For me, the biggest shift is people who don't care about local AI. The idea that you can no longer code without paying a tax to one of the billion $ backed company isn't sitting well.
I don’t understand why more people aren’t focused on how to get the benefits of ai but on your own machine. If the last 20 years of software transitioning off of our desktops and into the cloud has taught us anything, it’s that letting corporate entities run the software you rely on end to end gives you: worse software with more bugs, surveillance and subscriptions. Why on earth would you want that for everything you do.
Because a lot of the AI hype/use is driven by companies who just want to pay money for a service? Besides, my laptop would need a pretty big RAM upgrade.
I agree local is better, but the big companies are making decent products and companies are willing to to pay for that. They’re not willing to spend engineering money to make local setups better.
If there's a model that's as good as Claude 4.5 (not even 4.6) I would pay tens of thousands to run it locally. To my knowledge there isn't yet. Benchmarks may say so but I haven't used one that does yet. I always try new models that come out on openrouter
Local AI is what people want/need, but centralized AI is where the investors' money is flowing, because a walled garden has always been easier to turn into a cash printer.
The price does not matter, even if it were free. If you need to be logged on into an external service to be able to code, it's just not the same any more, and I'm thinking of basic technology here, but the political/distopian ramifications are crazy.
The marginal differences in quality seem pretty meaningful right now, enough to make Claude wildly dominant, but some of the locally runnable models like Qwen feel only a few months behind the leaders.
I'm betting the generational gains level off and smaller local models close the gap somewhat. Then harnesses will generally be more important than model, and proprietary harnesses will not offer much more than optimization for specific models. All while SaaS prices ratchet up, pushing folks toward local and OSS. Or at least local vs a plethora of hosted competition, same as cloud vs on prem.
After having gone all-in on LLM agents for a while, I'm not so sure anymore. An LLM with lots of context can sometimes generate more accurate code, but it can also hide decision-making from you, the person who actually has to maintain that code. If the LLM pulls in 1000 files to make a decision, that's no longer a decision that you can understand.
