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> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. A

by simonw 3mo ago

> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. Anyone else finding they're spending more time writing code (or at least driving agents to write code) now? 14% used to feel about right for me - I'd spend the rest of the time researching approaches and libraries, planning things out in issues, or sometimes just thinking really hard about problems I ran into. Now... I still do those things, but I'm doing many of them faster - and I'm often doing them while my coding agents are churning away on code. There's also this weird effect where the harder a problem is the more I can get done in parallel with it, because an agent might need to spend 20 minutes on it without my involvement.

enraged_camel 3mo ago
Yeah. I spend most of my day driving agents to write code, verifying the results, orchestrating work streams, and so on. The rest of the time, a Fable agent is organizing work in Linear/Jira and making sure coworkers are getting their stuff done in a way that won’t conflict.
geoduck14 3mo ago
I used it to write SQL and make dashboards. Back in the day, I would spend a lot of time doing that, then I changed roles. I dipped my toe in it recently and used AI exclusively. I would send a prompt, see the output, decide if that is what I wanted or not. I kept my brain in "what-if mode" and I let the LLM handle the technical specs.
- TheOtherHobbes 3mo ago
  'What-if' mode is a game changer. And underrated. The cost of prototyping has crashed. So you can A/B/C... various ideas, test them in the real world or by personal preference, to taste, and converge on designs that work for you. This used to very hard and expensive. Now it's so cheap it makes the idea -> test -> refine loop much tighter and faster.
  - geoduck14 2mo ago
    >The cost of prototyping has crashed. So you can A/B/C... various ideas) Oh yes! I would think "I wonder how the data would look if I did X" and feel the pain of complicated SQL... but then the LLM would just do it and I got to see if I liked or not! It was a delight
01100011 3mo ago
You read my mind. I suspect it is a transient spike while I blow through the backlog and I'll run out of things that AI can vastly accelerate in, say, 6 months. But right now? I'm spending 80-90% of my time blasting through implementing features, finding bugs, fixing old bugs, writing and improving my tools... Code was never the majority of my job. But right now the bar to doing things is so low and the sheer joy of blasting through some previously tedious, low to medium hanging fruit is thrilling.
- xnickb 2mo ago
  And when you are done, what will happen with all that code you wrote?
AdieuToLogic 3mo ago
>> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. > Anyone else finding they're spending more time writing code (or at least driving agents to write code) now? Not really, as once it is time to write code, the problem has been defined/understood (to the degree possible with knowledge acquired at the time), and encoding it is largely an exercise in typing along with verifying assumptions via test suites. Does GenAI quicken some portions of the above workflow? Sure, in the same way IDEs with contextual code snippet suggestions can make encoding faster.
geraneum 3mo ago
Does the code get reviewed? How do you deal with increased amount of code that may need to be looked at?
- simonw 3mo ago
  I review the code that matters - anything security adjacent or that's an API that will be used by other code in the future. I don't review code that either works or doesn't - most HTML and CSS layout code for example. There I test it on desktop and mobile and commit it if it works. Ditto for stuff that's simple. A JSON endpoint that runs a SQL query and returns some JSON? If it works and a glance at the tests looks OK then I trust my agents wrote it properly. I'm getting more confident with my judgement over what needs a close look and what doesn't over time, as so far I haven't been majorly burned my any mistakes that snuck through. Honestly, it's similar to being an engineer on a larger team. You don't review every line of code written by every one of your coworkers. I think this is THE issue of our time as programmers to be honest: do you review every line of code an agent writes? An increasing number of expert programmers are moving in the direction of NOT reviewing every line. It's working out OK for a lot of them.
  - t-writescode 3mo ago
    > Ditto for stuff that's simple. A JSON endpoint that runs a SQL query and returns some JSON? If it works and a glance at the tests looks OK then I trust my agents wrote it properly. That is *exactly* the sort of area I *wouldn’t* blindly trust AI, there’s a huge security boundary there. What if the AI is doing string concatenation with user-provided data???
    - simonw 3mo ago
      Once you've seen the AI not make mistakes like that a few dozen times you start to trust it not to mess that up in the future.
      - discreteevent 2mo ago
jreynar 3mo ago
[flagged]

by simonw 3mo ago

enraged_camel 3mo ago

Yeah. I spend most of my day driving agents to write code, verifying the results, orchestrating work streams, and so on. The rest of the time, a Fable agent is organizing work in Linear/Jira and making sure coworkers are getting their stuff done in a way that won’t conflict.

