JamesSwift

> we all know Anthropic's revenue will not be anything remotely like flatline for awhile

The SOTA US labs are one chinese open model away from being abandoned overnight by the masses. Ive argued before, but argue again here, that the current hardware shortages are the main thing keeping this from being a reality currently. If more people were able to run local models for a reasonable all-in cost, we would have a much higher velocity of iteration and improvement in the open source community. But its still too niche while people cant justify the cost, and so they continue to pay the premium for inference.

> Most software, once mature, is mostly done.

I think this is a dated mindset with AI in the mix. Not only is AI making it easier to do big-bang rewrites which wouldnt have been done before, it is making working on brownfield codebases more feasible. It is lowering the barrier to entry for non-devs to contribute to codebases. Most software did not stagnate because there wasnt a need to grow it more, it stagnated because the friction and/or cost of change hit a critical mass.

I think we are much too early into the "new era" of software to understand what it looks like tomorrow, especially in terms of what we assume to be true today.

Umm, what? Did we just enforce a global codefreeze in perpetuity? Or, even easier, did we just enforce a global codefreeze for the linux operating system in perpetuity? No? Ok, then how do we end up with a finite number of serious security bugs?

Yes, this is a new normal. No amount of what we historically would have thought of as "normal" preparation can prepare you for being instantly 0-dayed across one or sometimes multiple simultaneous fronts. Merely mentioning something tangentially related to a 0-day is generally enough for any random joe to "clean room" recreate the 0-day and be off to the races.

The historic embargo system is likely not sustainable and we need a shift in both approach and security posture (ie fully trustless architectures by default). Not only that, but because of the insanely amplified frequency and risk of the 0-days, you generally have to throw the baby out with the bathwater and leave yourself completely vulnerable to supply chain attacks. Because not short-circuiting taking upstream updates leaves you open to attack.

Theres shades of the old normal in this stuff, but absolutely this is the dial being turned up to 11 and I dont know if theres any right answers for small teams out there.

Just ask it to build you one. The era of hyper-focused personal software is just beginning.

It just doesnt generally work how I would expect it to work until you learn the details of how to make it work how you expect. Especially as you get into RX it gets really confusing about which execution context you should be on. And execution contexts in mobile land are pretty convoluted to setup IMO.

So yes "async" is easy, but "multithreaded/parallel" is a lot more error prone and explicit.

EDIT: I should also note I havent been in the space for a few years so Im not fully current on how it looks today

Its async model is a pain point, but otherwise it really does a great job of being able to accommodate a vast range of use cases

Yes, there is constant drama but the ecosystem is healthy and you have a choice of multiple upstream "vendors" to hitch your wagon to in terms of your nix experience, and for the the most part they all compile down to the same set of hydra packages so its not really an issue.

Its much easier for the agent to look at a nixos module and decide that it should do `services.nginx.enable = true` vs reverse engineering everything it should do to install nginx on the system.

And likewise if theres an issue then its much more straightforward for it to unwind what it did in nixos vs a traditional software install and not accidentally mess with other users/services on the system.

Looks to be more falling with style to me

lol right? So youre telling me they shipping 150,000 features this week? Or, maybe, they whack-a-moled 149,995 perf or bug regressions and shipping 5 new things. :shrug:

Right, and yet the openai/anthropic models are still a tier above other options despite everyone gunning for them for at least one if not multiple years. While there are numerous jev-likes being spun up _in less than a month_ that are performing (as far as I can tell) up to and sometimes exceeding jev's accuracy.

This isnt the same as dropbox putting in a bunch of work to make the UX "just work", or even stripe doing the same for payments. This is "send me an api call that is in 1 of 3 forms, and get a response back in this form". The heavy lifting is in making that fast and cheap, and because they havent demonstrated a secret sauce in making it hard to outperform actual results that leaves a lot of room for competitors to get their existing models to run faster and cheaper for the same use case.

Dropbox: is I have to move my entire collection and setup the app on all my devices

Instagram: I have to move all my posts and also convince all my network to move over

Github: not a terrible example

If I decided to move off of jev tomorrow it would be an api key and a base api path update. Maybe 30 seconds of work.

I mean, a large majority of "pro jev" posts I see purely focus on the speed/cost and take their word on the accuracy. The entire product is "we guarantee the response will fit this schema, and will do it fast and cheap". Personally, I dont see how anything in this class can be "production ready" as a general classifier without the ability to fine tune on top.

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