How do we define “seniority” and career/skill progress in the age of AI?
We keep hearing: “Juniors won’t stand a chance.”
But companies are still opening internships, which suggests something deeper than just skill-building still matters (like understanding systems, workflows, and how companies actually operate – the management part).
At the same time, AI is changing how we learn:
Instead of building skills from scratch, we often "copy-paste" them.
Instead of trial-and-error, we get near-instant solutions.
For example, I am learning to code based on my own project. But when Claude constantly gives me solutions, my level of understanding may be lower compared to someone who "figures out" these things by googling, trial and error. With Claude, I do not even feel like a junior yet.
At the same time, experienced developers using AI are becoming:
faster
more precise
more productive
How will we now be able to determine seniority and level of progress when each of us owns an AI assistant?
(By years of service? By successfully applying code from the AI? Real-world outcomes?)
I see this topic as important, especially because salary has always depended on seniority.
It would be good to know how the perception of progress and the remuneration associated with it is changing.
Replies
Nika, the result is the only currency. Seniority is no longer your ability to write code, but your ability to take responsibility for a working system.
The more confident and reliable you are in knowing exactly where AI will fail and how that will break the business six months later, the more senior you are. From now on, responsibility will be the difference between a junior and a senior. And industry connections, too.
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@byalexai it makes sense. We were focusing too much on "years of experience", but the output always mattered. But now, probably the most.
Flavored Resume
@voizematic I think you've captured this perfectly
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@voizematic in any case, now I feel even smaller because if juniors are not building their projects, they will be totally (I do not want to use this word but...) useless.
BrandingStudio.ai
@busmark_w_nika Seniority was always a proxy for judgment, not hours logged. The problem is we used years of experience as a shortcut for "this person has seen enough things go wrong that they know how to avoid them." AI collapses the time it takes to produce an output but it doesn't collapse the time it takes to develop judgment about which output is actually right.
I taught at university level for over a decade and watched students confuse fluency with understanding constantly, long before AI. What changed with AI is the quality and speed of what you can copy, which makes the illusion of competence more convincing and the underlying gap harder to spot.
My guess is seniority shifts to how good are your questions, how fast do you recognise a bad AI answer, and how well do you architect the problem before you hand it to the model. In my opinion the people who will define the new senior tier are the ones who can use AI to think faster without outsourcing the thinking entirely.
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@joao_seabra This reminds me of a company I worked for. The manager was very focused on how long you had been with the company, but she never took into account the intensity of your work.
Someone can work extremely hard and achieve or experience more in five years than someone who has been in the same company for ten years but barely put in any effort.
I would say that the intensity of work is as important as the number of years you have been working.
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@busmark_w_nika Intensity and intentionality, not just intensity alone. You can work extremely hard on the wrong things and still not build judgment. But you're right that the time metric misses it entirely. Someone who ships real products, gets them wrong, fixes them, and ships again in five years has seen more failure modes than someone who coasted through ten. The manager you described was measuring presence, not growth. Those are completely different things.
Apparent for Gmail
Should I ask AI the answer to this question? Just kidding.
I tend to agree with the consensus below. This is a much bigger leap than moving from long division to calculators, but I personally agree that the quality of the output still is highly related to the skill of the person using it. That the tool requires skill to get the truly desired end output.
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@apparentforgmail Do not have to use AI for the answer because your one is pretty clear and accur8 :D
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@tereza_hurtova I like to think and discuss this topic, because it also affects the salary. When someone now uses in the job description: The salary depends on the experience (so this floscule started being very abstract to me). If juniors are not needed, they then have to expect at least medior or only senior people :D
@busmark_w_nika That’s a really good point. It feels like "years of experience" is slowly turning into a very questionable metric... 😄 If output is easier to generate, then just counting years doesn’t tell you that much anymore. Maybe we’ll end up valuing things that are harder to shortcut – judgment, ownership, asking the right questions. But yeah… it definitely makes salary bands and role definitions a bit of a moving target now.
Honestly, I think we're moving into times when your work speaks way louder than your age or years in the industry.
It would be almost laughable if somebody claimed to be "senior in AI" based on years alone when someone who just started last month might be more focused and know way more than someone who's been dabbling for five years.
The real shift is that now we can actually see who produces results versus who just talks about their experience, and that's probably going to make hiring and promotions much more merit-based than they've ever been.
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@rohanrecommends actually when you are mentioning AI and seniority... it reminds me when one position wanted a senior for some AI-related stuff (it was in marketing)... but wtf? At that time, the AI had like one or 1.5 years. :D How someone could be a senior at that thing :D Sometimes it feels like companies do not think twice what they are asking for :DDDD
I'd say that seniority is shifting from "can you do this" to "do you know when something is wrong."
Taking consulting as an example, we see that AI can produce code, a financial model, or a strategy deck. The output looks right, but "looks right" and "is right" are not the same thing.
What AI can't do is tell you whether the output makes sense in context. That judgment comes from experience, and it's becoming the only thing that's genuinely hard to fake.
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@andreitudor14 In that case, once you do not have that knowledge (you will blindly trust AI), the level of knowledge will shift very slowly.
Many people just use AI for copypasting without acquiring "old-school" knowledge IMO.