The 8 levels of context maturity in AI-native engineering

AI usage is up 65%. Pull request throughput is up 7%. This webinar explains the gap, and how to close it.

Brandon Waselnuk walks through the eight levels of context maturity engineering teams move through on the way to autonomous agents, from tab complete to agent teams, and the GATE framework for levelling up safely. The session ends with live Q&A on skills, CI pipelines, draft PRs, security, and data residency.

What you'll learn

• Three common approaches that don't work. Curated rules files, MCP sprawl, and unattended background agents each give a lift and then hit a glass ceiling.
• How to measure AI productivity in ten minutes. Cycle time, review time, rework, and defect escape rate, baselined from your own Git history.
• Six requirements of a real context engine. Unified system context, targeted retrieval, conflict resolution, personalized relevance, permission enforcement, and token optimization.
• Where your team stands. You don't need level 8. You need to know where you are and what it takes to reach the next level.