Labs: Everything You Need to Know About Software Engineering Intelligence (SEI)

Engineering leaders have long used value stream management and CI/CD tools to improve software delivery practices. However, an increasing demand for cost and efficiency is leading to the adoption of new technologies. Enterprises are quickly adopting tools that combine deeper levels of visibility into the SDLC with net-new workflow automations, leading to a better developer experience and increased output. 

This week's labs episode takes an in-depth look at Software Engineering Intelligence (SEI) Platforms and how engineering teams are using this new technology to gain a competitive advantage. LinearB’s COO and Co-founder Dan Lines along with co-host Conor Bronsdon cover the evolution of SEI, its core capabilities, and how these tools are being used to drive predictability, resource investment strategy and an improved developer experience. 

Join our journey into the data insights and workflow automations that are driving the next wave of continuous improvement. Gartner estimates that the adoption of SEI platforms will increase to 50% of engineering teams by 2027 – whether you're a VP, manager, or developer, find out why adopting an SEI Platform is crucial to your future success.

Episode Highlights:

• 2:39 Digging into the data to find optimizations 
• 4:02 What is Software Engineering Intelligence (SEI)? 
• 9:08 What is profitable engineering and why should it be top of mind? 
• 14:56 How can SEI help a VPE or CTO? 
• 20:43 How does SEI relate to value stream management? 
• 25:05 The role of automation in continuous improvement 
• 29:36 How do SEI platforms help improve GenAI code orchestration? 
• 31:45 What makes a great SEI platform? 
• 34:19 What's next for SEI?

Show Notes:

• Moneyball (2011) directed by Bennett Miller • Reviews, film + cast • Letterboxd
• Download your complimentary Gartner® Market Guide: Software Engineering Intelligence (SEI) Platforms

OFFERS

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LEARN ABOUT LINEARB

• AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production.
• AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance.
• AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil.
• MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.