Dan Lines, co-founder of LinearB, joins to discuss the transformative potential of AI in software development. He reveals how intelligent automation can save up to 75 days of work in just six months. Dan emphasizes the importance of programmatic rules to safely integrate AI, detailing his company's gitStream technology that optimizes code reviews and automates low-risk merges. They also explore future AI workflows, envisioning a world where AI handles everything from design to deployment, enhancing developer control and productivity.
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insights INSIGHT
AI Adoption Lacks Cohesive Strategy
Many engineering leaders buy AI tools due to pressure rather than a cohesive strategy.
Without coordination, AI adoption may not improve productivity as expected.
volunteer_activism ADVICE
Control AI Use via Policy Rules
Use programmatic rules to control AI use across development safely.
Tailor AI powers by service risk level, enabling human review or safe merges as appropriate.
insights INSIGHT
AI Future in SDLC Workflows
AI in software development is evolving beyond simple code assistants to automated workflows.
Future AI may autonomously handle design, coding, review, and deployment, making control essential.
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Imagine saving as much as 75 days of work within a six-month period, all through intelligent automation.
Building on last week’s discussion about the critical shift from passive metrics to active productivity, host Ben Lloyd Pearson and LinearB co-founder Dan Lines now look forward to realities like this: 19% cycle time reduction and reclaiming significant engineering time. They move beyond common narratives surrounding AI to present actionable success stories and strategic approaches for engineering leaders seeking tangible results from their AI initiatives.
This concluding episode tackles how to safely and effectively adopt AI across your software development lifecycle. Dan explains the necessity of programmatic rules and control, detailing how LinearB's gitStream technology empowers teams to define precisely when, where, and for whom AI operates. This ranges from AI-assisted code reviews with human oversight for critical services, to enabling senior developers to make judgment calls, and even automating merges for low-risk changes. Ben and Dan also explore the exciting future of agentic AI workflows, where AI agents could manage tasks from design and Jira story creation to coding and deployment, making developer control even more critical.
Dev Interrupted