Let’s be real, you don’t need more than 1 hour for a proper technical interview.
The way most companies are doing interviews right now? It’s embarrassing.
They completely miss the point of what makes someone a good software developer. And don’t even get me started on how out of touch they are with the current state of AI.
Want to run an effective interview? Want to find out if someone not only has experience but also knows how to use modern AI tools to boost their work?
Here’s the process. One hour. That’s all it takes.
🔹 First 20 minutes: Let’s talk past projects
Ask about the candidate’s previous experience. Dive a bit into the projects they mention. This alone tells you a lot, what kind of challenges they’ve faced, how deep their experience goes, and how they think about solving problems.
Important: before the interview, send them a starter project (depending on the stack) so they can clone it and have it ready.
🔹 Next 40 minutes: Live coding, but make it real
Now here’s where it gets interesting, build a feature live, inside that starter repo.
But with a twist, let them use AI tools, VS Code with Copilot, Cursor, Windsurf, ChatGPT, Claude, Grok, whatever they want.
Autocomplete, AI prompts, agent mode, copy paste, search on the internet, it’s all fair game.
What matters isn’t if they use AI, it’s how they use it.
As they build:
- Ask about the code the AI generates, go deep on the candidate explanations about it.
- Look at the way they prompt. Are they treating the AI like magic, or are they in control? Do they give clear instructions about architecture, refactors, patterns?
You’ll quickly spot the difference between someone who leads with intention and someone who’s just hoping the AI does it all for them.
So what’s the catch?
Simple, this kind of interview only works if the interviewer actually knows the craft.
That means real technical experience, and being up to speed with modern AI workflows. If you don’t know how these tools work, you won’t know what to look for.
Conclusion
Cut the nonsense, skip memorized LeetCode problems that won't have any impact on the actual job. Focus on what matters, real world experience and modern tools.
That’s it.
Yes, it really is that simple.
Top comments (5)
Excellent post, Joaquin. This should be the new standard.
You've nailed it: the senior skill is no longer memorizing algorithms but auditing AI-generated code.
Thanks for outlining this. It's time to stop testing for memorization and start testing for accountability.
“... senior skill is no longer memorizing algorithms but auditing AI-generated code.”
Sure, but it was never really about memorization. Seniority has always been about understanding fundamentals and inner workings so you can judge scalability, reliability, and trade-offs.
That part hasn’t changed with or without AI.
My permanent concern is the classic Asimov-style scenario: people using powerful tools they don’t truly understand. In this case developers trusting code they don't fully understand.
That's a great point, Gerardo. You're right, it was never really about memorization, but about knowing the fundamentals.
I think the AI just makes it easier for people to skip that step. We'll see more code written by developers who don't truly understand it, which is the exact risk you're talking about.
It just reinforces the main idea: the person who does understand the fundamentals (the auditor) is the most important one in the room.
Good clarification, thanks.
Totally agree, I think we all know that, but at some point to speed up recruiting we end up on the ridiculous leetcode problem solving, and all went downhill from there.
The critical part in this era as you mentioned is that developers should fully understand the AI generated code, there is where you can detect seniority, and where I think the focus should be.
Thanks for the comment!
Thanks much for this comment Emilio, and thanks for reading!