I recently passed the first stage of a job interview, and the next steps are system design and live coding. When I opened my IDE to write a simple Python program from scratch, I unexpectedly struggled to get started. I've been relying heavily on AI to generate code at work, while I mainly review, debug, and adapt the results. I still understand the code when I read it and can predict its behavior, but I've become rusty at producing basic syntax and structure without an example. I've worked in DevOps and systems administration for more than 15 years, and although coding has always been part of my role, I haven't regularly written complete programs from the ground up in a long time. How would you prepare for a live coding interview in this situation? What exercises or resources would help rebuild fundamental skills and confidence? I'd also like to hear what kinds of practical tasks senior DevOps or SRE candidates are typically given.
4 Answers
A useful approach is to reverse the usual AI workflow. First write the solution yourself, even if it’s rough, then ask AI to review it, identify bugs, and suggest improvements without replacing the whole solution. You can also create practice tasks from the job description and solve them under a time limit. For a senior DevOps role, include troubleshooting, parsing logs, working with JSON, writing small automation tools, and explaining design tradeoffs.
I had a similar experience after spending years focused on architecture and reviewing other people’s work. Writing from a blank file felt surprisingly difficult, but the skill came back faster than expected. Practice small problems every day: conditionals, loops, data structures, file handling, API calls, and simple automation scripts. Focus on explaining your reasoning and testing your work rather than trying to write everything perfectly from memory.
The ability to understand and verify generated code is valuable, and developers shouldn’t be judged solely on whether they type every character manually. That said, a live interview may intentionally test fundamentals, so it’s worth practicing without assistance. Use AI after each exercise as a reviewer or tutor rather than as the author of the solution.
There is a real tension between modern workflows, where engineers are expected to use AI productively, and interviews that require unaided coding. Prepare specifically for the format you’ll face: clarify requirements aloud, sketch the approach, write a small working version, test edge cases, and discuss how you would improve it. Even if the final code isn’t perfect, demonstrating sound thinking and system awareness can matter a lot.
That makes sense. I’m comfortable reviewing and improving code, but I need to regain the muscle memory for starting from a blank page and building a simple solution step by step.