Definitely feels like a good amount of dev work is writing the same things over and over, in a different language, codebase or context. And it seems like llms are particularly good at translating, specializing and contextualizing across existing knowledge.
It might be financial beneficial once as an up-front payment,
but long term, as others have mentioned, really not good for the project to remove the only feature that gives firefox a defensible way to fill it's niche in the market.
I recently used cursor and it has felt very capable in implementing tasks across files. I get that cursor is an IDE but it's ai functionality feels very agentic.. where do you draw the line?
I had to look up MCST: it means Model-Centric Software Tools, as opposed to autonomous agents.
Devin is closer to a long-running process that you can interact with as it is processing tasks, whereas Cursor is closer to a function call: once you've made the call, the only think you can do is wait for the result.
Two lads set themselves up in the business of selling conkers one year.
Any accidentally dropped conkers were stamped on by any and all in the vicinity.
A conker that survived to the next year was considered "seasoned", although many's the wizened tippex-covered lump of questionable provenance appeared under this explanation.
I'm curious here too, I only flipped through your channels for a minute, but found something interesting immediately.
I go to youtube and seem to run out of quality quickly. I even went as far as crawling the HN frontpage for videos - see hacker news TV - https://xiliary.com/bck/hn-tv.html
PS acquired git prime and rebranded it as Flow, and then basically just kinda ignored it tbh. Basically it analyzed git data and gave info like velocity, how much work was new features vs refactors, etc. Very simplified explanation but for places where code-level analysis is used for performance tracking it can be useful. The problem imo is that while that kind of info is certainly interesting, in most cases it's not really that useful or actionable in practice.
this is my fear regarding AI - it doesn't have to be as good as humans, it just has to be cheaper and it will get implemented in business processes. overall quality of service will degrade while profit margins increase.
The point was that for many tasks, AI has similar failure rates compared to humans while being significantly cheaper. The ability for human error rates to be reduced by spending even more money just isn't all that relevant.
Even if you had to implement checks and balances for AI systems, you'd still come away having spent way less money.
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