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Early studies suggest that AI coding assistants can boost productivity by 26% to 55%. However, newer research highlights a paradox. Experienced engineers working on real codebases can become 19% slower when using AI, even though they perceive themselves to be faster. This session examines this “productivity placebo” and the underlying reasons behind it. The focus is on the cognitive overhead introduced by AI-assisted development, where responsibility shifts from writing code to validation, review, and integration. This shift can increase context switching as developers balance understanding AI-generated outputs with maintaining focus and flow. The session also explores how rapid code generation can introduce downstream costs in debugging and maintenance, and presents strategies to mitigate these challenges.
What You Will Learn
Who Should Attend