Opinion: Vibe Coding and Junior vs Senior Engineers — the Illusion of Skill in the AI Era

The emergence of AI in the software engineering world changed many things — coding speed increased drastically, access to solutions became easier to obtain, and the learning curve feels shorter than before. But along with that, a new phenomenon appears worth watching out for: junior engineers can look like senior engineers, without necessarily being so. This phenomenon is often closely related to vibe coding, especially when AI becomes the main tool in writing code. This article discusses how vibe coding affects juniors and seniors differently, why juniors can “look” senior, hidden risks for teams and organizations, and how to address it healthily.

Vibe Coding and the Illusion of Competence

With AI assistance, the produced code can look neat, the implementation appears complex, and features can be completed quickly in a much shorter time than before. However, a good-looking final result doesn’t always reflect the level of understanding of the person who produced it. This is what creates the illusion of competence — an illusion where the external appearance of work output doesn’t align with the actual understanding behind it.

This illusion of competence phenomenon isn’t new in the working world in general, but AI makes it far easier to happen in software engineering specifically, because AI can produce code with visual quality equal to code written by experienced engineers, without the same thinking process behind it.

How Junior Engineers Get Trapped in Vibe Coding

Fast Output, Shallow Understanding

Junior engineers who rely too much on AI and vibe coding often only focus on “code that works”, without truly understanding the reasoning behind each design decision taken, and end up struggling to explain the trade-offs of the approach used. This symptom usually only becomes clearly visible when deeper follow-up questions come: why choose this approach over other alternatives, what’s its impact on system performance, or how will this solution survive if traffic rises significantly. Answers to such questions are often not solid, because the junior never actually decided on that approach — the AI decided, and the junior just accepted the result.

Never Trained to Think in Systems

Senior engineers are generally trained to think about system boundaries, failure scenarios, and the long-term impact of a technical decision taken. Juniors who too often use vibe coding without control tend to see problems locally — only focusing on the code snippet being written, without thinking about its implications for the system as a whole — and often avoid the design process at the start because it feels slower than directly asking AI to produce a solution.

flowchart TD
    A[Engineer faces a problem] --> B{Way of thinking}
    B -- Senior --> C[Think about system boundaries, failure scenarios]
    B -- Junior with excessive vibe coding --> D[See the problem locally]
    C --> E[Solution considers long-term impact]
    D --> F[Solution only solves the surface problem]

Depending on AI as the Decision Maker

The main problem in this pattern actually isn’t the AI itself, but the position of AI in the thinking process of the engineer using it. If the AI determines the architecture, the AI determines the design patterns used, and the AI determines the application logic flow — then the engineer in question is essentially only acting as an operator executing instructions, not as a decision maker who truly understands and is responsible for the decisions taken.

The clearest sign of excessive AI dependency isn’t the speed of writing code, but the inability to explain why a particular approach was chosen. If the only answer that can be given is “because AI suggested it this way”, that’s a signal that technical thinking didn’t really happen.

Why Juniors Can Look Like Seniors?

Code Looks “Mature”

AI tends to produce code with good naming, neat structure, and popular patterns like the repository pattern or service layer. Visually, this result can make anyone looking at it think “this looks like senior code”. Yet, behind that appearance, the junior who produced it often doesn’t know why that pattern is used in a certain context, and more importantly, doesn’t know when that pattern is actually unsuitable or even wrong to use.

Output-Based Reviews, Not Reasoning-Based

In many teams, the code review process tends to focus on the final result — does the code work, does it pass tests, does it match the style guide — while questions about “why” the approach was chosen are rarely asked deeply. The reviewer’s understanding of the code author’s thinking process is also rarely truly tested. This review pattern lets juniors with shallow understanding still pass review, their code goes to production, and on the surface they look competent — even though genuine competence may not be there.

Seniors Too Focused on Speed

High delivery pressure often makes senior engineers accept AI-produced solutions as-is, as long as the code works and produces no errors, while deep design discussions are sacrificed to chase deadlines. In the long term, this habit harms the team as a whole — not because of one big wrong decision, but because of the accumulation of many small decisions, each of which feels reasonable to sacrifice for speed, until the team’s collective quality declines without anyone noticing.

