● AI Job Crisis
“If we just use AI a lot…?”…The real conclusion shown by Silicon Valley’s developer job-seeking crunch—‘the fundamentals of work’ have become even more important
5 things the current reader must know (covered in this article)
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A trend is already underway in Silicon Valley where junior developer hiring is sharply dropping.
“The developer doesn’t actually do the coding” isn’t an exaggeration—it’s becoming reality. -
Adopting AI doesn’t automatically translate into competitiveness.
If, on the contrary, work capability (problem definition·delegation·ownership·verification) deteriorates, it can backfire. -
What matters to a leader isn’t “bringing in AI,” but redesigning the organizational structure.
In an era when boundaries collapse, if teams only keep colliding, you don’t get results. -
Uncomfortable feedback, work-life balance label (work-life balance) conflicts, and the growing gap between senior/junior generations are also increasing.
The starting point for solving it is curiosity + reducing time lag + a 1:1 routine. -
The most important keyword is “unlearning” through metacognition.
The leader’s stamina is the ability to notice the moment when “what I used to be good at no longer works.”
News Briefing 1: Why Silicon Valley’s ‘developer job crunch’ has gotten even worse
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As US big tech companies have continued layoffs, large numbers of senior talent are flooding the market.
As a result, the argument goes that even the roles originally handled by juniors are being occupied by seniors, raising the entry barrier even further. -
Another observation continues: “Because there’s nowhere to go, big tech resignations are at the lowest level ever.”
If people can’t move easily, eventually hiring, movement, and growth get blocked all at once. -
A drop in junior hiring is connected not only to “economic impact,” but also to technological change (AI replacing coding).
In other words, it’s not that hiring numbers are just shrinking—it’s that the roles of the needed people are changing. -
With internships also shrinking, the shock feels much bigger for students and job seekers who are preparing.
It’s to the point where, like what professors say, you hear realistic lamentations such as “I wish you could talk to people and conduct interviews.”
News Briefing 2: The answer to “If we use AI a lot, won’t competitiveness go up?”
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To start with the conclusion, using AI is a ‘technology,’ and competitiveness depends on ‘the fundamentals of work’.
The people who use AI tools well are different from the people who define the work properly and take responsibility all the way through. -
In the AI era, especially higher levels of work remain.
Defining problems, delegating work, and owning responsibility become more valuable. -
A boundary emerges between “tasks that can be outsourced to AI” and “tasks that cannot.”
The person who understands that boundary ultimately drives performance. -
Another point is that even in developer work, ‘verification’ and ‘review’ are becoming more important.
When AI generates code, people move upward to “verify and take responsibility” from a higher level.
News Briefing 3: What leaders must do now—Delegation is not a ‘skill’ but ‘training’
1) Why beginner leaders can’t delegate
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Leaders who hesitate to delegate usually run into two things.
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“If I hand this over, will my value as a person decrease?”
→ Often solidifies into an identity issue -
“There isn’t someone trustworthy in the team.”
→ Often hardens into a staffing/trust/competency issue -
So the solution must start with the questions the leader personally asks, not “speaking well.”
Diagnosing the root cause of why delegation isn’t working will clarify the direction.
2) The correct delegation process (step-based)
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If you hand everything over at once, the chance of failure is high.
The professor’s proposed direction is step-by-step delegation.1) The leader sets the planning and delegates only part
2) If there are no issues, expand the scope
3) Reduce gaps through periodic checks (regular meetings)
4) Gradually, team members take ownership of planning too, and the leader shifts to report-focused
5) Ultimately, require “a culture where team members are delegated to” -
This last part is extremely important.
It won’t work if the leader simply dumps everything—what has to grow in the team is a culture that delegates the delegation itself.
3) Representative examples of wrong delegation
- There are critiques that delegations like “People are hard to manage, so we pass HR tasks to the HR department head” are wrong delegation.
In small startups, there are areas the representative must carry.
News Briefing 4: A 3-step logic for leaders to do uncomfortable feedback well
Core principle
- Uncomfortable words end up being postponed because of “relationship risk,” and the time spent postponing is dangerous.
That’s because an imaginary world grows in the leader’s head, the gaps of emotion deepen, and it becomes easy to explode.
Specific methods (the order emphasized by the professor)
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First: curiosity
Start from the perspective, “Why is the team member behaving like that?” -
Second: reduce time lag
Structures form where the longer you wait, the more you end up hating the other party. -
Third: a 1:1 meeting routine
If a manager who you usually don’t see suddenly demands face-to-face discussion, the team member gets more tense.
That’s why regular 1:1s reduce the courage required for conversations.
Framing of words (“reduce obsession with ‘I’m right’”)
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If you obsess that “trust only forms when I secure the evidence clearly,” it takes longer.
Also, evidence can still end up mixing in subjectivity. -
So the professor says to speak quickly using ‘observation → expected gap’.
Example: “I thought this would end by the end of this week, but seeing the morning meeting, it looks like it won’t be finished until next month too. What do you think?” -
And you need to repeat that the intention is not an attack but a solution.
It’s a way of constantly reaffirming the shared goal: “Let’s succeed together.”
