Luke a Pro

Luke Sun

Developer & Marketer

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05. The Dilemma and Way Out for Junior Engineers: A Realistic Survival Path in the AI Era

| , 5 minutes reading.

The Spread of Anxiety: When AI Steals Your “First Line of Code”

Recently, I have received many private messages from junior engineers, filled with confusion and anxiety.

“Senior, I just graduated, and my daily task is to write some simple CRUD interfaces. Now the company has introduced AI-assisted programming. With one command, the code is generated. I feel completely worthless. Will I be replaced by AI soon?”

This anxiety is not unfounded. AI is indeed extremely good at handling tasks that are highly repetitive, logically clear, and have weak dependency on context. And these tasks happen to be the “training ground” for junior engineers to get started and practice traditionally.

When AI can complete these tasks faster, more stably, and more consistently with standards than you, the “execution” advantage of junior engineers collapses overnight.

AI Won’t Replace Humans, It Replaces “Low-Judgment Roles”

In the first article, we mentioned that AI’s greatest destructive power is not replacing engineers, but creating cognitive illusions. For junior engineers, the biggest risk is that they are easily categorized as “Low-Judgment Roles”.

(Note: “Low-judgment role” here refers to positions designed by the organization to require only execution rather than judgment, not a denial of personal ability.)

Imagine this scenario: A junior engineer receives a task: add a “delete” function to the user management module. He used AI to quickly generate the frontend button, backend API, and database delete statement. The code “looks” flawless.

However, he might not have judged that:

  1. The business requires Soft Delete, not physical delete.
  2. Before deleting a user, it is necessary to check if the user has unfinished orders.
  3. The delete operation needs to log an operation log and notify relevant business parties.
  4. More fatally, if transactions are not handled correctly, it may lead to data inconsistency.

AI assumes by default that your question is correct. It efficiently executes your “wrong” instructions, generating “High-Quality Bugs”. This is scarier than hand-written bugs because it hides deeper and is easier to trust.

Junior engineers lacking experience and global vision can easily become “amplifiers” of AI errors.

The Way Out: From “Knowing One Tech” to “Combinatorial Competence”

So, is there a way out for junior engineers? Of course, but the path has changed.

Recall when I first entered the industry, I always thought about learning a framework deeply and thoroughly, thinking that was the only way to promotion. But in the AI era, I realized that road is becoming narrower.

Junior engineers in the AI era can no longer be satisfied with “Mastering a Framework”. Because the lifecycle of a framework in front of AI may be shorter than you can imagine. AI can master the usage of a new framework in seconds; spending months learning it is no longer cost-effective.

The real way out lies in cultivating “Combinatorial Competence” and “System Vision”:

  • Ability to Solve Complete Problems: You are no longer a “component developer”, but a “small problem solver”. Able to independently understand and solve a problem in a complete business loop from frontend to backend, from database to operations. This does not require you to master every field, but to build an “End-to-End Global Cognition”.
  • Judgment & Critical Thinking: AI gives you 10 solutions; you cannot accept them all. You need to be able to question, filter, and optimize. This is much harder than blindly executing AI-generated code, but also more valuable.
  • Learning and Adaptability: Technology changes too fast; the only certainty is change. Possessing the ability to quickly learn new tools, new frameworks, and new paradigms is more important than mastering any single technology.

Simply put, in the AI era, the survival way for junior engineers is to shift from “Writing Good Code” to “Using Code Well to Solve Complex Problems”.

New Responsibility for Managers: Cultivating “Supervisory Qualification” Instead of “Pure Executors”

For managers, cultivating junior engineers in the AI era is a brand new challenge.

  • Stop treating them as “Pure Executors”: Don’t just assign tasks that AI can easily complete.
  • Provide Context of “Complete Problems”: Let junior engineers contact the full picture of the business from the beginning, understanding the upstream and downstream impacts of the code they write.
  • Deliberately Cultivate the Ability to “Supervise AI”: Encourage them to question AI-generated code and guide them to discover AI’s potential “blind spots” and “hallucinations” through Code Review. This is harder than writing code yourself because you not only have to understand but also know how to “correct errors”.
  • Give “Small Scope Responsibility”: Let them have complete decision-making power within a limited scope. Even if they make mistakes, they can learn from the complete problem loop.

I once had a junior engineer who was assigned to be responsible for a small internal tool. Although this tool was simple, he participated in the whole process from requirement analysis, technology selection, development, testing to launch. A few months later, he grew into one of the members with the most global view in the team because he knew that the birth of a “system” is not just as simple as writing code.

Conclusion: Transcending Code, Embracing Complexity

AI will not replace those engineers with High Judgment and Global Vision; it will only make them stronger.

For junior engineers, this means you need to detach from code details faster and cast your eyes Beyond Code: the real needs of the business, the operating logic of the system, and the collaboration boundaries of the team.

In the AI era, the survival path for junior engineers is no longer “How much code can I write”, but “How complex a problem can I solve independently and be responsible for the result”. This is a shift in mental model, not a simple skill upgrade.

If an organization in the AI era only thinks about “hiring fewer newcomers” without thinking about “how to cultivate judgment”, it is simply overdrawing the future.