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My take on the difference between now and then is “effort”. All those things mentioned above are now effortless but the door to “effort” remains open as it always has been. Take the first point for example. Those little black boxes of AI can be significantly demystified by, for example, watching a bunch of videos (https://karpathy.ai/zero-to-hero.html) and spending at least 40 hours of hard cognitive effort learning about it yourself. We used to purchase software or write it ourselves before it became effortless to get it for free in exchange for ads and then a subscription when we grew tired of ads or were tricked into bait and switch. You can also argue that it has never been easier to write your own software than it is today.

Hostile operating systems. Take the effort to switch to Linux.

Undocumented hardware, well there is far more open source hardware out there today and back in the day it was fun to reverse engineer hardware, now we just expect it to be open because we couldn’t be bothered to put in the effort anymore.

Effort gives me agency. I really like learning new things and so agentic LLMs don’t make me feel hopeless.

by hnlmorg2 hours ago|

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I’ve worked in the AI space and I understand how LLMs work as a principle. But we don’t know the magic contained within a model after it’s been trained. We understand how to design a model, and how models work at a theoretical level. But we cannot know how well it will be at inference until we test it. So much of AI research is just trial and error with different dials repeated tweaked until we get something desirable. So no, we don’t understand these models in the same way we might understand how an hashing algorithm works. Or a compression routine. Or an encryption cypher. Or any other hand-programmed algorithm.

I also run Linux. But that doesn’t change how the two major platforms behave and that, as software developers, we have to support those platforms.

Open source hardware is great but it’s not on the same league of price and performance as proprietary hardware.

Agentic AI doesn’t make me feel hopeless either. I’m just describing what I’d personally define as a “golden age of computing”.

by HoldOnAMinute3 hours ago|

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Have you tried using GenAI to write documentation? You can literally point it to a folder and say, analyze everything in this folder and write a document about it. And it will do it. It's more thorough than anything a human could do, especially in the time frame we're talking about.

If GenAI could only write documentation it would still be a game changer.

by hnlmorg2 hours ago|

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The problems about documentation I described wasn’t about the effort of writing it. It was that modern chipsets are trade secrets.

When you bought a computer in the 80s, you’d get a technical manual about the internal workings of the hardware. In some cases even going as far as detailing what the registers did on their graphics chipset or CPU.

GenAI wouldn’t help here for modern hardware because GenAI doesn’t have access to those specifications. And if it did, then it would already be documented so we wouldnt need GenAI to write it ;)

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by orwin3 hours ago|

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But it write mostly useless documentation Which take time to read and decipher.

And worse, if you are using it for public documentation, sometimes it hallucinate endpoints (i don't want to say too much here, but it happened recently to a quite used B2B SaaS).

by throwup2382 hours ago|

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Loop it. Use another agent (from a different company helps) to review the code and documentation and call out any inconsistencies.

I run a bunch of jobs weekly to review docs for inconsistencies and write a plan to fix. It still needs humans in the loop if the agents don’t converge after a few turns, but it’s largely automatic (I baby sat it for a few months validating each change).

by XenophileJKO2 hours ago|

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Actually this makes me think of an interesting point. We DO have too many layers of software.. and rebuilding is always so cost prohibative.

Maybe an iteresting route is using LLMs to flatten/simplify.. so we can dig out from some of the complexity.

by hnlmorg2 hours ago|

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I’ve heard this argument made before and it’s the only side of AI software development that excites me.

Using AI to write yet another run-of-the-mill web service written in the same bloated frameworks and programming languages designed for the lowest common denominator of developers really doesn’t feel like it’s taking advantage leap in capabilities that AI bring.

But using AI to write native applications in low level languages, built for performance and memory utilisation, does at least feel like we are bringing some actual quality of life savings in exchange for all those fossil fuels burnt to crunch the LLMs tokens.

by fragmede3 hours ago|

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> perpetual subscription services for the same software we used to “own”.

In another thread, people were looking for things to build. If there's a subscription service that you think shouldn't be a subscription (because they're not actually doing anything new for that subscription), disrupt the fuck out of it. Rent seekers about to lose their shirts. I pay for eg Spotify because there's new music that has to happen, but Dropbox?

If you're not adding new whatever (features/content) in order to justify a subscription, then you're only worth the electricity and hardware costs or else I'm gonna build and host my own.

by hnlmorg2 hours ago|

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People have been building alternatives to MS Office, Adopt Creative Suite, and so on and so forth for literally decades and yet they’re still the de facto standard.

Turns out it’s a lot harder to disrupt than it sounds.