At work, I have the same difficulty using AI as you. When working on deep Jiras that require a lot of domain knowledge, bespoke testing tools, but maybe just a few lines of actual code changes across a vast codebase, I have not been able to use it effectively.
For personal projects on the other hand, it has expedited me what? 10x, 30x? It's not measurable. My output has been so much more than what would have been possible earlier, that there is no benchmark because these level of projects would not have been getting completed in the first place.
Back to using at work: I think it's a skill issue. Both on my end and yours. We haven't found a way to encode our domain knowledge into AI and transcend into orchestrators of that AI.
> deep Jiras that require a lot of domain knowledge, bespoke testing tools, but maybe just a few lines of actual code changes
How do new hires onboard? Do you spend days of your own time guiding them in person, do they just figure things out on their own after a few quarters of working on small tickets, or are things documented? Basically AI, when working on a codebase, has the same level of context that a new hire would have, so if you want them to get started faster then provide them with ample documentation.
> Do you spend days of your own time guiding them in person, do they just figure things out on their own after a few quarters of working on small tickets
It is this rather than docs. I think you're absolutely right about our lack of documentation handicapping AI agents.
> Hey, I'm not the OG commentator, why do I have to explain myself! :)
The issue is that you're not acknowledging or replying to people's explanations for _why_ they see this as exponential growth. It's almost as if you skimmed through the meat of the comment and then just re-phrased your original idea.
> When Fernando Alonso (best rookie btw) goes from 0-60 in 2.4 seconds in his Aston Martin, is it reasonable to assume he will near the speed of light in 20 seconds?
This comparison doesn't make sense because we know the limits of cars but we don't yet know the limits of LLMs. It's an open question. Whether or not an F1 engine can make it the speed of light in 20 seconds is not an open question.
It's not in me to somehow disprove claims of exponential growth when there isn't even evidence provided of it.
My point with the F1 comparison is to say that a short period of rapid improvement doesn't imply exponential growth and it's about as weird to expect that as it is for an f1 car to reach the speed of light. It's possible you know, the regulations are changing for next season - if Leclerc sets a new lap record in Australia by .1 ms we can just assume exponential improvements and surely Ferrari will be lapping the rest of the field by the summer right?
There is already evidence provided of it! METR time horizons is going up on an exponential trend. This is literally the most famous AI benchmark and already mentioned in this thread.
I am still using LLMs just to ask questions and never giving them the keyboard so I haven’t quite experienced this yet. It has not made me a 10x dev but at times it has made me a 2x dev, and that’s quite enough for me.
It’s like jacking off, once in a while won’t hurt and may even be beneficial. But if you do it constantly you’re gonna have a problem.
It’s immeasurable. I use AI for powering through personal projects, which would not have gotten done without AI because I also have a job and a life. It allows me to focus on the product and requirements rather than the code. It’s hard to measure because the projects would simply not have gotten done without it.
Can you talk a bit more about the incentives to trade latency sensitive strategies on IEX in the first place? Is it still lucrative for its liquidity despite them artificially slowing down orders? Does a meta game evolve with HFTs all working around their system, essentially making it still a HFT playground but with extra steps? Do you think their unexpected latency increase for you guys was intentional, to free the water from sharks?
For personal projects on the other hand, it has expedited me what? 10x, 30x? It's not measurable. My output has been so much more than what would have been possible earlier, that there is no benchmark because these level of projects would not have been getting completed in the first place.
Back to using at work: I think it's a skill issue. Both on my end and yours. We haven't found a way to encode our domain knowledge into AI and transcend into orchestrators of that AI.
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