I recently interviewed some fresh graduates and noticed an interesting pattern.
The projects on their resumes looked impressive:
- Beautiful UI
- Modern tech stacks
- AI-powered features
- Clean GitHub repositories
At first glance, they looked like strong candidates.
But when we started discussing their projects:
- Why did you choose this architecture?
- How does this API work?
- What challenges did you face?
- How would you scale this?
- What happens if this component fails?
Many struggled to explain their own work.
This made me think:
AI has lowered the barrier to building software, which is great.
But are we changing how we evaluate developers?
Maybe a project demo is no longer enough.
The real evaluation should focus on:
- Understanding of fundamentals
- Problem-solving approach
- Ability to explain decisions
- Debugging skills
- Ownership of the work
AI will help developers build faster, but understanding what they are building and why still matters.
Curious to hear from hiring managers and developers:
How are you evaluating fresh graduates in the AI era?