AI teams now deploy 1,000 times a month. Your pipeline wasn’t built for that.
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AI adoption has pushed project deployment rates from 357/month in 2021 to over 1,000/month by end of 2025 — a 175x increase. The core argument is that raw speed without direction is wasted: teams need to pair high deployment throughput with tight feedback loops to ensure changes are moving toward the ideal product (the 'Bullseye Model'). Manual stages in deployment pipelines become bottlenecks at this velocity, and deployment governance is critical for regulated organizations. The real competitive edge is no longer AI tooling itself — every team has access to the same tools — but the pipeline's ability to keep pace with code output and close the gap between current and ideal product state.
