blindhippo

Humans still write the code, we just do it using AI tools.

If we abdicate and let all software development and operations occur through the use of fully autonomous agents, someone is still ultimately responsible for the agents work/screw-ups. Thus, there is still a human writing code, from an ownership perspective. We all know it won't be the capital/manager class holding the stick there.

I have a feeling the same sentiment will ring true across most of the software industry in the next couple years. LLMs are cool, but they don't perform better than purpose built solutions at scale.

The Supreme Intelligence has entered the chat... My brain has been stuck on that same thought for decades - wouldn't it be great to have a wholly objective, impartial, and independent governing mechanism to limit the influence of power hungry monkeys and their lackeys.

A fantastic low to the ground example of the fundamental problems with human politics is seen in American HOA structures and proliferation. It's utterly amazing to me how insanely corrupt a bog standard HOA can get months into it's inception simply do to base human behavior.

I'll remain bearish on this as well. "Democracy" and collective government has been our species best attempt at this and well...

Dunno about you but I work for a "business" (large company, you've heard of it) and the concept of "High Performer" is synonymous with "best politician". Sure, a lot of theater goes into things, especially dances around "data points", but at the end of the day the top tier goes to the fortunate sons.

In many cases - yes, they have gotten that bad. It's pure fantasy that we live in a free market - there are a handful of companies that own nearly everything, there is very little customer choice or power to "speak with your money".

I do agree though - if one doesn't like the way a company does business, do whatever you can to avoid giving them yours.

I've been using these tools for nearly a year and half on a daily basis. They've become an integral part of my tool box for solving problems.

But writing code was never much more than 35-40% of my job while working for companies/others. Most my time has always gone towards communication, design, and validation. All three of those are not particularly vulnerable to mass AI automation except for the most trivial of scenarios and I have not seen evidence that has changed in over 2 years of so called "improvements".

My "exit plan" ultimately is to be one of the engineers capable of using these tools to scale my impact accordingly so I can focus on higher order problem solving, which ultimately is what is most valuable. I would be more concerned if I was in marketing/sales or frankly middle management.

Maybe this is just "copium" on my part, who knows, this sector is moving fast.

Might work for you, but if I multi task too much, the quality of my output drops significantly. Where I work, that does not fly. I cannot trust any agent to handle anything without babysitting them to avoid going off the rails - but perhaps the tools I have access to just aren't good (underlying model is claude 4.5, so it the model isn't the cause).

I've said this in the past and I'll continue to say it - until the tools get far better at managing context, they will be hard locked for value in most use cases. The moment I see "summarizing conversation" I know I'm about to waste 20 minutes fixing code.

If anything, the AI bubble is reinforcing to me (and hopefully many more people) that the "markets" are anything but rational. None of the investments going on have followed any semblance of fundamentals - it's all pure instinct and chasing hype. I just hope it doesn't tear down the world for the 99% of us unable to actually reap any benefits from it.

AI is basically a toy for 99% of us. It's a long long ways away from the productivity boost people love to claim to justify the sky high valuations. It will fade to being a background tech employed strategically I suspect - similar to other machine learning applications and this is exactly where it belongs.

I'm forced to use it (literally, AI usage is now used as a talent review metric...) and frankly, it's maybe helped speed me up... 5-10%? I spend more time trying to get the tools to be useful than I would just doing the task myself. The only true benefit I've gotten has been unit test generation. Ask it to do any meaningful work on a mature code base and you're in for a wild ride. So there's my anecdotal "sentiment".

Thing is, context management is NOT obvious to most users of these tools. I use agentic coding tools on a daily basis now and still struggle with keeping context focused and useful, usually relying on patterns such as memory banks and task tracking documents to try to keep a log of things as I pop in and out of different agent contexts. Yet still, one false move and I've blown the window leading to a "compression" which is utterly useless.

The tools need to figure out how to manage context for us. This isn't something we have to deal with when working with other humans - we reliably trust that other humans (for the most part) retain what they are told. Agentic use now is like training a team mate to do one thing, then taking it out back to shoot it in the head before starting to train another one. It's inefficient and taxing on the user.

I don't care what kind or style of job - if the balance of power in any labour relationship is overwhelmingly on the employer side, collective action is the only way labour can regain a modicum of negotiating power. To think that the style of job has any bearing on this relationship is naive.

The reports of time saved are so cooked it's not funny. Just part of the overall AI grift going on - the actual productivity gains will shake out in the next couple years, just gotta live through the current "game changer" and "paradigm shifting event" nonsense the upper management types and VC's are pushing.

When I see stuff like "Amazon saved 4500 dev years of effort by using AI", I know it's on stuff that we would use automation for anyways so it's not really THAT big of a difference over what we've done in the past. But it sounds better if we just pretend like we can compare AI solutions to literally having thousands of developers write Java SDK upgrades manually.

Humans (accountants) are non-deterministic, so unsure if an LLM would be better or worse if we threw more effort at the problem.

But in general, I tend to side with the "lets leave the math to purpose built models/applications" instead of generalized LLMS. LLMs are great if you are just aiming for "good enough to get through next quarter" type results. If you need 100% accuracy, an LLM isn't going to cut it.

"Let's knock down social media's walled gardens..."

Links to pay wall trying to get me to pay for some subscription service I've never heard of and would never want to sign up for sight unseen.

mmmhmmm

It could be argued that the emergence of the web and search engines in particular has established this as a common pattern long before AI was around. I'm not convinced that AI represents a dramatic change to this behavior, though the point about anthropomorphizing AI likely acts as a magnifier.

Same things I use it for as well - crap like "update this class to use JDK21" or "re-implement this client to use AWS SDKv2" or whatever.

And it works maybe... 80% of the way and I spend all my time fixing the remaining 20%. Anecdotally I don't "feel" like this really accelerates me or reduces the time it would take me to do the change if I just implemented the translation manually.