username_my1

yes and no, because you now keep using AI and AI doesn't care if it has seen the code or not before and you just keep fixing bugs / adding features without really understanding the code.

it's weird new reality, but if it works it works I guess. I'm still waiting on the first vibe-coded mass used prod app, not ware of any yet.

I'm starting to think that the LLMs ecosystem is going in the JS ecosystem direction, endless technologies with little to no adaption.

Literally everyday there is a new tool and the tools released last week are deprecated.

not available in our org (EU)

I'm genuinely amazed by anyone still using github CI for anything serious.

wasn't there an algo developed that would use wifi signal as a way to detect humans / movements even behind walls.

I imagine that would be a neater solution. if all what you need is a wifi receiver.

Same for chat control in the EU and all the dystopian post 911 spying agencies.

it's there to keep the well behaving citizens in check.

very authoritarian at the core.

yeah the trick is to use them at a slow enough speed that you can keep paying attention, honestly I think I should do 50/50 (with and without AI). but it's funny it feels we all just got busier with AI that I don't feel I can afford half using it.

Yeah I have a well established ... well designed codebase that I had before agentic coding and it does support horizental scaling (more services integrations doing more or less the same).

I got lazy around claude fable and astra, and asked them to work in loop (pick specified issue, develop it, qa it ...) have a separate CTO checking on arch.

at the end both models swore that the code is perfect and well designed and nothing is lacking.

I ran the software and it suddenly started writing large amount of data to CSV files instead of the typical DB usage.

AI decided to use csv for testing, and just drifted away. 0 regards to the actual project, 0 regards to common sense.

anecdotal but really weird, the project category is rather standard, I wouldn't accept such a mistake from a junior developer.

the target companies are the ones reporting the hacks in many cases.

because they didn't burn obscene amounts of Money training each LLM and didn't promise half the planet that their business is worth a trillion while not having even operational break even let alone the cost if you include the overhead.

Soft Bank just raised couple of billions in junk bond sale to support open-ai's current operations before the IPO.

it's a crazy situation where on one side the Chinese / open source LLMs are catching up and reducing the token price, on the other hand the current leading labs have spent everything they got, every new model will cost much more and the public market is too shaky to support an IPO.

They will make it, I don't doubt it, but it's a crazy situation.

I'm genuinely confused what's the relationship between LLMs improvements and them being so incoherent.

and it's not about the verboseness (even though it obviously contributes to the fatigue and loss of focus), I swear the vocabulary of the llms change working on the same task on the same codebase significantly.

I wonder if there are studies around this.

they don't have to answer for the next quarter, and that's good enough for me.

This is the problem with capitalism.

Nothing is ever enough, all the top tech companies, it's not enough that the conquered the global market, not enough that they dominated commerce, media, automotive, cloud, space ...

it's not enough that they have the largest headcounts on the planet (outside India / China).

they always need to do more and bigger the next quarter.

no morals, no core market, no other guideline, simply more, and I have to do it because else someone else will.

I really hope the Chinese keep killing everything that gets too big to fail.

endless growth is the same as cancer. unnatural destructive.

yeah digital infrastructure is more achievable, more important and can produce revenue more reliably compared to AI.

if sovereignty is the goal, drop Microsoft, aws and adapt / develop open source / EU alternative.

once serious progress is made there, more resources can be redirected into AI after all it's already too late to join the race.