I used to be a software engineer, but these days I find myself being more of an agents manager: constantly switching between 3-4 tasks that my agents are working on, and making sure that the features get shipped, the bugs fixed, with correct and clean code. There's no doubt that I'm producing more value for the company, but I wonder if that's the best I can do for myself if the goal is staying relevant in the coming years.
I wonder: if the AI is writing all the code, what value am I bringing?
In an attempt to keep my critical thinking and coding skills sharp, I sometimes foolishly try to debug errors or implement a feature myself. But it feels like wasting time when an agent can do it in a fraction of time.
What is gonna be sought after in the coming years: someone that persevered with manual coding and debugging but is slow and uncomfortable around agents, or someone that has little coding and debugging skills left but knows how to orchestrate dozens of agents effectively?
I'm curious to hear what other software engineers on HN's approach is.
imo the valuable thing we bring as software engineers is and has always been solutions to problems with the contextually correct quality/speed/cost tradeoffs. with agentic coding, these factors all shift and we're all in the process of recalibrating. namely the speed dial can now be shifted way down.
to answer directly, i live in claude code now. and while it's a different shape of daily work, i'm still engineering, still evaluating those 3 factors and figuring out how to triage and solve user-problems much faster than i could 5 years ago.
I have the agent grill me/ask me questions about what has been implemented, often on a fairly technical/granular level of the feature is important enough.This is obviously way slower than just vibing the whole thing and ticking off a passing test suite (that the agent also wrote). But I find that doing this has allowed me to retain most of my problem solving and reasoning skills (which have definitely atrophied).
People are kidding themselves thinking they fully understand what is going on at a deep level for 3-4 (or more) parallel tasks constantly context switching. It's also an anxiety-inducing way to work and has led to a proliferation of agent management tools enabling max efficiency.
Focusing on systems thinking/observability/knowing when NOT to build something/using agents to fix/learn new things quickly seem to be where I see devs still bringing the most value compared to any other cowboy.
if the AI is writing all the code, what value am I bringing?
What wouldn't an average person off the street be able to do?
I think you're mistaking typing characters on a keyboard for coding. Designing a system is coding. Knowing what refactorings to do to ensure things evolve in the right direction is coding.
Being able to recall all the syntax has lost value due to AI, but designing and leading the feature development hasn't and that can't (yet) be trusted to AI.
I'm not too worried about keeping skills sharp - if I'm ever put in a situation where they become relevant again I'm confident I can just relearn them.
I wonder: if the AI is writing all the code, what value am I bringing?
In an attempt to keep my critical thinking and coding skills sharp, I sometimes foolishly try to debug errors or implement a feature myself. But it feels like wasting time when an agent can do it in a fraction of time.
What is gonna be sought after in the coming years: someone that persevered with manual coding and debugging but is slow and uncomfortable around agents, or someone that has little coding and debugging skills left but knows how to orchestrate dozens of agents effectively?
I'm curious to hear what other software engineers on HN's approach is.
imo the valuable thing we bring as software engineers is and has always been solutions to problems with the contextually correct quality/speed/cost tradeoffs. with agentic coding, these factors all shift and we're all in the process of recalibrating. namely the speed dial can now be shifted way down.
to answer directly, i live in claude code now. and while it's a different shape of daily work, i'm still engineering, still evaluating those 3 factors and figuring out how to triage and solve user-problems much faster than i could 5 years ago.
I heavily use browser based LLM for bugs I care about. Code that is close to business logic like SQL is all 'by hand'.
Frontend stuff for me, which I'm bad at, I let agents do all of and I test the end result.
Other things are in-between, but time wise it's probably mostly me writing code. Lines of code is the LLM for sure.
I have the agent grill me/ask me questions about what has been implemented, often on a fairly technical/granular level of the feature is important enough.This is obviously way slower than just vibing the whole thing and ticking off a passing test suite (that the agent also wrote). But I find that doing this has allowed me to retain most of my problem solving and reasoning skills (which have definitely atrophied).
People are kidding themselves thinking they fully understand what is going on at a deep level for 3-4 (or more) parallel tasks constantly context switching. It's also an anxiety-inducing way to work and has led to a proliferation of agent management tools enabling max efficiency.
Focusing on systems thinking/observability/knowing when NOT to build something/using agents to fix/learn new things quickly seem to be where I see devs still bringing the most value compared to any other cowboy.
What wouldn't an average person off the street be able to do?
I think you're mistaking typing characters on a keyboard for coding. Designing a system is coding. Knowing what refactorings to do to ensure things evolve in the right direction is coding.
Being able to recall all the syntax has lost value due to AI, but designing and leading the feature development hasn't and that can't (yet) be trusted to AI.
I'm not too worried about keeping skills sharp - if I'm ever put in a situation where they become relevant again I'm confident I can just relearn them.