How to start when AI can write code faster than you
Every junior engineer asks: if AI can write code in seconds, why should companies hire me? Or better yet, why hire engineers at all if AI writes code faster? Let’s think about it.
Will AI replace software engineers?
I asked this question to the top 5 AI tools. The answers surprised me.
ChatGPT:
AI will not replace software engineers, but engineers who effectively use AI will likely replace those who do not.
Claude AI:
AI won’t replace engineers because engineering is about understanding problems and making decisions, not just typing code.
Gemini AI:
AI will not replace software engineers, but it is fundamentally redefining the role from a manual “code-writer” into a high-level “system architect” and orchestrator who manages AI agents to build increasingly complex systems at unprecedented speeds.
Meta AI:
AI won’t fully replace software engineers, but it will transform their roles by automating routine tasks, shifting the focus to higher-level design, problem-solving, and guiding AI tools.
Perplexity AI:
No, AI won’t replace software engineers — it will augment them by automating routine tasks, but human creativity, problem-solving, and oversight remain essential for complex systems and innovation.
Short answer: no, but the job is changing.
AI is great at writing code. It generates boilerplate, suggests algorithms, catches bugs. For clear problems, it’s fast and capable.
But software engineering isn’t just writing code.
What AI can’t do:
- Understand the real problem — requirements are messy. Engineers translate business needs into technical solutions.
- Make architectural decisions — monolith or microservices? SQL or NoSQL? These depend on context AI doesn’t have.
- Debug complex systems or production breaks — you correlate logs, question assumptions, navigate ambiguity.
- Collaborate effectively —you can do code reviews, design discussions and mentoring. These need human trust and communication.
- Ask the right questions — AI answers what you ask. Knowing what to ask separates good engineers from great ones.
The real shift: AI handles typing. Engineers focus on thinking — what to build and why.
It’s like past tool evolution: assembly → high-level languages → automated testing → AI. Each time, engineers moved to higher-level problems.
Software demand still outpaces supply. AI helps meet that demand rather than eliminate the need for human judgment.
Will AI kill junior engineer positions?
This fear is real. AI is good simple junior tasks — bug fixes, boilerplate code, basic features.
Some companies will hire fewer juniors and the demands on them will continue to grow. But junior roles will not disappear at all.
Why juniors still matter:
- Talent pool — you can’t have all seniors. Companies need to grow future tech leads and architects
- Fresh perspective — juniors question assumptions and identify uncertain aspects
- AI has limits — unclear situations require decision-making skills that develop with experience
What’s changed
The role is transforming, not disappearing. Now, junior engineers need to:
- Have AI skills
- Advance faster with higher expectations
- Move from “write simple code” to “solve simple issues with AI”
- Focus on learning systems design, debugging, and critical thinking
The bar is higher, but the opportunity exists.
Simply put, AI is changing the definition of a “junior engineer”, not whether we need one.
How to build experience for junior engineers in AI era
First of all, blindly copying AI code won’t teach you anything. But intentional learning does.
Use AI as a tutor, not a crutch:
- Try first, AI second (struggle 15–30 min)
- Don’t just accept code. Read every line AI generates. Ask “why this?” and “what are alternatives?”
- Modify and break code to understand it
- After AI helps, delete it and rebuild without help. This proves you understand
- Debug AI mistakes. AI is wrong often
What to do yourself (at least initially):
- Set up dev environments
- Read docs and source code
- Debug with print statements and breakpoints
- Write tests (then let AI suggest edge cases)
- Manual refactoring exercises
Measure understanding, not speed
Can you explain the code? Modify it to meet new requirements? Debug it when it breaks? Make architectural decisions? If not, we haven’t learned anything — we have just copied it.
Changing your thinking
We should treat AI like a 24/7 senior engineer ready to answer our questions, not like someone who’s going to do our job. Let’s use it to accelerate understanding, not bypass it.
Conclusion
In general AI is not enemy, this is an advantage and a powerful learning tool that previous generations didn’t have. Our opportunity is to use it wisely.
Thanks for reading, I hope you found this piece useful. Happy coding!
Resources
AI vs Gen Z: How AI has changed the career pathway for junior developers
Will AI Kill Junior Engineer Jobs? was originally published in Level Up Coding on Medium, where people are continuing the conversation by highlighting and responding to this story.
