Tech Leaderism

AI Vanity Metrics

AI adoption in software development is accelerating, but so is skepticism among developers. Management often celebrates impressive numbers, but many engineers see through these vanity metrics that look good in presentations but don't reflect the reality of building software.

Counting lines of code generated by AI is a common example. Management may report a large percentage of code written by AI, but more code is not necessarily better. AI can produce verbose, redundant or buggy solutions, increasing maintenance costs.

Ticket closure rates and sprint velocity are often cited. Closing more tickets does not guarantee that the right features are delivered or customer problems are solved.

Claims about time saved per developer can also be misleading. The time saved is often spent debugging or rewriting AI-generated code, reducing actual benefits. Similarly, adoption rates and flashy demos can look impressive without proving real value or scalability.

Better indicators of AI's value include bug rates, avoided defects, code review burden, and overall cycle time from idea to production. Security issues, maintainability, scalability and technical debt are also critical, as is developer satisfaction. If engineers are productive, creative and supported, AI adoption is genuinely adding value, if not, the tools are failing.

Developers resist when AI adoption is justified by meaningless numbers and when hidden costs like review time, debugging and technical debt are ignored. As one developer wrote in Reddit: "AI sort of becomes a management tool, not a developer tool". Vanity metrics create friction by making AI a selling proposition rather than a productivity boost.

AI can significantly augment development, but only if companies measure meaningful outcomes. Leaders should ask whether AI improves reliability, reduces time-to-market, addresses customer needs and expectations and genuinely boosts developer productivity.

Shifting from vanity metrics to actionable metrics is essential. Only then can AI move from hype to genuine impact.