No, AI is not Making Engineers 10x as Productive

Claims that AI has made engineers 10-100x more productive are widespread but misleading. True productivity gains require improvements across all stages of software development, including ideation, review, testing, and deployment—not just coding speed.

The human processes in engineering, like code reviews and product management, remain bottlenecks. Even if AI accelerates code writing, these collaborative and iterative steps cannot realistically be compressed tenfold without sacrificing quality or feasibility.

AI excels at generating boilerplate code and simple scripts, especially in popular languages like JavaScript and React. However, it struggles with complex codebases, less common libraries, and maintaining coding standards, often producing hallucinated or insecure outputs.

Real 10x engineers typically achieve their productivity by preventing unnecessary work, improving developer experience, and fostering better team communication—not merely by coding faster. AI tools currently do little to reduce redundant or poorly scoped tasks.

The math behind 10x productivity is daunting: completing three months of work in just over a week would require every aspect of the development pipeline to be equally accelerated, which is practically impossible given current workflows and human factors.

Many claims of AI-driven productivity come from secondary sources like managers or investors who may have incentives to exaggerate benefits. Primary accounts from engineers show AI as a helpful but imperfect assistant requiring active human oversight.

Using AI for coding can produce short bursts of speed, such as quickly generating a custom ESLint rule, but these gains do not scale across all tasks. Over time, diminishing returns set in as codebases grow and complexity increases.

It is perfectly acceptable to choose coding methods that prioritize enjoyment and craftsmanship over marginal productivity gains. Sustained motivation and quality often matter more than speed, and forcing AI usage can lead to burnout or suboptimal results.

Leaders should avoid pressuring engineers with unrealistic 10x AI productivity expectations. Such pressure can degrade code quality, increase technical debt, and harm morale. Trust and balanced workflows foster healthier, more sustainable engineering teams.

In conclusion, there is no secret AI revolution making engineers superhuman overnight. AI is a useful tool but not a magic bullet. Engineers should trust their skills, focus on meaningful work, and ignore hype-driven anxiety often amplified by social media.