When everyone has AI and the company still learns nothing • Hacker News Board

Re: When everyone has AI and the company still learns nothing

#131

Post by cdud3 » Tue, May 05, 2026, 4:44 PM UTC

SlinkyOnStairs wrote: post #57

thfuran wrote: post #44

Earlier quoted context omitted.

>Sooner or later investors will see the "$2M spend" and demand "$4M net profit", and that's not going to materialize. I think this is probably going to happen at the same time that the providers start really jacking up token prices to extract all the value they can.

Almost certainly. Software firms are pretty bad at self-evaluation and they're profitable enough that Capitalism won't force them to do it either. Right now the subscriptions are still in the range of reasonable business expenses, but pretty soon they'll have to jump and $200/month/seat subscriptions turning into $2000/month/seat subscriptions is going to get even very badly ran companies to re-evaluate.

Amen. We are still running highly unoptimized workflows in AWS and nobody reviews why we spend so much $ on that now while it was peanuts when we did it all ourself.

Re: When everyone has AI and the company still learns nothing

#132

Post by asdfman123 » Tue, May 05, 2026, 4:45 PM UTC

dakiol wrote: post #126

If you're a regular engineer like me, there's no real upside to using AI in a company setting. They're boiling us. Of course, the HN elite (investors, execs, celebrities, and top-tier engineers) will say otherwise because "how can you be against innovation man?" AI/LLMs aren't innovation the way TCP/IP, linux, or postgres were. To be clear: claude/codex/gemini/grok/whatever exist for profit, to squeeze the last drop…

1) The game is not ending, it's changing. AI can sling a lot of code but we still need engineers that actually understand what the hell is going on. That's always been the bottleneck. It could eliminate junior positions, but seniors are fine for now.

2) It's been a hard lesson for me to learn because I'm naturally a contrarian, but you are hired to do what management wants you to do. If you resist, your best bet is to hope they don't notice or care, but it's not going to change much.

Re: When everyone has AI and the company still learns nothing

#133

Post by WorldMaker » Tue, May 05, 2026, 4:45 PM UTC

_pdp_ wrote: post #12

pards wrote: post #7

In my large enterprise world, AI adoption hasn't made it outside of the development teams - only developers have access to Github Copilot. Code takes 6-12 months to make it from commit to production. Development speed was never the bottleneck; it's all the other processes that take time: infra provisioning, testing, sign-offs, change management, deployment scheduling etc. AI makes these post-development bottlenecks w…

Yep. I would argue that any sufficiently large system reaches a point where more code is in fact the opposite of what it needs. Nutrition and calories are only useful up-to a point and then we have diminishing and later on negative returns. Even-tough it is not the best analogy because we are describing two different system, it helps put a mental model around the fact that churning more is often less. Side Note: A go…

> I would argue that any sufficiently large system reaches a point where more code is in fact the opposite of what it needs.

I have absolutely worked on code bases I would describe as "marbleized bricks" where the best thing I can do is carve out the statue they already contain. There's a great satisfaction in making PRs that mostly delete things, but the later result is a program that works faster, has fewer bugs/edge cases, is easier for the next person to debug.

The LLMs certainly can add more layers of marble. Companies don't often know how much more they need an artist with sculpting tools more than a bricklayer.

Re: When everyone has AI and the company still learns nothing

#134

Post by woeirua » Tue, May 05, 2026, 4:46 PM UTC

The hype is extreme right now and everyone is still trying to figure out how to use the tools. People who are further along the bleeding edge are trying to tear down all the process that we used to have to further improve velocity. After people go all the way to "dark factories" most companies will realize that they don't actually have any good ideas for what to build, and honestly never did. They've been coasting for years, someone else can replicate their product now and its just a race to the bottom. At that point, token budgets are going to collapse.

I'm staunchly pro-AI as a technology, but I do think the bubble is going to pop in the next year or two just because the business value won't materialize for most companies fast enough.

Re: When everyone has AI and the company still learns nothing

#135

Post by nazcan » Tue, May 05, 2026, 4:49 PM UTC

pards wrote: post #7

In my large enterprise world, AI adoption hasn't made it outside of the development teams - only developers have access to Github Copilot. Code takes 6-12 months to make it from commit to production. Development speed was never the bottleneck; it's all the other processes that take time: infra provisioning, testing, sign-offs, change management, deployment scheduling etc. AI makes these post-development bottlenecks w…

It may not be the biggest bottleneck, but if you can have a similar amount of time, but reduce the number of engineers by 30%, that's a huge win.

And having less people involved means there is much less communication and alignment.

Not to say it's a panacea.

