[antirez]

Indeed this will likely happen in the future, but not today. I was experimeting with SSD streaming in DwarfStar for DeepSeek v4 PRO inference in 128GB systems (and Flash inference iwth 32/64). GPT 5.5 ran the whole night, I checked what it had accomplished regardless of all the hints I provided in the specification document. After reasoning on the problem I gave him the design fixes and the tokens/sec were 4x after 10 minutes. And this is true for every domain where the human babysitting the AI know a few things in that domain. However this is a moving target, and at the current rate, soon or later, indeed AIs will do much better than us in many domains.

[croes]

Your job safety doesn’t depend on the capabilities of AI but on what management thinks are the capabilities of AI

[antirez]

I don't think this makes any sense. Companies with managers that think AI capabilities are superior will be replaced if they are wrong as the companies will perform very poorly.

[applfanboysbgon]

Hello, efficient market fallacy. Markets are not actually efficient, and especially not instantaneously so. There are a million ways to observe various market inefficiencies[1], so it's childishly naive to assert that they are in fact perfectly efficient according to some ideological belief of yours without considering reality.

[1] Some examples: https://danluu.com/nothing-works/

[antirez]

What I say has nothing to do with efficient market hypothesis. Here the question is simpler: in small companies where there are competitors, who does the wrong choices will be seriously hit since customers will star preferring less slop and more reliability, if AI is mis-used. And companies that instead of firing, hire the folks that are "ideas people" and can use AI efficiently, and now how to control the quality of the output, will deliver more and better. For bigger companies: AI is driving salaries at a more normal level (honestly we want a bit too high, in recent years, even for people with a very low level of knowledge, didn't we?) and to marginally reduce total spending and not deliver the timeline they have, and are used to observe for years, will be noticed. Also companies in the past had a dangerous tendency to over-hire. I don't think now they will invert the direction and over-fire. I have the feeling many managers will instead reason in terms: what is today the great programmer fit? The one with low level knowledge of each algorithm, or the one that has good ideas and understands product, quality, processes, other than programming? And they will try to mix AI and people in order to have an edge.

[applfanboysbgon]

I think we're in partial agreement on some things. I agree that the software field overhired and overpaid people who should never have had jobs in software in the first place, and that a correction is/was overdue. I also generally agree that small companies cannot afford to produce garbage software, and if they make poor decisions about hiring or AI usage, they will die in the womb. But startups failing is not really what I think of when somebody says "companies will be replaced" or "your job security is contigent on what management thinks of AI capabilities". Those sentences both convoke images of already-successful enterprise companies, and already-successful enterprise companies are the ones that are most resistant to market forces. Indeed, we already see this in the real world, because most enterprise companies produce truly horrifyingly bad software, even before AI. The secret is that you need to produce good software to become successful, and then once successful, network effects take over and your company can become unbelievably inefficient and have little to no fear of being replaced. Tech is a ridiculously winner-take-all field, and it's very common for a single company to capture over 50% of their market, after which point they are effectively irreplaceable no matter how many bad decisions they make, at least for many years if not decades.

[florkbork]

The lag time between firing your core team and finding out that was a bad idea can be measured in years of slow attrition.

[antirez]

Actually workflow impact in the world of software can be observed in weeks/months at max. And token spending too, is a voice that they see at the high floors. Also, there was never a strong willing in IT companies to reduce cost of work force: it is done sometimes, but it is more common to see them over-hiring.

[florkbork]

Yeah, nah.

Simple example: Who will renew the SSL cert? Day 1: meh, no impact. Day 2: meh, no impact. Day 700: who the hell manages this and why are we making no revenue?

You might think that is laughable; what a pack of newbs!

But this stuff has already happened without even LLMs in the mix.

https://www.digicert.com/blog/lessons-from-the-equifax-data-... comes to mind.

The number of flea circus level orgs where someone has flubbed it and been on leave, causing a few hours outage? More than one in my experience.

Where it's more hostile? https://www.reddit.com/r/sysadmin/comments/1itiu8n/it_team_f... is a common narrative.

[croes]

And such management faults never ever happened before.

[ben_w]

And even then, there's a reason for the motto "move fast and break things" even if Zuckerberg eventually moved away from it.

The hard question, one which everyone and everything who isn't a domain expert (so AI, juniors, and quite a lot of managers and politicians) suck at, is "which things are safe to break, and which things really do need quality?"

[manincharge]

What happens when said management gets replaced by AI? That should happen rather soon, especially in a company where the functions to be managed are increasingly other applications of AI.