AI is now table stakes in software engineering hiring, but it is also warping the signals we used to trust.

In this episode, the AI hosts cover my article about a growing pattern I call “AI-fluent, fundamentally lost”: candidates who can produce impressive output with prompts, yet struggle to explain the logic, constraints, and architectural trade-offs behind what they ship.

The result is a new kind of risk: “glass cannons” that look productive fast, but can drive long-term maintenance cost and technical debt when fundamentals and judgment are missing.

They cover the arguments for a more durable hiring approach that evaluates both system-level reasoning and AI-assisted execution, treating AI as a productivity accelerator, not a replacement for critical thinking ...