See my later post in this thread, I go into more detail about how I use AI in the restorative process.
In addition, I literally had AI build a complete list of parts to order from Amazon down to the caps for each system I wanted to rebuild -- it was close to 20 different items, I would have probably given up if I had to try and assemble this list from different YouTube videos.
No, not everyone, there's no easily accessible video showing how to setup aquarium lights to slowly de-yellow ABS plastic -- at least I didn't find one; AI helped me find an obscure reference to it and I then read a few message boards where it was mentioned.
I also use AI to take in-progress pictures as I desolder to help me check for traces that need to be repaired or help identifying specific chips. I probably could try and find a video where the same chip is featured and someone explains it, and/or retrieve the schematic for the specific logic board, but that's very painful and does slow the process. Think of AI, in this specific case, as enabling skill development for me in a field I wouldn't have necessarily have gotten into, because of being short on time and AI helps me consolidate that information quickly.
For example: AI has helped me get into restoring retro tech, specifically resoldering leaky caps on retro Macintosh logic boards. Before AI, I didn't know how to use a multimeter (I knew theoretically how it worked), I didn't know how to use flux, solder wick, heat gun. I also didn't understand how bromine radicals yellowed plastic and how to reverse it by using blue light similar to what they use for indoor aquariums.
This is more accurate, I've written enough code in my life to never really want to do it again ....but I still love creating (code was merely the way to do it) so LLMs help with my underlying passion.
I don't find the same, like you, principle/CTO engineer, there's a world of difference between simplistic prompt/vibe coding and building a properly architected/performant/maintainable system with agentic coding.
That's great and I'm the same, 40s multiple founder and I was ready to hang it up after my last exit -- had 0 passion to code anymore and now I'm back and LLMs are reigniting my passion to create again.
Same, I have a bunch of skills defined ith proper YAML headers and semantic triggers installed, I make a point of listing not too many but making it quite specific.
Even with that, I have to be very specific in triggering a skill and it's hit or miss if it picks up on the skill -- usually I have to say there is a skill with this go and use it.
That's really interesting, I love the idea of being able to use columnar support directly within postgresql.
I was thinking of using Citus for this, but possibly using duckdb is a better way to do. Citus comes with a lot more out of the box but duckdb could be a good stepping stone.
In addition, I literally had AI build a complete list of parts to order from Amazon down to the caps for each system I wanted to rebuild -- it was close to 20 different items, I would have probably given up if I had to try and assemble this list from different YouTube videos.