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Exclusive research, reports, ROI tools, workshops, infographics, and ready-to-use presentation templates for engineering leaders looking to build a continuous improvement engine. 

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This demo guides you through the AI Insights Dashboard, demonstrating how to track and analyze trends in AI tool adoption, rule coverage, and code quality. You’ll also see how to correlate insights with survey data to understand the impact of AI.

Understand AI adoption and developer impact with the AI Insights Dashboard

This demo walks you through connecting Anthropic’s Claude to LinearB data, querying insights and recommendations, and building repeatable metrics dashboards – all powered by the LinearB MCP Server.

Using the MCP Server with Claude

Measuring efficiency in the AI-driven SDLC means tracking whether your whole software delivery system got faster and more reliable, not just whether developers are using AI tools more.

Measuring Efficiency in the AI-Driven SDLC

Do we still need to buy the vendor platforms we’re evaluating, or could a small team and a Claude subscription build the parts we want?

How to build your own engineering productivity platform

DIY engineering productivity dashboards fail within 3 to 6 months for the same reason every time: the dashboard was never the hard part.

Build vs. buy

An operating model for engineering productivity with practical guidance for how to measure AI impact.

The APEX framework

Everything you need to define, hire, and empower the Director of AI enablement in your engineering organization.

Hiring kit: Director of AI Enablement

This guide will show you why Rework matters, how to measure it, and how to reduce it with smart practices and automation.

Quickstart metrics guide: Rework

In this guide you’ll learn why Planning Accuracy matters, how to measure it, and how top-performing teams improve it.

Quickstart metrics guide: Planning Accuracy

This guide will show you why DSAT matters, how to measure it, and how to improve it with practical actions and automation.

Quickstart metrics guide: DSAT

This guide will show you why Cycle Time matters, how to measure it, and how to reduce it with the right practices and automations.

Quickstart metrics guide: Cycle Time

Get complimentary access to the full report.

LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms

Created from a study of 8.1+ M PRs from 4,800 engineering teams across 42 countries.

2026 Software Engineering Benchmarks Report 

Hear how leading enterprises are applying LLMs to accelerate testing and code migrations.

How Meta & Google are scaling AI across the SDLC

Learn what 20k high-performing teams are doing to remove friction and scale AI effectively.

The 6 bottlenecks slowing AI-driven development

How dependency management bots are affecting your Developer Experience and Productivity.

Managing Bot-Generated PRs & Reducing Team Workload by 6%

This LinearB Research Report breaks down how to measure the impact of Generative AI code across the software delivery lifecycle.

Measuring Impact: The GenAI Code Report

The DevOps Research and Assessment (DORA) team at Google and LinearB have partnered to gather research from over 36,000 professionals worldwide for the 2023 Accelerate State of DevOps Report. 

2023 DORA Report

This report represents the average annual return on investment engineering organizations realize when using LinearB to increase developer efficiency, streamline reporting and reinvest new value.

ROI Calculator

Engineering leaders should focus on addressing both sides of their dual mandate during executive and board meetings: Operational Excellence & Business Outcomes. The CTO Board Deck provides templates that help guide you through the KPIs and project updates business stakeholders are most interested in. 

CTO Board Deck Template

Watch a 35-minute workshop where we'll show where agentic AI breaks down when trying to build an engineering productivity platform that drives improvement.

Build vs. buy: Why DIY engineering metrics break at scale 

GitHub Copilot here, Cursor there, Claude Code somewhere else. AI across tools is adopted, but is it actually working?

AI impact: Measure what matters

Explore new AI insights from the 2026 Software Engineering Benchmarks Report – backed by 8.1M+ PRs across 4,800 engineering teams and 42 countries.

2026 Benchmarks Insights

In this 35-minute workshop, you’ll learn how MCP insights and AI workflows are helping enterprise teams boost developer productivity and experience.

Closing the AI gap: Surpassing executive expectations for AI productivity

In this 35-minute workshop, we’ll unpack how enterprise teams are redefining the PR lifecycle to accommodate AI-generated code at scale.

The AI upgrade to your SDLC: A data workshop on AI code reviews

Watch this live panel discussion to hear the latest trends in how enterprises are using AI to drive developer productivity.

Beyond Copilot: What’s Next for AI in Software Development

Move over copilot, we’re in the driver’s seat now. We’ve introduced three new AI-driven features that are saving developers ~3 hours a week.

The Future of Productivity Is AI-Driven

Join this 35-minute workshop to explore the slides and best practices CTOs use when speaking to the board about their Developer Experience initiatives. 

Translating DevEx to the Board 

Move from academic frameworks to impact-based data practices in this on-demand workshop

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