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frocodillo

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First of all, this is more than just note taking. It appears to be a (yet another) harness for coordinating work between agents with minimal human intervention. And as such, shouldn’t part of the point be to not have to build that mental model yourself, but rather offload it to the shared LLM “brain”?

Highly debatable whether it’s possible to create anything truly valuable (valuable for the owner of the product that is) with this approach, though. I’m not convinced that it will ever be possible to create valuable products from just a prompt and an agent harness. At that point, the product itself can be (re)created by anyone, product development has been commodified, and the only thing of value is tokens.

My hypothesis is that “do things that don’t scale”[0] will still apply well into the future, but the “things that don’t scale” will change.

All that said, I’ve finally started using Obsidian after setting up some skills for note taking, researching, linking, splitting, and restructuring the knowledge base. I’ve never been able to spend time on keeping it structured, but I now have a digital secretary that can do all of the work I’m too lazy to do. I can just jot down random thoughts and ideas, and the agent helps me structure it, ask follow-up questions, relate it to other ongoing work, and so on. I’m still putting in the work of reading sources and building a mental model, but I’m also getting high-quality notes almost for free.

[0] https://www.paulgraham.com/ds.html

Yes, definitely. Technique is partly about efficient mechanical movement, sending the various parts of your body in the right direction(s) and not waste effort on movement that doesn’t contribute to propelling you forwards. But for endurance sports, it’s really about minimizing energy cost at a given speed. To use running as an example, you can improve biomechanical efficiency through better timing, correct loading of tendons, tendon stiffness, elastic energy use, and more.

I find it interesting that this is the conclusion you draw from this. I won’t go into a discussion on the efficacy of the various mandates and policies in reducing spread of the disease. Rather, I think it’s worth pointing out that a significant portion of the proponents of these policies likely supported them not because of a desire to follow the authority but because they sincerely believed that a (for them) relatively small sacrifice in personal freedom could lead to improved outcomes for their fellow humans. For them, it was never about blindly following authority or virtue signalling. It was only ever about doing what they perceived as the right thing to do.

That’s already addressed in the article; it’s like paying off credit card debt with another credit card.

I guess it all depends on your end goal. If you intend to make your vibe coded app into a profitable, maintainable product with any sort of reliability guarantees you better understand its failure modes and how to fix things when they break. It’s really hard to create recovery procedures for a black box.

No one’s being forced, but we’re encouraged to explore and experiment with AI tools. And not just for writing code. It's a quite firm belief in the company as a whole that the winners in the 'AI age' will be the companies that are able to utilize AI tools improve their internal workflows and become more productive. So we get to try out lots of different things, and we make sure to share our learnings with each other.

I would argue that is a feature of pair programming, not a bug. By forcing you to use the slower I/O parts of your brain (and that of your partner) the process becomes more deliberate, allowing you to catch edge cases, bad design patterns, and would-be bugs before even putting pen to paper so to speak. Not to mention that it immediately reduces the bus factor by having two people with a good understanding of the code.

I’m not saying pair programming is a silver bullet, and I tend to agree that working on your own can be vastly more efficient. I do however think that it’s a very useful tool for critical functionality and hard problems and shouldn’t be dismissed.