It became diminishing returns years ago, long before AI.
But absent a central planner for all human endeavor, people are free to see if their particular brilliant idea will be the one in a million that gets traction.
I mean, do you understand the systems you work on? Down to the ISA? The transistors? The electrons?
The stack gets taller and more complex, as it ever as. People who understand one part of the stack in great depth rarely understand the entire stack. Those who understand its full shape don’t have complete depth at any one part. This is how computing has worked for a few decades at least.
You don’t have to shut up, you’re free to dive in and learn. But you’ll have to balance breadth and depth like the rest of us.
I think most people with even a bachelor's in anything STEM know it down to the transistors. That's also been true for decades. Every time I hear this line of argument I cringe. Computers aren't that deep compared to other engineering topics.
> Every time I hear this line of argument I cringe.
Because it’s the same kind of fatuous logic that intelligent design proponents use. This thing is so complex so we can’t possible understand it. Therefore, it’s magic.
People specialize for sure, but it’s not like the average person can’t figure this stuff out with some motivation.
Before you get to transistors you need to understand memory types (heap, stack, etc). You need virtualization, interrupts, and threading. You need CPU vs GPU, character encoding, and memory mapping. At least ipv4 and layers 1-3 of OSI. And much more.
Do you really think anyone with a bachelors in STEM has all that, or are you saying full stack knowledge is satisfied by knowing a high level language plus the fact that transistors switch passing or blocking current based on a signal?
But assuming that one ex-dev with a large AI budget is highly profitable, why wouldn’t you convert the other 9 and give large ai budgets as well?
I guess if the company has no opportunities for growth so they only need exactly as much output as one team? But that sounds like a company that’s doomed anyway, regardless of ai.
You need to grow customers or contracts by 10x to fill the new pipeline and that's an impedance mismatch. Easier to let 9 go and hire later, especially since everyone else will be doing the same thing and there'll be a rather large pool of talent.
How you identify talent in this new world is a different kind of a problem which I don't think people figured out still and won't for quite a while.
If an org suddenly has 10x the production capacity for the same price and can’t figure out how to sell it profitably, it is mismanaged and will die. That’s very much the case for a lot of businesses for sure, but there have been filters before (the internet, for instance) and we survived.
I’d love to see data. For my part the products I use seem to be moving faster, with more small fixes, accessibility better designed in, localization better (even if imperfect) and more rapid releases.
I’m not sure Google, Apple, and Microsoft are the best barometers of AI impact on software engineering. They write software, but at such scale and with such ossified business practices that would expect them to be laggards in leveraging AI.
And things like windows slow context menu are exactly where AI is less useful, because the problem is cruft and the requirment to maintain backwards compatibility with decades of first and third party apps written for older versions. Fixing that is a huge refactoring exercise which AI can do, but which is extremely complex and full of risk.
Same with writing a net new OS: what do you want in the OS? The problem is requirements and market need, not code.
This is also being done in retail, where manufacturers and/or distributors pay for preferred placement (end caps, eye level, etc), but how do you check that e.g. Safeway is really doing that across a couple of thousand stores?
You hire minimum wage people to walk around stores with cameras. This was actually done with notepads occasionally, but so much less expensive tondo with AI.
True, in-store planogram compliance and floor-plan compliance have got in focus again. It never lost the focus to be honest, just that now there is an expectation to do it while ensuring nothing fall through the cracks.
But there is a much more stringent privacy requirement here since customers walking in those stores haven't really signed up for this analysis. Hence, difficult to just setup the camera and take continuous data for analysis.
Interesting on the privacy angle. I’m not sure anyone is really caring about that; there are lots of companies offering automated compliance services. I’m not super close to that industry but close enough that I’ve heard the pitches, and even the “no expectation of privacy in public” CYA has never come up.
What’s going to be fun are robotic stockers, racing to ensure compliance when a person/bot flagged as an auditor is in the store.
You’ll be reaching for the Pepsi and some robot will swoop in and replace the entire shelf with Coke when the Pepsi auditor walks into the store. Then you’ll reach to bottom shelf for your Coke and just as the robot swaps it back to eye level because the Coke auditor walked in. The store having sold the same placement to both.
This might be already happening. Competitor's market share (without details) is common to share. Scintilla onboarded by Walmart earlier this year might already be giving instore AI capabilities.
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