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After some time learning programming, a developer gradually exits the beginning phase — the one where they heavily relied on imitation: watching a project and replicating it, following tutorials step by step.

This isn't wrong. It's a natural and essential part of the beginning.

But with time a shift begins: reliance on imitation decreases and attempts to build things independently emerge. This is where the sensitive phase starts.

Over-Relying on Self Before the Foundation Is Complete

After reducing reliance on external guidance, an internal feeling of independence begins: "I must understand everything on my own."

But this is where the imbalance happens. Because this phase is still too early for complete self-reliance. The foundation isn't complete yet.

The problem isn't relying on yourself — it's turning it into an absolute rule. The programmer still needs a balanced mix of experimentation, research, and learning from others.

When this balance breaks: complex solutions for simple problems, reinventing existing solutions, unreasonably slow progress.

Partial Understanding of Core Concepts

In this phase, programming concepts start being used with greater confidence but partial understanding.

Take "code reuse" — it gets treated as a fixed rule: if code repeats, convert it to a function. But in reality, reuse isn't a mechanical rule — it's a design decision that depends on context.

This partial understanding creates a false sense of mastery.

Facing Real Problems for the First Time

Until now, most of what was learned was within a structured environment: clear problems, defined steps, expected solutions.

But when entering larger projects or a real work environment, the picture changes completely. The problem is no longer "code that doesn't work" — it's a complete system with interconnected parts and unclear causes.

This is where the difference between theoretical training and real experience becomes apparent.

Chasing Perfection Before Being Able to Build

A common mistake is trying to reach perfect code in a phase where the foundation isn't even complete yet.

Focus shifts to perfect design and perfect organization before a complete project even exists. The goal transforms from "building" to "improving something unfinished."

Over-Relying on AI

Using AI as an assistive tool is very useful. But the problem starts when it becomes a substitute for thinking.

Ready-made solutions are accepted without understanding them, or used to bypass the analysis process entirely. This creates a dangerous gap: code that works but without real skill behind it.

Anxiety From Noise Around You

In this phase, programmers start getting distracted: any opinion becomes a source of anxiety. "This language is dying." "This field is no longer in demand."

The problem isn't the existence of opinions. It's treating them as facts.

If a programmer wants to know a language or technology's standing in the job market, there's one clear measure: job platforms. They directly reflect reality. For over 20 years the same predictions repeat — and many languages predicted to vanish are today more widely used than ever.

The Real Collision with the Job Market

When attempting to enter the job market, the full picture becomes clear. The question is no longer "do you know programming?" It's "what can you contribute inside a real team or project?"

Companies don't just look for someone who writes code — they look for someone who understands the problem, works within a team, and adds clear value.

This is where programmers discover that technical skills alone aren't enough.

The phase after the first year isn't a phase of knowledge shortage. It's a phase of reshaping how you think. Real growth doesn't come from complete isolation or complete dependence. It comes from the balance between both at the right time.