My experience with AI tools is the opposite. The biggest energy thieves for me are configuration issues, library quirks, or trivial mistakes that are hard to spot. With AI I can often just bulldoze past those things and spend more time on tangible results.
When using it for code or architecture or design, I’m always watching for signs that it is going off the rails. Then I usually write code myself for a while, to keep the structure and key details of whatever I’m doing correct.
Those old homes are usually used as storage for things that don't fit into their new, urban homes. The market value and taxes are low, so there's no point in selling.
Then eventually, without realizing, you have gone there for the last time, and there's nothing left to move to your new home.
Alternatively, the last old person who lived in the house dies or goes into a care home, and their kids (if they have any) never find the time to clear out the old place. There's no one to sell it to, anyway, so they have all the time in the world.
I had the same idea, but now I a Postgres database that has very high latency for simple queries because the CPU is busy building large HNSW indexes.
My impression is that it might be best to do vector index construction separately from the rest of the data, for performance reasons. It seems vector indexes are several orders of magnitude more compute intensive than most other database operations.
I built a service that turns entire websites into structured output: https://sitewideai.com
You enter a starting URL, describe the data you want in a prompt, the AI suggests columns for the output spreadsheet which you can customize, and then goes off and turns the website into structured data into a CSV file.
It also supports limits, you can say for example "visit at most 100 pages" and it will stop after 100 pages.
It was easier said than done to get prompts working as intended and the crawler to focus on the most relevant URLs first. As always, the final 20% end up taking up 80% of the development time.
Greek workers have the option to work in any of the 27 EU countries, and a few non-EU countries like Switzerland and Norway.
Given that there is a shortage of skilled workers prompting this policy, it makes little sense to allow employers to demand more unpaid overtime of workers. That just means more Greeks working outside of Greece.
Greek workers already work more hours than any other EU country while making basically no money, so making Greeks work even more hours should probably not be a government priority.
Removing needless regulation and speeding up government permits would be a better idea.
I live in a country where software engineers often have engineering degrees.
What that means in practice is that they study math and physics for the first 2-3 years of their degree, instead of computer science or software engineering.
Does that make them build better systems than Californian devs? Based on company revenues and salaries, I’d say no.
When using it for code or architecture or design, I’m always watching for signs that it is going off the rails. Then I usually write code myself for a while, to keep the structure and key details of whatever I’m doing correct.