How Senior Engineers Use Vibe Coding

Senior engineers also use vibe coding — that doesn’t mean they’re immune to the temptation of AI’s speed. The difference isn’t whether they use vibe coding or not, but the control and awareness accompanying it.

Senior engineers usually know when produced code is throwaway and won’t be maintained, know when to do a total refactor instead of just polishing AI output, and know where exploration ends and engineering discipline must begin. This awareness is what distinguishes healthy vibe coding usage from risky usage, not just how often AI is used in the code-writing process.

Bad Impacts If Left Unchecked

Invisible Technical Debt

Code from the combination of AI and vibe coding often looks neat visually, but is structurally fragile and hard to develop further. Technical debt from this pattern usually doesn’t appear immediately — it’s only felt later, when the system grows, the team gains members, or the needed features get more complex than previously imagined. Because of this delayed impact, this type of technical debt is often more dangerous than more visible technical debt, because there’s no clear early warning signal until the problem is already large enough.

Juniors Never “Level Up”

Without consistent design discussion, architectural reasoning, and failure scenario analysis, junior engineers risk stagnating in their career development. They’ll struggle to become true seniors — not just seniors in title or tenure — and won’t be ready to lead more complex system design in the future, because the core abilities needed for that were never truly trained.

Seniors Lose Their Mentoring Role

If senior engineers only do quick reviews then approve output without digging deeper, the knowledge transfer from senior to junior doesn’t really happen, and the engineering culture within the team gradually weakens. The mentoring role that should be one of the senior engineer’s greatest contributions to team growth goes unused, even though this is one of the most important values brought by senior experience.

The Solution: Shifting Focus from Output to Reasoning

Reviews Not Just “What”, But “Why”

Get used to asking questions that dig into the thinking process, not just checking the final result: why was this structure chosen, what other alternatives were considered, and under what conditions will this solution fail. Such questions force the code author to truly rethink their decisions, and quickly reveal whether the understanding behind the code really exists or is just a result that “looks correct”.

Separate the Exploration and Production Phases

Vibe coding suits the exploration phase, while structured coding — with consciously thought-out design — is needed for code that will go to production. Don’t mix these two phases without a clear transition, because this mixing is often the source of problems: exploratory code written quickly ends up being directly used as a production foundation without ever being redesigned.

AI as a Teaching Tool

Use AI to compare various possible approaches, explain the trade-offs of each option, and analyze the impact of a technical decision — not as a single source of truth whose answers are accepted as-is without questioning. Using AI this way actually accelerates the learning process, because AI can explain the reasoning behind an approach quickly, as long as the user indeed asks for that explanation, not just for finished code.

Seniors Must Become “Design Guardians”

The senior engineer’s role isn’t writing the largest amount of code, but maintaining the quality of thinking within the team. A good senior lets juniors explore freely, but still challenges the reasoning behind every decision taken — this role is far more valuable than just being the fastest code contributor in the team, because its impact is felt across the whole team, not just on one feature being worked on. The time investment in challenging juniors’ reasoning early in their careers usually pays off many times over in the long run, because juniors trained to think deeply will be far more ready to handle greater complexity later, compared to juniors used to accepting AI output without ever being questioned.

Summary

• Vibe coding with AI assistance creates an illusion of competence — code can look neat and complex without reflecting actual understanding.
• Juniors who rely too much on AI often can’t explain trade-offs, see problems locally, and make AI the decision maker instead of themselves.
• Juniors can “look” senior because AI code looks visually mature, code reviews often only focus on output, and seniors themselves are sometimes too focused on chasing delivery speed.
• The difference between senior and junior isn’t whether they use vibe coding, but control, trade-off awareness, and the ability to distinguish throwaway code from code worth maintaining.
• Left without control, this pattern accumulates invisible technical debt, makes juniors stagnate, and removes the senior’s mentoring role.
• The solution: focus reviews on reasoning not just output, separate the exploration phase from production, use AI as a teaching tool, and position seniors as design guardians.
• A mature engineer isn’t the one who writes code fastest, but the one most aware of the consequences of every technical decision taken.