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When everyone has AI and the company still learns nothing

robert-glaser.de

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

#21

Post by reaperducer »

homeonthemtn wrote: post #9
rob74 wrote: post #4

One more point I noticed: since AI adoption is being promoted by companies, collaboration between developers could suffer. Why wait for a more experienced developer to have the time to explain some aspect of the codebase to you (and at the same time confess your ignorance), when AI can do it right away in a competent-sounding way (and most of the time it will probably be right, too)?

That's a valid point. Dev/team member isolation, not a great environment to build

Dev/team member isolation, not a great environment to build

Gone are the days of mandatory corporate "synergy" and after-work bar gatherings to promote "team building."

AI is showing people in the tech industry that they're just interchangeable cogs. AI is bringing the offshored Indian work environment to Silicon Valley.

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

#22

Post by razodactyl »

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…

Especially when it waits a month and all the effort is either irrelevant or incompatible with latest changes that finally got through. So much token wastage to top off the recent chaos. Hopefully it improves just as fast as it materialised.

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

#24

Post by razodactyl »

_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…

Seeing this too. Machines are great at pumping out content.

Tl;dr's, quick references / QuickStarts / cheat sheets and FAQs are also some things they're great at generating.

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

#25

Post by cadamsdotcom »

rogerthis wrote: post #16
rob74 wrote: post #4

One more point I noticed: since AI adoption is being promoted by companies, collaboration between developers could suffer. Why wait for a more experienced developer to have the time to explain some aspect of the codebase to you (and at the same time confess your ignorance), when AI can do it right away in a competent-sounding way (and most of the time it will probably be right, too)?

That already happens here. I am old dev who was the goto guy for people with certain business and technical questions. Not anymore (which is part good, as I'm interrupted much less, and part bad, as sometimes they regard the wrong answer as truth).

You could vibe yourself up an AMA tool where people can submit questions, an agent goes to work on them, then the question and agent answer sit in a queue waiting for you to provide a review and give your weigh-in.

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

#26

Post by cadamsdotcom »

AI by itself isn’t that useful. An agent forgets and makes enough mistakes that you have to check all its work, which can be net productivity negative.

It really comes into its own when you treat it as a tool that can build other tools. For example, having it build tools that force it to keep going until its work reaches a certain quality, or runs compliance checks on its outputs and tells it where it needs to fix things. Then and only then, can you trust its work.

Right now most current roles & workflows are designed around wrangling the tools you’re given to do a certain job. In that regime AI can only slide in at the edges.

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

#27

Post by i_think_so »

> one team uses Copilot as autocomplete and calls it a day. Another team runs Claude Code in tight loops, with tests, reviews, and constant steering. A product owner suddenly prototypes real software instead of mocking screens in Figma. A senior engineer delegates a root-cause analysis to an agent and comes back to the valid solution in under an hour; this would’ve taken him two weeks without AI. A junior person produces polished code but has no idea which architectural assumptions got smuggled into the system. A support team quietly turns recurring tickets into workflow automation, because they know exactly where the work hurts and nobody in the Center of Excellence ever asked the right question.

This is just sales copy for various AI companies, laundered through an "influencer". It might as well be the CIA sending their article to be published in Daily Post Nigeria, so that the NYT can quote it as "sources".

The title is just clickbait. The rest of the content are fluffy bunnies and rainbows. It's all summed up as "continue to consume product, but remember to also do X". Sales copy + HBR MBA bait.

The closest thing to an honest, less-than-rosy example is the "junior person" who has no idea about the code they committed.

What about the "senior person" who has no idea about the code they committed? What about the CISO who doesn't understand that pasting proprietary documents willy nilly into the LLM's gaping maw might have legal/security/common sense implications, and that it is his job to set policy on such behavior? What about the middle manager who doesn't even try to retain the most experienced dev in the company because "we don't need the headcount anymore, now that Claude is so fast"? What about the company eating its own seed corn because every single junior position has been eliminated and there are no plans for the future anymore? What about the filesystem developer who fell in love with his chatbot girlfriend and is crashing out on Discord?

Oh wait, scratch that last one. He left the company and is crashing out on his own.

Carry on, then.

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

#28

Post by yetihehe »

razodactyl wrote: post #24
_pdp_ wrote: post #12

Earlier quoted context omitted.

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…

Seeing this too. Machines are great at pumping out content. Tl;dr's, quick references / QuickStarts / cheat sheets and FAQs are also some things they're great at generating.

Like in that comic strip[0], where one side uses AI to inflate his bullet points to make it look better and have more content in the email, then other side uses AI to summarize it to bullet points.

[0] https://marketoonist.com/2023/03/ai-written-ai-read.html

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

#29

Post by wongarsu »

zidoo wrote: post #23

Once people try to increase quality instead of speed they will see how LLMs are powerful. Everything else is just sales pitch by Nvidia and friends.

Even if LLMs write more buggy code they can still bring up software quality in the short to medium term by allowing you to clear out a lot of the backlog of bugs and UI issues that are known but never had enough priority to be fixed

Debugging and developing first fixes is also one of the spaces where current LLMs are the biggest force multipliers. Especially if you have reproduction cases the LLM can test on its own

But long-term it might look very different as more and more of the code becomes LLM written

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

#30

Post by SadErn »

cadamsdotcom wrote: post #26

AI by itself isn’t that useful. An agent forgets and makes enough mistakes that you have to check all its work, which can be net productivity negative. It really comes into its own when you treat it as a tool that can build other tools . For example, having it build tools that force it to keep going until its work reaches a certain quality, or runs compliance checks on its outputs and tells it where it needs to fix t…

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