alt Hacker NewsI think the logic can be applied to humans as well as AI:
Sure, the AI _can_ code integrations, but it now has to maintain them, and might be tempted to modify them when it doesn't need to (leaky abstractions), adding cognitive load (in LLM parlance: "context pollution") and leading to worse results.
Batteries-included = AI and humans write less code, get more "headspace"/"free context" to focus on what "really matters".
As a very very heavy LLM user, I also notice that projects tend to be much easier for LLMs (and humans alike) to work on when they use opinionated well-established frameworks.
Nonetheless, I'm positive in a couple of years we'll have found a way for LLMs to be equally good, if not better, with other frameworks. I think we'll find mechanisms to have LLMs learn libraries and projects on the fly much better. I can imagine crazy scenarios where LLMs train smaller LLMs on project parts or libraries so they don't get context pollution but also don't need a full-retraining (or incredibly pricey inference). I can also think of a system in line with Anthropic's view of skills, where LLMs very intelligently switch their knowledge on or off. The technology isn't there yet, but we're moving FAST!
Love this era!!
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Maybe if they could learn how to switch their intelligence on, that would help more?
> As a very very heavy LLM user, I also notice that projects tend to be much easier for LLMs (and humans alike) to work on when they use opinionated well-established frameworks.
i have the exact opposite experience. its far better to have llms start from scratch than use batteries that are just slightly the wrong shape... the llm will run circles and hallucinate nonexistent solutions.
that said, i have had a lot of success having llms write opinionated (my opinions) packages that are shaped in the way that llms like (very little indirection, breadcrumbs to follow for code paths etc), and then have the llm write its own documentation.