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The 2025 Stack Overflow survey reveals how autonomy and AI are reshaping development

Erin Yepis of Stack Overflow analyzes the 2025 Developer Survey, detailing the AI paradox (high adoption, falling trust), the critical importance of autonomy...

The AI maximalist: why engineering leaders need to invert their thinking

Kubernetes co-creator Craig McLuckie advocates for the "AI Maximalist" philosophy, urging engineering leaders to invert their thinking by asking "Why can't we...

Here’s where AI coding agents are delivering reliable code refactoring

New research analyzing 15,000+ AI refactorings reveals agents excel at routine cleanup but struggle with architectural changes. Learn where AI delivers value...

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Speed as a moat: building the open innovation engine at AMD

AMD's Anush Elangovan reveals why speed of innovation is the only true moat in AI, detailing how the open-source ROCm stack fosters an "innovation flywheel"...

Product

Measuring the impact of Copilot and Cursor on engineering productivity

Track GitHub Copilot and Cursor adoption, usage, and ROI in one unified LinearB dashboard. Correlate AI metrics with delivery performance and outcomes.

Is the future of AI development spec-driven?

Amit Patel, Director of Software Development for AWS Kiro, explains why spec-driven development is the future of AI development, solving the context loss...

The new engineering leader: navigating AI as a core business metric

Lake Dai, a globally recognized AI expert, explains why the modern CTO must adopt the financial acumen of a CFO to manage AI compute costs (30-50% of OpEx) and...

What is the best AI code review tool?

Discover which AI code review tools actually work in production: This controlled benchmark reveals why LinearB's statefulness and signal-to-noise ratio...

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.

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