ochronus

Is that a problem?

Nicely done! And yes, I'd love to see it open sourced.

As much as Micro$oft is ... subpar, .NET never fails to amaze in the last couple of years. Kudos to the team.

Immich is wonderful, but if you're mostly looking for a solution to take your mind off the problem and don't want to self-host, try Ente photos.

Ugh, I see "future" and "meta" in the same sentence, hard nope

The author is conflating coding with other parts of the sw engineer role.

Yup, if you know what to point it at - where does _that_ skill come from? Experience.

Wherever I worked (and as long as it was up to me), the mindset and expectation was that a junior we hire will need to become a medior in max 2 years. Of course, we provided the right investment (environment, mentorship, coaching, learning budget). This also acted as a filter at hiring. This way the question was never "for today's tasks do we need a senior OR a junior".

About AI: Unless there's another breakthrough, AI is not getting significantly better. A junior with 2 years of proper training easily surpasses AI in judgment and arch design skills, etc. - and you will need seasoned engineers to make the calls and shepherd AI even. Where will those people come from if nobody is investing in juniors?

If you do your hiring (and then mentorship) right, even such juniors can skyrocket in 1-2 years. AI won't do that. So, in case of willing juniors, you get much, much more "out of them" soon, if you invest a little. They will be able to tackle problems you can't solve by "throwing more AI at it"

Huh? How so? Please add some sources

Nope, it's the lawyer firms that come after you. Google removes reviews on request for its own comfort, but if you provide proof, they put it back. Then the lawyers come.

This is lovely

No, no, much better: make it a SKILL.md ;)

I think Liquid Glass is a general UX/Product blunder, not a deliberate evil masterplan to force users to buy new phones.

Doesn't match my personal experience over a handful of iPhone generations. I know, anecdotal only, but still.

I see your point, but I'd be surprised if they'd lose a significant user base in the end; the hype is just way too high

I don't think they are clueless, but rather, struggling. Being an AI provider is a money burner, and they probably don't have enough fuel for the fire anymore, so they are trying things to squeeze more $$$ and limit usage at the same time.

Yes, it's related to the limits of the subscription plans. 2ish months ago the same sub started hitting limits earlier and earlier on very similar tasks/codebases. Then they said, Oh, sorry, it was a caching bug, now it's fixed. It wasn't. Then a couple more bugs. Still no fix. Recently they announced "doubling the limits" (made possible by the Grok deal) - still hitting limits super fast compared to how it used to be 2+ months ago. Moreover, the models got somewhat dumber and slower, too.

Yeah, claude code is mostly unusable at this point. It's been in a constant decline for a good 1-2 months. It's more like a scam now.

Hence the only other path: slow, constant enshittification of the models' performance

As predicted by many. The math is, as usual, mathing.

No, it's not, except for a small percentage of the userbase.

Haha, right, just like the recent uncommunicated changes to limits, cache, etc.

This is awesome! Thank you for building it!

Hmm, the bug I hit lasted for days and burned through my credits/limits/tokens like crazy, consistently. It's gone after the last update.

No, I think they mean:

- https://www.reddit.com/r/ClaudeAI/comments/1s7mkn3/psa_claud...

- https://www.reddit.com/r/ClaudeAI/comments/1s7zgj0/comment/o...

Ok, so this is how they try to compensate for their messed up month of bugs (insane token burn)

Really cool :)

Of course, this is still considering the current model of working. Which in itself is a question.

This discussion feels analogous to me to the age-old "we can do it fast now, and do it right later" tradeoff discussion, except now it's about knowledge, maintainability etc.. There are stages of companies and types of products where solution quality has a bigger buffer, some are more critical. We also know that in many places, once you shipped a crappy solution in a week, you've now set an expectation, and management will expect you do repeat that forever, not getting the time to actually fix/rearchitect when needed.

We used to brush that off with the "we'll fix all of that once we've shipped", now we brush it off with "doesn't matter, AI can fix it later easily". This applies to knowledge about the code, domains and quality itself, too.

To me, this is a reasonable tradeoff to discuss, and sticking to either extreme ("AI is cancer" and "AI is the silver bullet") feels silly.

There's real risk here, and I do see a lot of seniors act like kids in the candy store. That speaks volumes to what AI really unlocks (cheap experimentation, for one!), but also warrants caution.

Based on the data (not great quality tbh...) we have, the net speedup is more realistically around 5-10% of the total time of software engineers, and we're yet to see the cost of that speedup.