Gflops to even think.
Blindfolded programming would be the programming we do in the shower
by TZubiri - > if a seasoned programmer sits behind Claude Code, the quality output will likely be higher than if a non technical person does it
Anecdotal: I recently rewrote a service in Rust for a much needed 100x performance boost (largely due to architectural changes, somewhat due to better runtime).
My colleague who now maintains the app is not a Rust developer and knows little about threads and tokio. Debugging a problem, he said he’d reach the context window before pinning the problem. I never have that problem and effortlessly find problems in the first 100k tokens without trying.
The difference must be in the wording that initially guides the agent.
by sshine - I really like this idea, because I think people forgetting that when you are writing code there exist a time T greater than zero, where you're not actually writing code and you're doing this thing called "thinking", ha ha. I find that there's a lot of times where I'm sitting staring at the screen and the lines of text sort of blur, and I'm in my head thinking about the connection of everything and not really worried about the actual implementation and how bites are moving, but wondering about the structure and the nature of the actual flow of the code. There's a wonderful XKCD about this, where a person sitting on a computer has this very beautiful stack of thoughts and clouds about what's being written, and then someone walks up to them and says something, and the entire cloud pops. If I understand this article, I think that's exactly a reasonable analogy to it. There is something that happens in the mind, and perhaps a neural weights, where the non-execution is where creativity and problem solving happening by mapping to the higher level concepts and stitching them together without having to specifically worry about the line level details. They still crop up, and implementation will probably always be king, But I do think I agree with this entirely!by tikimcfee
- Analogies work at an abstraction, and gotta take the chess analogy at its face value, as deeper people go into what's different between the chess and real life (deterministic vs non-deministic), one is not getting the lesson the author is presenting.
Remember, analogy is not territory. Every analogies fail at some point
by yipinwong - I do not think the metaphor can go very far. Have blindfolded chess become the "productivity trend" that every one should learn it to enjoy chess? Have normal chess players been replaced because skilled players can do blindfolded?by qbane
- I'm not completely convinced by this comparison between blind chess and prompting LLMs.
In blind chess you get deterministic information about the state of the board: each mental update to your board model can be precise, and you have the full state at every point in time.
LLMs are notoriously non-deterministic, and even at temperature zero you still can't predict exactly where the weights will take you next.
I suppose you can get closer to deterministic if you adopt a prompting style where you almost dictate every line of code, but at that point the coding agent is more of a typing assistant.
The productivity benefits of coding agents unlock themselves when you figure out how to turn short prompts - "add tests that exercise the registration form and check the happy path and all failure states" - into larger changes.
If you're completely blind to the results of those you're going to end up with a system you don't 100% understand very quickly. In blind chess terms you'll no longer know the positions of every piece on the board.
by simonw