101–110 of 129 posts
I don't get the second brain thing. I don't keep a second brain, I just read and think a lot. I once did a physics masters and, when asked how to make steady progress, one of the professors (who had published with Paul Dirac no less) made the comment "well, my secret is that I think about physics all the time" I started practicing this for the stuff I'm interested in ... and the result is that I generate a lot of ide…
I don't get the second brain thing. I don't keep a second brain, I just read and think a lot. I once did a physics masters and, when asked how to make steady progress, one of the professors (who had published with Paul Dirac no less) made the comment "well, my secret is that I think about physics all the time" I started practicing this for the stuff I'm interested in ... and the result is that I generate a lot of ide…
The whole idea of second brain is simply cringe. I know using this word itself is cringe but it's the most accurate one for how I feel. While it doesn't necessarily have anything to do with AI, the trend of glue AI onto everything certainly didn't help. For you guys' 5 min of entertainment: https://youtu.be/6NukGtwJb7Y?t=256
As Claude said to me when I said the same thing - it's not really its idea you had to ask the right questions. I find this true in some ways - asking the right question and finding out what the AI's have hidden inside them is like panning for gold imho.
LLMs don't have sense experience, so it doesn't have real reasons to prefer one option over another when nothing has been specified in the prompt. It can only guess based on what's most represented in its training. "Ideas" are only being simulated by an RNG; the AI can "suggest" (output) them, but they don't "have" the idea either.
If you couldn't make the decision yourself in the first place, pulling a slip of paper out of the hat only helps in the cases where the choice really didn't matter at all. Otherwise you'll look at it, frown, and still feel stuck.
I have this problem even in codebases. Claude will work on something, and add detailed comments in which it extrapolates the from the design and confidently states intentions and decisions which aren't actually grounded in reality. Then, later sessions suffer when it reads back those hallucinations and treats them as canonical.
Delete the comments: I’ve gone on a tear with these recently because they’re nothing but trouble. The absolute least worst outcome is they chew up your token budget. But what tends to happen, and this is much more serious, is they poison future work and make further modification of the codebase more burdensome and error prone.
Agreed.
Probably better to add whatever instructions it takes so that the agent doesn't write comments, at all, ever. If you need comments to understand the agent's code, the necessary information should already be in a conversation somewhere; and you should summarize it yourself, because the comment will be for your own benefit. Otherwise you are letting past-agent steer future-agent more or less at random.
I keep two separate vaults. It's a pain but no ai writing should mix with my own. Otherwise how can I differentiate my discoveries from its
Earlier quoted context omitted.
Delete the comments: I’ve gone on a tear with these recently because they’re nothing but trouble. The absolute least worst outcome is they chew up your token budget. But what tends to happen, and this is much more serious, is they poison future work and make further modification of the codebase more burdensome and error prone.
I completely block all LLM comments via pi extension, it makes using them significantly more enjoyable. If the LLM wants to add a comment it must ASK me explicitly to do so. Seeing LLM comments in other peoples code is very upsetting because theres just so much meaningless noise.
what happened to ideas are cheap - execution is everything. As Claude said to me when I said the same thing - it's not really its idea you had to ask the right questions. I find this true in some ways - asking the right question and finding out what the AI's have hidden inside them is like panning for gold imho.
It used to be that we only recognized a tiny fraction of the actual ideas involved, because most of them were intermingled with execution. We would sit there and bang out code at single-digit WPM while trying to keep block diagrams of process memory (or UML diagrams, or whatever else) in our heads, and then run the compiler and/or the tests and realize we'd gone wrong anyway.
Now we have lightning-fast "execution" devoid of real insight (just making choices more or less arbitrarily as they come up) because the LLM can do more and more without human intervention, but for some tasks it goes off the rails because the insight actually is necessary.
It used to be a mess, but with OKF (Open Knowledge Format), things are more manageable and navigatable (for me as well).
Consider AI vault as a scratch pad that AIs use, not as something you put your own thought into it.