Engineering Intelligence & Developer Productivity in the AI Era
summary
Claims that engineering intelligence platform Oobeya centralizes SonarCloud/SonarQube, Jira, GitHub and CI/CD into team scorecards and an AI assistant that flags risks and suggests fixes. Specific results shown: delivery efficiency +35%, cycle time −24% and predictability +41% after unifying signals. Shows live demo of dashboards, AI chat, and modules that track AI coding-assistant adoption (80% of customers) and measure AI’s impact on quality vs speed.
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chapters (13)
- 0:00Introduction
- 1:15The Importance of Visibility in Modern Software Engineering
- 2:12How Faster Development Increases System Complexity
- 3:57Why Engineering Leaders Still Lack Clear Performance Insights
- 4:22AI Accelerates Development but Doesn’t Reduce Complexity
- 5:51Common Visibility Gaps Across Engineering Teams
- 8:31OB as the Engineering Intelligence Layer
- 9:49Integrating the Full SDLC Toolchain for Better Insights
- 10:40Team Scorecards for Unified Engineering Metrics
- 11:43OB AI Assistant Providing Guided Engineering Insights
- 12:32Analytics Across Projects, Code Quality, and Delivery
- 13:54Tracking AI Tool Adoption and Developer Impact
- 14:32Why Engineering Intelligence Becomes Foundational
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