Comment by slopinthebag
8 hours ago
I think the industry has leaned waaay too far into completely autonomous agents. Of course there are reasons why corporations would want to completely replace their engineers with fully autonomous coding agents, but for those of us who actually work developing software, why would we want less and less autonomy? Especially since it alienates us from our codebases, requiring more effort in the future to gain an understanding of what is happening.
I think we should move to semi-autonomous steerable agents, with manual and powerful context management. Our tools should graduate from simple chat threads to something more akin to the way we approach our work naturally. And a big benefit of this is that we won't need expensive locked down SOTA models to do this, the open models are more than powerful enough for pennies on the dollar.
I'm hearing this more and more, we need new UX that is better suited for the LLM meta. But none that I've seen so far have really got it, yet.
When you steer a car, there isn’t this degree of probability about the output.
How do you emulate that with llm’s? I suppose the objective is to get variance down to the point it’s barely noticeable. But not sure it’ll get to that place based on accumulating more data and re-training models.
Well, the point is by steering it you can get both more expected/reproducible output, and you can correct bad assumptions before they become solidified in your codebase.
You can get pretty close to reproducible output by narrowing the scope and using certain prompts/harnesses. As in, you get roughly the same output each time with identical prompts, assuming you're using a model which doesn't change every few hours to deal with load, and you aren't using a coding harness that changes how it works every update. It's not deterministic, but if you ask it for a scoped implementation you essentially get the same implementation every time, with some minor and usually irrelevant differences.
So you can imagine with a stable model and harness, with steering you can basically get what you ask it for each time. Tooling that exploits this fact can be much more akin to using an autocomplete, but instead of a line of code it's blocks of code, functions, etc.
A harness that makes it easy to steer means you can basically write the same code you would have otherwise written, just faster. Which I think is a genuine win, not only from a productivity standpoint but also you maintain control over the codebase and you aren't alienated or disenfranchised from the output, and it's much easier to make corrections or write your own implementations where you feel it's necessary. It becomes more of an augmentation and less of a replacement.
You wrote all that and didn’t address the question lmao.
There’s diminishing returns and moreover this idea that people are holding it wrong / they need to figure out the complexity goes against all that has been done over the past 30 years : making things simpler.
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