4 ms·

I think of AI like a Junior Engineer. If I understand the problem well enough, and have a really good description of what I want, like I'm explaining it to a j

I think of AI like a Junior Engineer. If I understand the problem well enough, and have a really good description of what I want, like I'm explaining it to a junior engineer, then they do an OK job at it. At my last job, we had a coding "challenge" as part of the interview process, and there was a really good readme that described the problem, the task, and the goal, which we gave the candidate at the start of the session. I copy/pasted that readme into copilot, and it did as good a job as any candidate we'd ever interviewed, and it only took a few minutes. But whenever there are any unknowns or vagaries in the task, or I'm exploring a new concept, I find the AIs to be more of a hindrance. They can sometimes get something working, but not very well, or the code they generate is misleading or takes me down a blind path. The thing for me, though, is I find writing a task for a junior engineer to understand to be harder than just doing the task myself. That's not the point of that exercise, though, since my goal is to onboard and teach the engineer how to do it, so they can accomplish it with less hand-holding in the future, and eventually become a productive member of the team. That temporary increase in my work is worth it for the future. With the AI, though, its not going to learn to be better, I'm not teaching it anything. Every time I want to leverage it, I have to go through the harder tasks of clearly defining the problem and the goal for it.

kyleee 1y ago
“ The thing for me, though, is I find writing a task for a junior engineer to understand to be harder than just doing the task myself.” I have been thinking about this angle a lot lately and realizing how much of a skill it is to write up the components and description of a task thoroughly and accurately. I’m thinking people who struggle with this skill are having a tougher time using LLMs effectively.
rsynnott 1y ago
Only really terrible junior engineers will _pretend they know how to do the thing and just produce nonsense_, tho.
- insane_dreamer 1y ago
  This is the key problem. The LLM won't ask questions or clarify something that it doesn't understand; it'll just proceed with what it thinks it knows, and more often than not, get it wrong. It does usually summarize what you want, but that's simply a restatement of the prompt (sometimes verbatim), which is not the same as the type of follow-up questions that a good Jr engineer would make.
  - cadamsdotcom 1y ago
    That’s what it does unprompted. Prompt engineering involves (among other things) anticipating this and encouraging the model to ask clarifying questions before it begins. Separately but related, models are getting better at recognizing and expressing their own uncertainty; but again they won’t do that automatically; you need to ask for that behavior in your prompt. And finally; models aren’t yet where they should be with regard to stopping to ask questions. A lot of the Devin style agentic products are going to push & eval their models for their ability to do this, so it’s a capability you can reasonably expect to see from future models and will make a lot of my post obsolete. So right now you need to ask the model to ask you clarifying questions and tell you what it’s uncertain of - before it goes off and does work for you.

kyleee 1y ago

“ The thing for me, though, is I find writing a task for a junior engineer to understand to be harder than just doing the task myself.” I have been thinking about this angle a lot lately and realizing how much of a skill it is to write up the components and description of a task thoroughly and accurately. I’m thinking people who struggle with this skill are having a tougher time using LLMs effectively.

rsynnott 1y ago

Only really terrible junior engineers will _pretend they know how to do the thing and just produce nonsense_, tho.

insane_dreamer 1y ago
This is the key problem. The LLM won't ask questions or clarify something that it doesn't understand; it'll just proceed with what it thinks it knows, and more often than not, get it wrong. It does usually summarize what you want, but that's simply a restatement of the prompt (sometimes verbatim), which is not the same as the type of follow-up questions that a good Jr engineer would make.
- cadamsdotcom 1y ago
  That’s what it does unprompted. Prompt engineering involves (among other things) anticipating this and encouraging the model to ask clarifying questions before it begins. Separately but related, models are getting better at recognizing and expressing their own uncertainty; but again they won’t do that automatically; you need to ask for that behavior in your prompt. And finally; models aren’t yet where they should be with regard to stopping to ask questions. A lot of the Devin style agentic products are going to push & eval their models for their ability to do this, so it’s a capability you can reasonably expect to see from future models and will make a lot of my post obsolete. So right now you need to ask the model to ask you clarifying questions and tell you what it’s uncertain of - before it goes off and does work for you.