AI is the future of the SDLC

Dev Interrupted

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5M ago 35:44

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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.

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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.

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