jonfw
The answer is that all companies will not be using the same frontier LLMs competitively
This will be yet another technology that will benefit from economies of scale. Big businesses and those in PE portfolios will lead the charge, adopt AI, increase efficiency, and gain market share at the expense of mom and pop shops.
This will be good for our 401ks because we're all primarily invested in big business
Due to technological advances, solving equations stopped being a marketable skill, but understanding mathematics is as important as ever.
Software engineering will follow a similar route as math- the marketable skill will no longer be to write code, but writing code will be necessary to understand the big picture and build the marketable skills.
Remember that there are other LLM providers, open models, and previous gen models, that are way cheaper that frontier Claude and still way better than what can realistically run locally
Qutebrowser was my favorite browser for keyboard navigation but firefox, chrome, etc. have extensions for this as well.
When I hear that "we found X bugs using some new tool", where the standard for bugs is low and doesn't neccessarily require user impact in realistic scenarios, I think to myself- duh! You went looking for bugs, of course you found them.
For a sufficiently complicated product, in my experience, you don't have to look far.
In humans, it seems that improvement in a new domain seems to follow a logarithmic scale.
Why wouldn’t this be the same for an AI?
If you are at the limits of your architecture you may need to re-write things, and if you are rewriting things you can not arbitrarily speed that up by throwing dollars at it.
But the 1% of repos that do have PRs and actions are likely going to be seeing enormous increases in volumes
I have been a part of two very large companies with self hosted gits and I've seen enough to be confident that this is an incredibly hard thing to manage
And if my grandmother had wheels, she'd be a bicycle!
We are miles off from open models having parity with what the AI labs are putting out.
And that's putting aside the compute requirements to run the top open models and the poor economics of running these models locally.
I suppose that curl + API docs could replace a CLI but that's really token inefficient
Just because I am not likely to join the class of billionaires, does not mean I can not become wealthy! I prefer to measure wealth in terms of quality of life rather than by comparison to others.
I do not have to join the capital class to produce a great life for my family and live in stability and happiness
Inflation and the deficit don't have a 1:1 relationship. For the same dollar of debt, you'll see more inflation from social service spending than you will from tax cuts.
Microsoft experience a sort of reputational resurgence in the tech world these past few years with some commitment to open source contribution and a really nice pivot towards linux and cloud.
Their pivot to AI is much less popular!
This means that billing happens asynchronously. You may use queues, you may do batching, etc. But you won't have a realtime view of the costs
Decades ago engineering salaries were a fraction of what they are today, developing countries did not have computing and educational infrastructure, and we had worse solutions to the logistics challenges from off-shoring.
It is increasingly difficult to justify the US salaries and I'm not sure that the talent pipeline in the US is so superior to make up for it.
As folks optimize for getting these high paying jobs it is increasingly difficult to find someone who has legitimate problem solving skills vs someone who has invested a lot of effort into looking hireable.
One of the interesting things about working on distributed systems, is that you can reproduce problems without having to reproduce or mock a long stack trace
So I certainly don’t see the case you’re talking about where it takes hours to reproduce or understand a problem without a debugger. Of course there are still many times when a debugger should be consulted! There is always a right tool for a given job.
If you rely on monitoring the behaviors of an individual coding agent to produce the output you want, you won't scale