Resources &
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Explore the barriers to AI adoption in senior software engineers and how leaders can transform their AI skepticism into AI advocacy.

Discover what data-driven engineering is, why it matters, and the five operational pillars that help teams make smarter, faster, and impact-driven decisions.

Discover which engineering team metrics to track based on your software engineering culture. Learn how cultural values determine the right measurements for your team's success.

Engineering productivity metrics vary by operating model. Compare metrics for remote, hybrid, outsourced, and distributed software engineering teams.

Discover the best software engineering metrics for startups, scale-ups, and enterprises. Learn how to choose metrics in software engineering by company stage.

Discover the three systemic barriers that undermine AI coding assistant impact and learn how top-performing enterprises are overcoming them.

Explore the Faros AI Hubble release, featuring GAINS™, documentation insights, and a 100x faster event processing engine, built to turn AI engineering potential into measurable outcomes.

METR's study found AI tooling slowed developers down. We found something more consequential: Developers are completing a lot more tasks with AI, but organizations aren't delivering any faster.

Key findings from the AI Productivity Paradox Report 2025. Research reveals AI coding assistants increase developer output, but not company productivity. Uncover strategies and enablers for a measurable return on investment.

Full Report: What data from 10,000 developers reveals about impact, barriers, and the path forward. Insights from our analysis of 1,255 teams across leading software engineering organizations.