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Joined 1 year ago
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Cake day: June 10th, 2023

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  • Kagi has good search results and they are presented well. It also has some useful features like forbidding certain sites and prioritizing others. I like that by paying I’m the customer and not the product. And their “small web” initiative is commendable.

    That said, I’ve been a customer for nine months on an annual subscription, and I will not be renewing. The first reason is that I find them just too expensive for what they do. The second is that, even being that expensive, they’re not breaking even. That undermines my trust in their future as a search engine and makes me less interested in paying a little extra for a good cause.



  • It’s wild that they are not breaking even with these prices. I’ve had an annual subscription since January and made nearly 5000 searches. Extrapolating to a year, I will have been paying about $0.17 per search. If that would go to the electricity bill then it corresponds to about 1 kWh of energy per search, enough to run a 50-watt laptop PC for 20 hours.






  • Only because bugs are defined as errors in implementation details. You can still have errors in your design (sometimes referred to as design bugs).

    It’s not about “entrusting” to AI any more than I would be entrusting important code to a junior developer to just go off and push to production on his own. We still have code review, pair programming etc. As I said, I read the output code, point out issues with it, and in the end make manual adjustments to fit what I want. It’s just a way of building up the bulk of the code more quickly and then you refine it.


  • I’ll confess I only skimmed the article, but it seems like just a bunch of unsubstantiated opinions and I don’t buy it.

    Using AI generated code is like pair programming with a junior programmer. You tell the junior what to do and then you correct their mistakes by telling them how to do better. In my experience, explaining things to someone else makes you better at your craft. Typically this cycle includes me changing the code manually at the end, and then possibly feeding it back to ChatGPT for another cycle of changes.

    Apart from letting me realize and test my ideas quicker, this allows me to raise the abstraction level of my thinking. I can spend more time on architecture and on seeing the bigger picture, and less time being blinded by the nitty gritty details. I would say it makes me both a faster and a better programmer.


  • I found that the most impractical thing with these was that the user interface for selecting songs was typically “you have 200 songs and I’m gonna play them in sequence, if you want a particular song you must skip ahead until you hear it”. It worked for a 12-track audio CD, but felt like an underdeveloped toy feature when used with MP3:s.