geoduck14 3mo ago

I used it to write SQL and make dashboards. Back in the day, I would spend a lot of time doing that, then I changed roles. I dipped my toe in it recently and used AI exclusively. I would send a prompt, see the output, decide if that is what I wanted or not. I kept my brain in "what-if mode" and I let the LLM handle the technical specs.

TheOtherHobbes 3mo ago
'What-if' mode is a game changer. And underrated. The cost of prototyping has crashed. So you can A/B/C... various ideas, test them in the real world or by personal preference, to taste, and converge on designs that work for you. This used to very hard and expensive. Now it's so cheap it makes the idea -> test -> refine loop much tighter and faster.
- geoduck14 2mo ago
  >The cost of prototyping has crashed. So you can A/B/C... various ideas) Oh yes! I would think "I wonder how the data would look if I did X" and feel the pain of complicated SQL... but then the LLM would just do it and I got to see if I liked or not! It was a delight

01100011 3mo ago

You read my mind. I suspect it is a transient spike while I blow through the backlog and I'll run out of things that AI can vastly accelerate in, say, 6 months. But right now? I'm spending 80-90% of my time blasting through implementing features, finding bugs, fixing old bugs, writing and improving my tools... Code was never the majority of my job. But right now the bar to doing things is so low and the sheer joy of blasting through some previously tedious, low to medium hanging fruit is thrilling.

xnickb 2mo ago
And when you are done, what will happen with all that code you wrote?

AdieuToLogic 3mo ago

>> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. > Anyone else finding they're spending more time writing code (or at least driving agents to write code) now? Not really, as once it is time to write code, the problem has been defined/understood (to the degree possible with knowledge acquired at the time), and encoding it is largely an exercise in typing along with verifying assumptions via test suites. Does GenAI quicken some portions of the above workflow? Sure, in the same way IDEs with contextual code snippet suggestions can make encoding faster.

geraneum 3mo ago

Does the code get reviewed? How do you deal with increased amount of code that may need to be looked at?

simonw 3mo ago
I review the code that matters - anything security adjacent or that's an API that will be used by other code in the future. I don't review code that either works or doesn't - most HTML and CSS layout code for example. There I test it on desktop and mobile and commit it if it works. Ditto for stuff that's simple. A JSON endpoint that runs a SQL query and returns some JSON? If it works and a glance at the tests looks OK then I trust my agents wrote it properly. I'm getting more confident with my judgement over what needs a close look and what doesn't over time, as so far I haven't been majorly burned my any mistakes that snuck through. Honestly, it's similar to being an engineer on a larger team. You don't review every line of code written by every one of your coworkers. I think this is THE issue of our time as programmers to be honest: do you review every line of code an agent writes? An increasing number of expert programmers are moving in the direction of NOT reviewing every line. It's working out OK for a lot of them.
- t-writescode 3mo ago
  > Ditto for stuff that's simple. A JSON endpoint that runs a SQL query and returns some JSON? If it works and a glance at the tests looks OK then I trust my agents wrote it properly. That is *exactly* the sort of area I *wouldn’t* blindly trust AI, there’s a huge security boundary there. What if the AI is doing string concatenation with user-provided data???
  - simonw 3mo ago
    Once you've seen the AI not make mistakes like that a few dozen times you start to trust it not to mess that up in the future.
    - discreteevent 2mo ago

jreynar 3mo ago

[flagged]