We're noticing a recurring trend in the tech industry: more and more companies are implementing policies to prohibit the use of ChatGPT and similar AI tools during technical interviews.
Here’s the kicker — developers are already using AI tools every day on the job. So why block them during interviews? It’s like asking a carpenter to build a table without a hammer… to “see how skilled they really are.”
We’ve tested the opposite: allowing AI in interviews. ChatGPT, search engines, docs — all fair game. The results?
Good developers still shine. Bad developers still flop.
AI doesn’t magically turn weak candidates into strong ones. But it supercharges the good ones.
What AI-Allowed Interviews Actually Reveal:
💡 How candidates approach problem-solving.
You get a clearer window into how someone breaks down a challenge, identifies what they don’t know, and decides how to move forward — all essential traits for real-world engineering.
💡 The quality of the prompts they write.
Prompting is a skill. Watching how a candidate structures their queries to AI tools tells you a lot about their clarity of thought, technical vocabulary, and strategic mindset.
💡 Whether they trust AI blindly or think critically.
Not all AI output is accurate — and a strong candidate knows that. The best ones double-check, debug, ask “does this make sense?” and show you how they validate results rather than just copying and pasting.
💡 How they combine tooling with judgment.
It’s not about replacing skill with shortcuts. It’s about showing judgment, using tools to accelerate the right things, and knowing when to step in manually. That’s what great engineers do.
It’s not just about whether someone knows an answer — it’s whether they know how to get to it efficiently, using the tools they'll be using on the job.
Here’s What We Recommend:
✅ Embrace AI tools in business-focused coding interviews.
Rather than banning them, give candidates access to the same tools they’ll use on the job — whether that’s ChatGPT, GitHub Copilot, or something else.
✅ Pay close attention to how candidates interact with those tools.
Are they using AI to boost their problem-solving? Can they prompt well, validate output, and debug intelligently? These are the skills that matter in real-world development.
✅ Shift focus away from rote memorization and textbook problems.
Knowing how to reverse a linked list without help is fine, but it rarely reflects the day-to-day of modern software development. Prioritize evaluating how someone thinks, not just what they’ve memorized.
✅ Treat AI usage as part of the signal — not a red flag.
A candidate who can effectively collaborate with AI is showing resourcefulness, adaptability, and modern engineering habits. Those are assets, not liabilities.
The real value isn’t whether a candidate can write an algorithm from memory — it’s whether they can ship a feature, solve a problem, and deliver results in today’s tool-rich world.
One Thought to Sit With:
If someone uses ChatGPT so well that they pass your interview and deliver results…
does it matter they didn’t do it alone?
Great devs leverage tools. And AI is just another (very powerful) tool.
👉 Know a fellow tech lead or hiring manager who needs to hear this? Share this issue with them.
Thanks for reading,
CTO Teachings