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#code#comments#llm#productivity#more#llms#prompt#coding#write#actually
Discussion (16 Comments)Read Original on HackerNews
* Learning stage: 0.5x - 1x. I change my system prompt to teacher mode, taking the productivity hit for actually learning the system/tool pays off dividends later. I change my system prompt to "teacher mode" and slowly loosen it as I get more confident.
* Working-knowledge: 2x - 3x. Once I am ramped up enough I feel like I can get a decent productivity boost. Most of the time is spent at the planning stage. This is my mode for areas I don't really own or care about, just need to get work done.
* Mastered: 10x+ I have been doing web front end for 12+ years, I can quickly review plan/implementations and for my initial prompt I already know most of what I want built.
1x == my speed before AI
This really needs to be calibrated to the type of work and complexity.
I can actually believe that LLMs would speed up basic web dev work in small, simple codebases 10X for simple requests.
These conversations usually turn into people talking past each other because theyâre working on different things. For other less routine and more complex work, expecting a 10X productivity boost is not realistic at all. It doesnât matter how good you get at writing prompts and reviewing plans. LLMs just donât solve everything for you in a good way. Some times the true nature of the problem is revealed while implementing it and by deferring everything to an LLM you spend days throwing tokens at the wrong thing. There is a lot of work where the LLM speed up comes from helping you quickly search docs and codebases and double check your code, but handing the entire thing off to an LLM isnât reasonable. These tasks arenât going to reach this mythical 10X productivity boost that is genuinely achievable for much simpler work.
- 25% planning & aligning with other teams
- 25% coding
- 25% testing/verifying
- 25% code review/rework
One argument was that agentic coding speeds up that coding part a bunch. So maybe there's 2x speedup in coding. But that's only a small speedup in the totality of everything software engineers do.
Amdahl's Law should be familiar to anyone with a 4y computer science/engineering degree. Why aren't they applying it to their own throughput?
Suddenly devs who were cranking out features with no interest in infrastructure are attacking giant refactors to make the code more understandable to the LLM.
Other devs are using LLMs to build themselves quality of life SDLC tools completely separate from the core code base.
Plenty of other examples of this.
Of course, the main issue is that theyâre completely undebbugable now. My bash scripts used to be a sequential list of commands, now theyâre 500 lines of variable laden functions.
Is my life any better? Dunno. But itâs satisfying (until thereâs a bug)
Well, that means the quality actually dropped then :). Looking impressive isn't equal to quality, understandability and reliability is
A node glob() or a regexp string.replace call is probably easier to read than spaghetti shell.
And your llm might do a much better job of creating clean, readable and testable code.
> Never write READMEs, docstrings, or comments. I will write those myself later. And yes, I really mean this.
This is quite validating as I came to the exact same conclusion myself. Weâre required to use an LLM for every task at work that touches codeâ , and I was really struggling to get Claude to stop with the long waffly comments that reiterate the next few lines of code in 3x as many characters, making contextless references to subtasks in whatever harness du jour weâre using this week.
No amount of examples or explanation of what I wanted would make it stop. And then I realised of course, Iâm asking something which has no concept of meaning (or, indeed, anything) to only add meaningful comments. More fool me I guess.
Of course, itâs ultimately pointless given all of my colleagues are regularly opening PRs with more comments than code anyway. 80% of my code review responses these days are just increasingly exasperated âpointless comment, please removeâ.
â This is just as infantilising as it sounds, by the way
[0] https://github.com/chrisvariety/branch-fiction/blob/deb37f2b...
Why not just write the code in the prompt so LLM can paste it.
I found that latest codes don't write comments in code by default. And when they do, they write stupid shit like "This was code that did X, it was now removed".
You have to explcitly prompt them to write comments in code. They are still useful for you, the user. But are arguably useful for the model, too, given how many of them (especially Claude) only reads small chunks of files. So I'd rather have code comments than it reproducing a picture from incomplete data.
I already convert from multipliers to percentage of increase, so when someone claims 10x they very likely mean +100% productivity, and here 2x means +20% productivity, which seems about right. Nobody that was normally productive before LLMs has suddenly 10x'ed their output now.
The problem is that 20% productivity when it comes to generating code, really doesn't translate in 20% productivity increase overall, when you take into account the fact that the code quality is worse, the fact that writing code is actually not the majority of your time spent, and that people get burnt out from the usage.
Take that, you mere 10x-ers! Your days are toast!