321–330 of 330 posts
No, they come duller and increasingly dependent on the LLM doing them for you.
And that happens to the generations that learned to code earlier without the LLM. What would happen to the later ones, those getting in uni after LLMs emerged, that would never get a real feel for the basics to begin with?
Earlier quoted context omitted.
The benefits of knowing regex is not about the syntax (that’s what docs/google/books are for), but knowing when it’s right to use it. Immersion with the codebase is not about coding and syntax (which is actually very easy for me). It’s about being able to intuit that a particular combination can result in a buggy state and provides the wrong result downstream. You lose that you stay in the dreamland of specs.
That's fair. This all feels similar to the shift that happened when Google came on to the search scene. To use your example, people realized they no longer needed to memorize syntax. Instead they only needed to ensure they understood the big picture concepts, and they could fill in the blanks on demand with Google. This is all just moving that layer of abstraction one level higher.
Earlier quoted context omitted.
That's fair. This all feels similar to the shift that happened when Google came on to the search scene. To use your example, people realized they no longer needed to memorize syntax. Instead they only needed to ensure they understood the big picture concepts, and they could fill in the blanks on demand with Google. This is all just moving that layer of abstraction one level higher.
Not really. Before google, we had (and still have) books. What the internet and later google changed was the availability of information (If I had to rely on libraries and bookstores, I'd never be a programmer today). The job was never about memorizing knowledge, only the application of it. That has not changed since the dawn of computing.
With google that mostly went to the wayside. I just needed to know something existed and I could pull together far more information faster than I was spending before to just do quick lookups
I didn’t say the job was about memorization back then. Rather I found that each of these new abstraction layers made it easier to go broad with one’s on hand knowledge instead of deep
Earlier quoted context omitted.
0.25 day flight vs 120+ day walk doesn't really seem like a fair comparison, nobody is hundreds of times more productive from this.
5 minutes assigning the task to an agent and doing something more productive vs. 2 days of tedious typing you've done a billion times already.
Yes there is a dissonance, using LLMS just took their dot point notes and spread them thin. I personally would prefer just the notes and some personal anecdotes to tie the notes into a cohesive whole. This, this approach here, is not better.
Earlier quoted context omitted.
Does that include the training?
yes. training is a magnitude lower of energy of the lifecycle of frontier models. with current use of opus etc, the math is closer to 1%. https://libguides.usc.edu/blogs/USC-AI-Beat/hidden-costs-of-...
Earlier quoted context omitted.
> So what’s the ideal “middle ground” in this situation? I use agents to code. But I remember the early days of just AI smart complete in the IDE, where as the programmer I had to be more involved with designing and implementating the solution. This kept me engaged with the implementation as it was being built out. Now with agents, I find myself trying to catch up with what the agent did and spend more time code revi…
I think it's the opposite. Being only the code reviewer devolves into being lazy and cutting corners. The sharpening comes from hands-on practice.
> LLM’s amplify what you already have: opinions, structure, frameworks. So far, so agreeable, but… > If you have thoughts, they come out sharper and faster. I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. Actual muscles need exercise to stay in shape (let alone grow), so does the brain. Can we really be sure that thou…
I guess I'm lucky to have taken the career path I have, but I write very little code these days being in pre-sales now. "Productivity" is pretty stark and obvious in sales. You can output all the text you want, maybe it even compiles and passes test suites and looks pretty in a demo. But does it sell? It's nice to be able to have the only true measure that matters actually be measurable. I have yet to use an LLM for…
>> You would probably be surprised how few actually have the agency to do even this small step.
Humans have been gravitating into cognitive thinking and not specialized tasks, some of us, a handful do repetitive tasks and that is ok, but, the majority of us work better in context, in guidance. LLM offers that, offers that abstraction that we were and are looking into all aspects of our lives. We once plow the fields, and harvest by hand, and was good, but suddenly became cumbersome, too much to handle and machines came along to do the job of 20, faster and better, and there humans just tweak the machine, teach the small repetitive tasks. We did that with everything and we change our lives, the way that we upskill ourselves and our communities, we let specialized human tasks as a comfort/skill/romantic/artistic outlet, like some specialized vineyards or specialized farms that do specific very specific things. But the rest we delegate and move to another areas. I believe the problem is not LLM/AI is how we are going to up skill, repetitive jobs no longer need us, so we need to upskill for context, for management, strategy