Everything You Need to Know About Software Engineering Intelligence (SEI)
Plus, don't copy/paste from other companies, the fuzzy space for making mistakes, and the best/worst programming languages for dev workflow.
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
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.
“You're getting pressure to deliver projects on time. You're getting pressure to take, the millions of dollars in workforce that you have and ensure they're working as efficiently as possible and then report that back to the board. You're getting pressure to make sure that the developer's experience is fantastic, because these folks can work anywhere they want in high demand, right?
So if you're the VP of Engineering, I think software engineering intelligence helps you push one of your initiatives that would have been very difficult to do without data.”
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?
The Download
The Download is engineering leadership content we’re reading, watching, and attending that we think you might find valuable.
1. Explaining Software Development Methods By Flying to Mars [Comic]
2. Don't Copy/Paste From Other Companies
We’ve all done it – we see a company succeeding using a specific methodology and instantly think we could apply it to our team to achieve the same outcomes.
’s article emphasizes the pitfalls of copying organizational structures from other companies without considering the underlying principles and context that made them successful. Effective organizational change requires understanding and integrating the values and principles that drive the methods, rather than merely replicating surface-level structures.
Complimentary Gartner Guide to Software Engineering Intelligence Platforms (Sponsor)
Engineering teams are rapidly adopting Software Engineering Intelligence (SEI) Platforms to improve engineering team productivity and value delivery. According to Gartner’s recent Market Guide, the use of SEI platforms by engineering organizations will rise to 50% by 2027, compared to 5% in 2024.
Get ahead of the curve, and learn how you can unlock the transformative potential of SEI platforms by leveraging key features like:
Extensive data from DevOps tools for critical metrics and insights.
Customizable dashboards that highlight pivotal trends and inform strategic decisions.
Insights into key performance indicators that showcase your team's achievements.
3. The Fuzzy Space for Making Mistakes
Fear of making minor mistakes will stop your team from innovating and learning.
’s latest piece highlights the importance of creating a "fuzzy space" for making mistakes, and why errors are opportunities for learning and growth.She advocates for fostering a culture of open communication, celebrating learning, setting clear expectations, providing support, and leading by example to reduce fear and pressure around making mistakes.
4. Labs: The Best & Worst Programming Languages For Dev Workflow
We’ve been using our Labs episodes as a platform for exploring engineering trends and data, and one of our most popular is our episode on the best and worst programming languages for dev workflow.
In this episode, LinearB’s CTO Yishai Beeri revealed what LinearB’s data scientists discovered about programming-language productivity from analyzing thousands of dev teams and hundreds of thousands of pull requests.
Upcoming Events
Software Engineering Intelligence: Exposed & In Action
June 27th | Online
Highlights: How can you drive developer productivity, lower costs and deliver better products? On June 20th and 27th, LinearB is hosting a workshop that explores the software engineering intelligence category.