LinearB Blog | Insights and Best Practices for Software Engineering Leaders

Closing the AI gap: How to measure adoption and impact in engineering (without falling into the ROI trap)

Measure AI adoption and impact in engineering with usage visibility, throughput + quality metrics, and credible ROI narratives grounded in delivery data.

A guild, not a mandate: Superhuman's blueprint for AI success

Superhuman's Loic Houssier shares a blueprint for driving bottom-up AI adoption by overcoming skepticism with a trusted internal champion, fostering an AI...

AI as a value multiplier: a human-centric approach to engineering leadership

Super.com's Matt Culver explains why AI should be used as a value multiplier, not a cost-cutter, advocating for a human-centric approach to engineering...

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Vector databases: the essential foundation for reliable AI applications

Pinecone's Ram Sriharsha explains why vector databases are the essential foundation for reliable AI applications, enabling RAG for trustworthy output and...

Enterprise vibe coding: how Salesforce balances speed with governance

Salesforce's Dan Fernandez details the Enterprise Vibe Coding strategy, explaining how to balance the speed of agentic AI with governance by using a Trust...

How CloudFlare adopted MCP and made it enterprise-ready

Cloudflare adopted the Model Context Protocol (MCP) and made it enterprise-ready by using a "customer zero" dogfooding philosophy, leveraging observability as...

The creator of the iPhone keyboard on building transcendent AI

Ken Kocienda, creator of the iPhone keyboard and autocorrect, details his disciplined approach to generative AI and explains how extractive AI and "evolutionary...

Specialized intelligence in AI applications: bridging research with real-world impact

Elizabeth Lingg from Contextual AI details her methodology for building specialized AI applications, explaining how to bridge the gap between research and...

Dialing up determinism: building production-grade AI

Alex Salazar from Arcade reveals the four "demo killers" that prevent AI agents from reaching production and explains how embracing constraint and determinism...

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