The Engineering Leader’s Guide to the AI Software Development Stack

Most engineering teams don’t fail at AI because of tooling – they fail because there’s no plan for change management.  

In this guide, we outline a proven framework engineering leaders can use to drive meaningful, measurable results from AI across their organizations and throughout the SDLC.

This isn’t a maturity model or a vision deck. It’s a practical roadmap grounded in data from teams actively using AI.

You’ll learn how to:

• Instrument clear telemetry on AI usage and outcomes
• Drive enablement through training, guidance and accountability
• Build momentum and scale with confidence
• Stay aligned with a rapidly evolving AI dev landscape
• Make deliberate organizational changes to meet the moment

If your teams are experimenting with AI, but leadership still lacks confidence in the results, this framework provides the structure you need.