- Published on
Amazon Kiro replaces ad-hoc prompting with a spec-driven workflow: structured EARS requirements, correctness properties, and property-based tests. The result is AI-generated code you can actually verify against its original intent.
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- Published on
Stanford research across 120k developers shows median AI coding ROI of just 10%, despite millions in tool spending. The variance between teams is massive—and telling.- Published on
Coding evals jumped from single lines to full codebases in four years. Static benchmarks miss the production gap that destroys rollout timelines.- Published on
Lessons from autonomous driving reveal how to make AI agents robust: focus on infrastructure, feedback loops, and simulation over model selection.- Published on
AI coding productivity gains evaporate at enterprise scale. Bloomberg's deployment across 9,000+ engineers reveals why platform thinking matters more than tool quality.