Re: When everyone has AI and the company still learns nothing

#136

Post by mediaman » Tue, May 05, 2026, 4:56 PM UTC

c-linkage wrote: post #93

ravenstine wrote: post #32

Earlier quoted context omitted.

It kinda racks my brain how a lot of people don't think this way. For example, way before the current state of AI, I wrote my own CLI to make aspects of my job easier and easier to write scripts to automate; some colleagues have noticed my tool and said I should share it, and my diplomatically worded answer is no. I don't share it with anyone because of the negative return in both supporting it and everyone else bein…

In my place of employment, anything I create while on company time or using company resources is the property of my employer. So while it might be nice to say I won't share, boss-man can certainly make it so I must share.

Ownership of the IP, as it were, is certainly true, but usually with these tools, most of the battle is documenting it, training people, answering questions, etc., and if you aren't motivated to do that it's very hard to make it happen.

Boss-man actually has a very difficult time turning legal theoretic right into actual deliverables.

Re: When everyone has AI and the company still learns nothing

#137

Post by SoftTalker » Tue, May 05, 2026, 5:01 PM UTC

SlinkyOnStairs wrote: post #37

pards wrote: post #7

In my large enterprise world, AI adoption hasn't made it outside of the development teams - only developers have access to Github Copilot. Code takes 6-12 months to make it from commit to production. Development speed was never the bottleneck; it's all the other processes that take time: infra provisioning, testing, sign-offs, change management, deployment scheduling etc. AI makes these post-development bottlenecks w…

> Development speed was never the bottleneck; it's all the other processes that take time: infra provisioning, testing, sign-offs, change management, deployment scheduling etc. So much of Management (both mid and executive) still considers Software as if it were an assembly line; "We make software just like how Ford makes cars". Code as a product. Which isn't to say that most software development isn't woefully ineff…

"We make software just like how Ford makes cars".

People who say this kind of thing probably have no idea how Ford makes cars either. The assembly line is the last step. All the research, design, engineering, and testing happens before any sheet metal is stamped out. So the comparison might be more true than not, but unknowingly.

Re: When everyone has AI and the company still learns nothing

#138

Post by SoftTalker » Tue, May 05, 2026, 5:04 PM UTC

daheza wrote: post #116

thfuran wrote: post #44

Earlier quoted context omitted.

>Sooner or later investors will see the "$2M spend" and demand "$4M net profit", and that's not going to materialize. I think this is probably going to happen at the same time that the providers start really jacking up token prices to extract all the value they can.

I'm a manager and the VPs are starting to ask - how many story points are we getting with AI now. Now we do story points = number of days to implement. (I know this is not real agile but just assume you are in the same position) I can't answer that question but plenty of other managers are fully ready to just give bogus numbers. For my team, use of AI has indeed lowered the story point cost. The coding part of the st…

> story points = number of days to implement

Some variant of this has been the case in every agile team I've ever worked on.

Re: When everyone has AI and the company still learns nothing

#139

Post by sandeepkd » Tue, May 05, 2026, 5:04 PM UTC

JohnMakin wrote: post #115

highfrequency wrote: post #114

Earlier quoted context omitted.

What’s wrong with the finance team (vibe) coding a janky prototype for planning?

prototypes/mvp's often become the production version

This seems to be the default path which is encouraged/suggested lately, only happy path until you acquire customers

Re: When everyone has AI and the company still learns nothing

#140

Post by soks86 » Tue, May 05, 2026, 5:10 PM UTC

nazcan wrote: post #135

pards wrote: post #7

In my large enterprise world, AI adoption hasn't made it outside of the development teams - only developers have access to Github Copilot. Code takes 6-12 months to make it from commit to production. Development speed was never the bottleneck; it's all the other processes that take time: infra provisioning, testing, sign-offs, change management, deployment scheduling etc. AI makes these post-development bottlenecks w…

It may not be the biggest bottleneck, but if you can have a similar amount of time, but reduce the number of engineers by 30%, that's a huge win. And having less people involved means there is much less communication and alignment. Not to say it's a panacea.

That's an interesting take I don't see anyone else bringing up.

It would also, I would think, make it easier for the 30% fewer engineers to earn a better living in the long run and reduce human management effort.

This makes the most sense to me. So far AI, being fallible, can only augment humans so you can have less humans to do the same work (or tasks where accuracy can be less than 100%, like lower level support calls/questions). Next comes the task of re-balancing the distribution of labor or teaching other departments to utilize AI.

To me that rings the most true because where AI saves me the most time is in never having a bug that takes more than a few hours to pinpoint, even if I'm looking in the wrong place, because with enough clues the AI will look in the right place before I think of doing so. Like finding a needle in a haystack. It doesn't suddenly make me 100x more productive, but it saves a lot of time on some time consuming tasks.