Source: The Next Web
Greg Brockman's disclosure at Sequoia's AI Ascent conference signals a shift: AI-assisted development has moved from augmenting human engineers to replacing their primary output. This creates a feedback loop where AI-trained models improve on codebases written by previous AI iterations, potentially accelerating capability gains but also concentrating technical debt and architectural decisions within black-box systems that OpenAI's own engineers may struggle to fully understand or audit. The metric matters less as proof of AGI proximity than as a marker of where capital is flowing—enterprises will now measure engineering productivity through code velocity rather than code quality, affecting hiring, skill development, and software development economics.