It’s time to be right.

A senior AWS engineer argues that the future growth of agentic AI in software development will be constrained more by defect rates than by raw capabilities. Using a four-quadrant framework of defect frequency vs. seriousness, the post explains which user segments can realistically benefit from AI agents today. The author highlights AWS initiatives aimed at improving agent correctness — including spec-driven development (Kiro), formal code reasoning (Strata/Lean), autoformalization (Bedrock AR Checks), and deterministic policy tools — and calls for industry-wide changes: benchmarks that capture failure severity, end-to-end success metrics, a taxonomy of agentic failure modes, and a culture that takes worst-case outcomes as seriously as best-case ones.