alt Hacker NewsAI didn't erase the junior engineer's value, it increased it it
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> The junior engineer executes it, which nowadays means prompting it to an AI tool, and creating a pull request (PR). The PR receives feedback from more senior engineers. The junior engineer gets the feedback and takes it to the AI tool again, proposing changes.
Yeah this part should not exist anymore. It doesn’t where I work.
When I get a PR I just ask an agent to make the proposed changes. There is absolutely zero incentive for me to give feedback for you to give to an agent when I can give it to an agent myself.
Coding isn’t the job anymore. It’s understanding systems and architecture design, and ownership of what you work on. Being able to design solutions, understand them, deliver them and support them in production is the job now. Engineering is still engineering. End to end ownership is the job.
I think it is less about junior/mid engineers, and more just about the kinds of work inexperienced/cheap developers are often doing: assembly line, JIRA-ticket-taker type development.
This is especially impacting Indian tech workers in the US [0] since these are often the types of roles that InfoSys and other foreign tech consulting firms are staffing. The new $100,000 fee to sponsor an H1B visa has made it difficult to justify hiring foreign tech workers when most of the time they are just going to be using American LLMs to do their work anyway.
[0] https://thefederal.com/category/news/h1b-visa-indian-tech-wo...
This is something I've been thinking about the last couple days: how to get junior engineers to be valuable.
I developed a system to help prepare for leet coding interviews so I never feel lost under pressure solving a problem again. It is like a debugger that steps through the code showing all the values of all the variables with data visualizations that reflect the logic so I can grok what it is doing. [0]
After I had the Claude build it, I started looking at the values and there were some mistakes. So, again, the coding agent ran all the code, recorded all the values, and made sure that they line up.
Here is the really cool thing about that. The coding agents can't be trusted. By observing the values stepping though, what I really was doing was debugging coding agent code. It is debugging code presented in a way that is extremely simplified.
What I've been thinking about yesterday and today is, can I do the same thing with a pull request? Have the coding agent run the code, capture all the values, and create a console for the reviewer to step through looking at with data visualizations that abstractly represent that code.
Two things. 1. Coding agents can't be trusted and 2. reviewing code is very difficult. But is it possible to use coding agents to make reviewing code easy for humans? I think so.
That would be a great way for junior engineers to be extremely useful. They only have to step through the code and make sure that all the values line up.
> If the assumption is that AI is going to radically simplify the technical portion of the role, then the people who have started their careers with AI will be in the best spot once they have acquired the experience.
This doesn't make sense - AI is to allow unskilled people to produce what was previously only produced by skilled people.
IOW, how does having 2 years of experience using an LLM to generate code beat having 2 months of experience?
The whole point of using the LLM is that very little skill is involved; how does starting earlier with it provide an advantage? If it's as good as it is claimed to be, starting later with it won't make a single iota of difference to the generated results, compared to someone who started earlier.
"They don’t know what skills they lack. They don’t even know what skills are required because they haven’t put the effort in."
This is it.
Evolving into a developer role was more or less directly proportional to the effort you put in. Before AI I used to ask applicants to the department I oversaw whether they have a GitHub Account with a project to show, and bonus, which they are immensely proud of, no matter what.
You had to grind and hustle, no shortcuts, and no amount of stackoverflow.com copy and paste could save you.
And that leads me to two problems for the disguise of one: effort. This not only means reading and redoing simple exercises to complex projects, but committing to it instead of doom scrolling or TikTok frenzy.
I reserved weekends for certain technical books and was frustrated, that there was so few time and so much book left.
AI gave instant gratification a new dimension. It is horrible until AI gets as good as a perfect project from a prompt or we need to abandon it.
Poor young guys, the joy of tuning out is over either by design or habit.
And make no mistake. I don't blame them. We are all victims and perpetrators at the same time but on a different level.
> This summer, we assigned the problem to an intern (that’s less tenure than a junior engineer). The intern led the development of this feature. They talked to the product manager to understand the problem and requirements. They wrote the design document on how to approach it, aligned with the team, and built it. Of course they did that with the help of AI, and the team they were working with.
So, interns can still produce some value. How much value?
> In our product, there was a feature which had been requested for years, but had not been built yet. It wasn’t overly complex, but it was not critical.
