alt Hacker NewsWell, there is also a big difference that it will not learn over time. If a junior makes a mistake and it will not be caught in time they will automatically learn.
With LLMs we have to teach them about their mistakes with adapting the harness and then hoping it will stick.
What I also find particularly hilarious about this whole thing is that we were always complaining about how difficult it is to put our tacit knowledge into words and therefore couldn't produce clear instructions for juniors to quickly ramp up. Now we are trying to do just that. I think we will find, just as we did in the past, that it's not possible. I do think a good harness improves results but LLMs will not be able to reach senior levels. Just my 2c.
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They learn between model iterations. You're right, it isn't the same thing as Junior developers' competence improving with experience - the current model's weaknesses are locked in. But it does mean that much of the Junior level thinking and mistakes will be outgrown by successor models.
Maybe someone knows, but it seems like the model used to be called the model, and the thing using a model (handling prompts and context and tool calling and feeding the model) used to be called the agent.
Are we now calling the model the agent and the agent the harness?
> If a junior makes a mistake and it will not be caught in time they will automatically learn.
I think this sentiment applies well to junior software engineers (with mentorship). But imagine the much larger swaths of entry level employees in operations, support, or sales functions. When you have a 400 person team with 20% annual turnover (since people move in / out of entry level jobs frequently), the management + training + monitoring becomes a huge challenge.
I think the typical HN sentiment of "llms aren't deterministic" fails to take into account how non-deterministic giant groups of people are. Every group of 10 people typically needs a manager. And every 10 managers needs another manager. By comparison the engineering work on dialing in your LLM guardrails feels pretty worthwhile.
Part of the positive aspect here is that if I have a junior dev who learns a lesson today, maybe they and their immediate peers learn it, but it won’t be all my junior devs and it certainly won’t be junior devs at other companies.
With models, there’s no reason that a model error in company A can’t be fixed for all of company A, and companies B-ZZZ.
> Well, there is also a big difference that it will not learn over time.
My work is in tick-tock loop of learning - learn without modifying weights, demonstrate learnings to human, but then lock it back in (accumulate and spread).
This looks less like training and more like mentoring.
Getting a human to mentor an agent is a hard UX task, but the learning loop is not a technological problem anymore.
We can only get a tick once a week, no matter how many tocks we can do an hour.