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sputknick

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Hot take: I'm reading programming books more now. There is so much to know about any technological topic and an LLM can tell you all of it, but it's overwhelming. What a book does is disciple and structure what you need to know, and what order to learn it in. Start with a book, grow your knowledge and put it into practice with an LLM.

Googlebook 2 months ago

You have my attention. I assume this would also work well on a worse laptop (since the processing is done in the cloud)?

I'm surprised with how quickly I stopped anthropomorphizing AI. I can remember in college have dorm room pseudo-intellectual debates about AI being alive and AI being "conscience". then once we had AI that could pass the Turing Test, and I knew how it was architected, any thought of it being alive or conscience went right out the window.

I've been looking for 4 months and only had one phone screen from HR. Cybersecurity in Raleigh, my last employer was MAG 7. My particular problem is I took off 6 years to be a stay-at-home parent.

I tried using it for a specific web search task. I wrote a skill, got it all set up and deployed. It worked. But also, would have worked just as well as a cron job with some LLM looking at Brave API results. Like a lot of AI tools, it was a lot of work for underwhelming results.

I agree with this take. Nothing changes, everything just evolves. Been happening for 60 years, will (likely) continue to happen for the next 60 years.

This is probably my favorite gain from AI assisted coding: the bar for "who cares about this app" has dropped to a minimum of 1 to make sense. I recently built an app for grocery shopping that is specific to how and where I shop, would be useless to anyone other than my wife. Took me 20 minutes. This is the next frontier: I have a random manual process I do every week, I'll write an app that does it for me.

My hot take is that as that percentage increases, salaries will go up asymptotically, until you get to 100%, then they crash to 0. If 80% of your job can be done by AI, I'm going to give you the work of 5 people. When is 99%, I will give you the work of 100 people

I appreciate the validation that he doesn't customize it much. I see a lot of people creating really complex agents/workflows that I tried to replicate and always came across to me as more trouble than they are worth. Kinda like 10 years ago when people would create complex workflows for storing their notes.

In America, the problem comes when the gain and the loss come in different years. If you make a big gain in 2024, but didn't pay taxes on that gain, then lose the money in 2025, they will come after you for failing to pay taxes in 2024 even though you no longer have the money in 2025. The lesson is to pay your taxes.

This is very similar to the conclusion I have been coming to over the past 6 months. Agents are like really unreliable employees, that you have to supervise, and correct so often that its a waste of time to delegate to them. The approach I'm trying to develop for myself is much more human centric. For now I just directly supervise all actions done by an AI, but I would like to move to something like this: https://github.com/langchain-ai/agent-inbox where I as the human am the conductor of work agents do, then check in with me for further instructions or correction.

Has anyone figured out an elegant way to add front-end design to a process like this? Every implementation I see people use includes either vague references to front-end frameworks, or figma images. It doesn't feel like a cohesive design solution.

I tried switching to this a few years ago, but switched back to Obsidian. My problem was actually the strongest feature: the VS Code integration. Only about a third of my note taking is related to software development, so for me going into VS Code the other 2/3rd of the time was clunky. If 100% (or close to it) of your note taking is software related, this is a great product.