The platform engineer’s guide to AI adoption
This guide explores how AI is redefining the role of platform teams in 2025 by delving into:
Strategies for architecting AI-native infrastructure and workflows
What 20K+ engineering leaders are doing to operationalize AI at scale
How platform engineering can enable safe, scalable AI adoption across the SDLC
The platform engineer’s guide to AI adoption
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Insights from 20K+ engineering leaders
Learn how today’s top engineering minds are preparing for an AI-first future, including:
Why unified documentation and high-quality data matter more than ever
How platform teams are enabling zero-touch deployment pipelines
The cultural and technical shifts needed for AI-human collaboration at scale
Your playbook for scaling AI with confidence
Inside, you’ll find practical checklists and expert-backed strategies to:
Establish AI governance frameworks without sacrificing velocity
Create invisible guardrails and human-in-the-loop validation
Standardize metrics and build trust in AI-generated output
Common AI bottlenecks (& how to avoid them)
This guide reveals the most critical bottlenecks slowing AI-driven development, including:
Isolated tools without orchestration layers
Legacy infrastructure unfit for autonomous agents
Disconnected knowledge and tribal documentation
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More resources
Workshop
Build vs. buy: Why DIY engineering metrics break at scale
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.
Guide
How to build your own engineering productivity platform
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?
Report
LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms
Get complimentary access to the full report.