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- Hacker News
- TBH it was already pretty bad. There is a stark difference between the best and the average in my experience. The top, say, ten percent of coders are vastly better than anyone else when it comes to anything but boilerplate glue code(which is still needed and is better done by average coders anyway).
This is speaking from my experience as a systems/c/c++ guy. If you are a js web frontend guy, python, or whatever I have no idea if this applies to you.
by 01100011 - I fall into the category of senior engineers who benefit from LLMs for all the reasons mentioned in this post. I find it's possible to agree completely with sentiments like this and still feel as if this is all written in the sand below the high tide line, and ten years from now nobody will care about this.
Horsemanship and sailing were both specialized skills of high value to society, and now they're not. But in each case there was probably a liminal period, when being an accomplished horseman or sailor was still valuable, even as motors were taking over. Eventually that period ended, as the new generations without those skills found ways to get by with cars and motorboats.
by jp57 - I strongly agree with the concept that cognitive friction is the engine of learning.
First and foremost, it's an issue of "dependency": if you stop training the "muscle" of logic and reasoning, it gradually atrophies, just like unused physical muscles. You become dependent on external tools that replace a capability you once had yourself.
A historical example that brought about a similar shift is this: when the production process moved from the craftsman's mind and hands to the Fordist factory (and the assembly line), the skill of building things shifted from human craftsmanship to anonymous, structured processes.
Bit by bit, traditional artisans lost their knowledge and "know-how." Today, having a piece of furniture in our home depends on a massive production and supply chain; the "average" person no longer has the ability to build it themselves.
The exact same thing is happening to software.
We are the (now "former") software craftsmen.
by aledevv - As a tech educator I 100% agree. LLMs are not going to become a "new compiler" where we don't have to worry about the code any more. There's a reason we trust deterministic systems.
I've been worried about this a lot, I even created an agent skill called do-i-understand that's designed for novice devs (and experienced too, because atrophy) where the LLM asks you questions about the PR you're about to submit. I've found it helps a lot: https://github.com/AnthonyPAlicea/skills/blob/main/skills/do...
One way or another, there will be a skill reckoning.
by TonyAlicea10 - The snake eating it's own tail for llm software development has really been met with a shoulder shrug whenever it gets brought up. At best you might have a small cohort of developers that don't cook their brains with AI and their reward for that appears to be having to review terrible AI code written by people who have cooked their brains.
Completely unsustainable.
- // The need for ongoing friction in long-term skill formation.
The subtitle of the story tells it all.
There are some people who seek out friction. Think about an athlete or a hardcore nerd.
The best engineers are ones who were fascinated with computers and learning as kids and persued it at every opportunity. Found their own friction in other words.
For those kinds of people, friction-seeking is the constant and what LLMs did is moved the point of where the friction occurs.
For example - the best engineers I've worked with didn't necessarily have lots of experience coding in assembly because that kind of friction was no longer necessary. But they could solve hard problems (and if a problem really required assembly they could go learn it)
What I think will be hit much harder by AI is the low tier engineer. Someone who was never truly curious and committed to it, for whom it was just a job. For example a typical offshore ticket pusher kind of person. That kind of person never went out to find friction and that's the kind of thing that's never going to fly again - if I want mediocre or average, the LLMs are sufficient
by xyzelement - I see a large emphasis placed on headless agentic/vibe coding, what I don't see people talking about is how great guided coding is.
I have over a 15 YoE writing software and guided coding sessions - that is, using an editor like Zed or VSCode with an LLM integrated, writing code how you normally would but using a flash model to prompt away the annoying parts and/or plan - is as productive as vibe coding, produces significantly higher quality, is actually enjoyable, and you actually stay sharp.
Flash models (DeepSeek v4 flash) tend to be so fast that you don't have time for parallel agents, you lock in and rapid fire prompts, building high quality software while incrementally reviewing it as you go. VETO bad edits and try again or rewrite them manually.
By contrast, I have noticed headless agentic coding tends to be an unreviewable black box. The major issues I've found is that, even with a human-in-the-loop, you accumulate defects which compound and eventually you're spending millions of tokens to make trivial changes in a ridgid codebase.
Ultimately, tiny, highly cached, fast models like Qwen's 27b/a3b range or DeepSeek flash are highly capable and relatively inexpensive to run. Hoping people realise we don't need 14 trillion parameter models and I'll be able to buy some ram for my workstation
- 100%
We're already seeing this at the enterprise level. Companies have dictates from leadership that "if you're writing code manually, you're doing it wrong."
Okay, that kind of works for a while. We are indeed producing a shit-ton of code, but the reality is that engineers are pumping out code faster than the humans can understand and (honestly) review it. That sounds great until you realize that "hey Claude, read this Jira ticket and implement the feature in this code base" isn't really worth $200K/year.
This is all complicated by the fact that we're also losing our grasp on reality from the other direction because we have leadership air dropping AI generated manifestos on the product owners and product owners having to use AI to transmute all that shit into 1,500 word Jira tickets that are 10% necessary feature work and 90% LLM boilerplate.
So now you have software engineers whose job has changed radically to the point that the hardest part about being a software engineer is just filtering through AI generated artifacts from all directions just to try to get a feature out the door.
by ryandvm