News Briefing 5: Work-life balance label (work-life balance) conflict is a matter of ‘motivation,’ not ‘generation’
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In Silicon Valley, “people whose off-work switch doesn’t turn off” is mentioned as a characteristic.
Korea has a culture where people work less outside even if they work inside the office,
while in Silicon Valley, work may end quickly, but logging in and additional work can continue. -
However, they say the standard for “being hardworking” doesn’t necessarily have to mean working overtime.
As long as you produce results aligned with the expected level you’re given, you should be recognized. -
Like the Denmark team member case, there are also forms where even without big career ambitions, people can finish the assigned work well.
In the end, what matters is the frame of meeting level expectations + playing as a team when it gets hard. -
An ideal work-life balance is focus in the “marathon” perspective.
It’s summarized as the claim that a life where you keep running like a 100m sprint is inefficient and unhealthy.
News Briefing 6: The essence of leadership in the AI era—‘mission·context’ stays, only ‘organizational structure’ changes
1) The essence of leadership doesn’t change
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The essence of mission/vision and “what problems we want to solve” doesn’t change.
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What should change is how you structure the team in concrete terms and how delegation is handled.
2) If the organizational structure breaks, AI adoption matters less
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Traditionally, there has been a division-of-specialty structure (planning-design-front-back development, etc.).
That was because it required technical specialization. But as AI advances, the boundaries are blurring. -
However, if you leave the organizational structure as it is, you can actually increase “collisions.”
For example, the design/development collides while trying to distribute the ideas made by planning, resulting in no overall value being created. -
So what a leader must wrestle with isn’t AI adoption itself, but an organizational structure suited for the AI era.
3) Why startups might become even more advantageous
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Newer companies with fewer legacy (old fixed) organizations can redesign teams more flexibly.
That’s how a structure can emerge where end-to-end execution is possible with a small number of people. -
Companies mentioned as examples (e.g., cases showing fast development with AI native approaches) lead to the message that “starting small and finishing end-to-end makes speed possible.”
News Briefing 7: Areas AI can replace vs. areas people must remain in
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From a development perspective, coding itself is increasingly covered by AI.
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Instead, the areas where people do more are “problem definition (what to solve),” “coordination (who gets what),” and “verification and responsibility.”
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In other words, the weight of roles shifts upward.
So it can be interpreted not as a reduction in needed headcount, but as a change in the ‘role definition’ of the people needed.
News Briefing 8: The risk that the job-seeking market could move in a ‘worse direction’
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AI adoption itself isn’t the whole problem, but if the direction of change becomes too radical, the disadvantaged group grows.
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When seniors are laid off and enter the market, the number of seats juniors are supposed to fill shrinks even more.
As a result, juniors have fewer places to go and may be pushed toward lower wages and less desirable work. -
The professor emphasizes the reality not only that students can’t get jobs, but that there aren’t internship spots either.
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There are also warnings like “the capacity to discuss social justice disappears and the accumulated proportion of risky outcomes grows.”
‘Most important additional summary for blog readers’ (a point that doesn’t show up elsewhere much)
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In the AI era, competitiveness is about more than “how much AI you use.”
It’s the ability to make the results ‘responsibly valuable’ when you blend in AI (problem definition-delegation-verification). -
From a leader’s perspective, the real bottleneck isn’t “lack of coding staff,” but
the leader’s habit of failing to design delegation step by step.
If you hand everything over at once, or extend time to secure evidence, or do explosive feedback without regular 1:1s, team productivity eventually breaks down. -
Work-life balance label conflict shouldn’t be read as a fight over work-life balance philosophy or a generational issue;
it should be read as a problem of not understanding each person’s motivational drivers and applying the same yardstick. -
Organizational structure isn’t solved by “just adopting AI.”
The key warning is that as boundaries blur, structure can actually amplify collisions.
The main message I want to convey (one-line conclusion)
- In the AI era, ‘work fundamentals (context·problem definition·delegation·verification·responsibility)’ matter more than ‘coding skills,’ and leaders become the people who redesign the organizational structure.
SEO keyword natural inclusion check (as context)
- The core flow of today’s article connects to AI hiring trends, leadership strategies, future industry structure changes, work automation, and digital transformation.
< Summary >
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In Silicon Valley, as AI replaces coding and junior hiring drops, seniors are being laid off too, making entry even harder.
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Even if you use a lot of AI, competitiveness doesn’t automatically appear.
‘The fundamentals of work’—like problem definition, delegation, responsibility, and verification—are key. -
Leaders shouldn’t assign delegation all at once; they must design it step by step and create a culture of “delegating delegation.”
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Uncomfortable feedback improves through curiosity + reducing time lag + regular 1:1 meetings + framing the observation–expected gap.
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Work-life balance label conflict isn’t a generation problem; it’s a matter of understanding motivation, and organizations perform better when they redesign structure to fit the AI era.
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In the end, leadership’s essence (mission·context) stays the same, and the key is that execution methods and organizational structure change.
[Related posts…]
- Silicon Valley’s job crunch and AI transition, hiring structure changes
- Leadership strategies in the AI era: delegation·feedback·organizational design
*Source: [ 티타임즈TV ]
– 실리콘밸리의 개발자 취업난, 얼마나 심각할까? (한기용 산호세주립대 교수)
