I understand why so many people are questioning software engineering right now.
Every week there’s another headline saying AI will replace developers.
Junior engineers are worried there won’t be jobs.
Senior engineers are wondering how long their experience will stay valuable.
And honestly, if you spend enough time on tech Twitter or LinkedIn, it can start feeling like the industry is collapsing in real time.
But after using AI heavily in my day-to-day work as a software engineer, I’ve started seeing things differently.
AI didn’t make me feel less useful.
It made me feel more capable.
Before AI became part of my workflow, a lot of engineering time disappeared into things that were mentally draining but necessary:
- repetitive refactoring
- debugging small issues
- writing boilerplate
- digging through documentation
- trying to remember syntax
- cleaning up legacy code
- writing SQL queries
- optimizing simple functions
- translating vague tickets into technical tasks
None of these tasks were impossible.
They were just time-consuming.
Now, a lot of that friction is reduced dramatically.
One of the biggest changes I noticed was backlog cleanup.
Tasks that used to sit untouched because nobody wanted to deal with them suddenly became manageable.
Not because AI magically solved everything.
But because it helped reduce the “mental startup cost” of difficult tasks.
Sometimes all you need is:
- a starting point
- a refactored example
- help understanding unfamiliar code
- a faster debugging path
- quick documentation summaries
That momentum matters more than people realize.
A task that feels overwhelming at 9AM suddenly becomes achievable when AI helps break it down.
I also noticed we started delivering faster as a team.
Not in a “replace developers with AI” kind of way.
More in a:
- less context switching
- faster research
- quicker prototyping
- fewer hours stuck on repetitive problems
- better ticket breakdowns
- improved communication
kind of way.
The interesting part is that AI didn’t just help with coding.
It helped with thinking.
I’ve genuinely started thinking more like a project manager because of AI.
Not because I stopped engineering.
But because I spend less time fighting small implementation details and more time thinking about:
- priorities
- tradeoffs
- user impact
- scalability
- timelines
- technical debt
- delivery strategy
AI handles enough of the repetitive workload that I have more mental space for higher-level decisions.
And honestly, I think that’s where software engineering is heading.
The value of developers won’t disappear.
The value will shift upward.
The engineers who become most valuable over the next few years probably won’t be the ones writing code completely manually.
They’ll be the ones who know:
- how to guide AI effectively
- how to validate output
- how to make architectural decisions
- how to communicate clearly
- how to combine engineering with product thinking
Because generating code is only one part of building software.
Real-world engineering still involves ambiguity, responsibility, tradeoffs, and human decisions.
AI helps with execution.
But humans still decide direction.
I honestly think this is one of the most exciting times to become a software engineer.
Not because AI makes the job easy.
But because developers now have tools that can massively increase their leverage.
The industry is changing fast.
That part is true.
But software engineering has always evolved.
And the people willing to adapt usually end up ahead.
So if you’re considering software engineering as a career, don’t focus only on whether AI can write code.
Focus on whether you’re learning how to use the most powerful development tools we’ve ever had.
Because the worst time to quit software engineering might be exactly when the industry is transforming the fastest.