Said another way: The feature was of so little value that it was not even worth assigning to a non-AI-assisted intern! This is what most of us mean when we say “AI lowers the value of…”
Sort of like how there's a running joke, "this meeting could have been an email"; I think that for all the substance I found in this "4 minutes to read" blog post, it could have been a one-sentence comment in some discussion thread somewhere instead.
AI didn't X, it Y. Where Y is write this post.
It's setting them up for absolute failure.
They use it like a crutch and are unable to think critically or do tasks manually.
I wouldn't want to hire anyone to my team with that deficiency.
This article is wrong.
So surely there's more demand to hire junior engineers and their salaries have gone up?
I'm tired of being told what things aren't or what they don't do.
I think reducing junior value to something like time to first merge is playing with fire. Semblance of value is not value, and the value increase here, if there is any, is from the AI.
I trust junior + claude significantly less than I trusted pre-AI juniors. I do not think it will age well to put so much pressure on juniors to make contributions early and with mostly automated mentorship before they really understand what they are doing and why.
I see the complete opposite becoming the case.
In a world where code can be generated rapidly, it's super critical that you have a core few set of people who really understand the macro design of the codebase and can continue to factor it well and iterate quickly.
Adding more people and contributors just increases the probability that nobody really understands the structure of the codebase, it degrades into DRY and unfactored slop.
The cost of reviewing other people's code is almost too high to be worthwhile now... It's much easier to just cut them out and do it yourself.
A core set of very skilled people can just implement whatever change you are doing, but better, cleaner and faster.
I built a fairly large and complex project with Codex and had to spend about 50% of the time factoring things down as I went into well contained modules, had a full understanding of the architecture at a high level. It would have been pretty difficult to do this if bringing in other contributors.
Too many people comment about AI from the perspective of throwing feature A or B over the wall at the workplace, but anybody who has built a huge project from scratch will see how important good design is in regard to iteration speed and result quality.
That being said, there are still areas where changes should be sized reasonably and human reviewed e.g. foundational or very mature software
If the task is simple enough that you can throw AI at it with an intern and get it solved, then it should've been solved already in the first place. I'd argue in more mature organizations all the things that are "backlog todos" are such because there is inherent complexity that can not be solved simply by throwing tokens at it or there are too many unknown unknowns.
Every single time I see an article like this come out on hacker news I have the same reaction “sure, this year”.
There is still room for juniors… in fall of 2026. Will there be in fall of 2030? If your thesis rests on LLMs and AI systems not dramatically improving over where they are today, is it worth anything?
I find it kinda funny how everyone has such divergent opinions of who AI benefits.
Such profound thought. Almost on the level of Hegel.
And then the senior engineer burns the f#ck out.
Reviewing 100 lines of Junior dev slop was bad enough. Now 1000 lines of misguided jr dev ai slop?
Ugh.
I couldn't disagree more. Juniors have very poor design sense and can't guide the AI to land in the right spot. Consistently on my team the developers who are the most reliant on AI are causing me the most trouble. They produce a lot of code but constantly make the same mistakes and can't seem to learn and improve their own design skills, or are doing it at a snail's pace.
We still need the good junior engineers.
Author here. My last post on this reached the front page, and the main objection was that after AI, the junior's marginal value is gone: if a junior just passes specs to an AI tool and PRs back, why pay the salary?
That deserved a real answer, so I wrote this post. Short version: that describes a problem with how the role is structured, not what juniors can do. Push back welcome.
It largely depends on the person. We have several junior engineers who cannot solve a problem without AI. When AI can’t solve it, they just keep trying and failing. And I mean weeks to months late. Then rinse and repeat on the next task. It used to be that they would have been forced to seek help from a senior engineer. Combine the teaching with a real struggle is what makes them better.
As it is now, they aren’t being taught and they’re not learning from what the AI is producing because they don’t understand it. The produced code is a black box, and the AI’s development is a black box too. All they know is that running it produces something like what they asked for. They have no idea about failure modes which is a fundamental concept of engineering. The worst part is that AI is covering up their deficiencies. They don’t know what skills they lack. They don’t even know what skills are required because they haven’t put the effort in.
There are obviously good junior engineers that are using AI judiciously and not as a crutch. They’re the ones who still interact with seniors to get help and actually learn. They would have been successful without AI too. These are the ones the author is talking about. In my experience, the momentum is moving towards the worse type of junior the more AI is adopted. Unless that changes, it will erase their value.