Introducing SURGE™: The 5-Part Framework for Proving AI Engineering ROI

​Your engineering org adopted AI coding tools fast and their invoices scaled faster. And now the questions are landing: the CFO wants ROI, not adoption, and you want more token budget. The board wants proof, not promises. The usage dashboards cannot answer either of them.

​This live session brings together the people behind SURGE™, Hivel's framework for measuring the ROI of AI in software engineering, built on DORA and SPACE. No recycled adoption stats, no vendor pitch. A working walkthrough of how to measure what your AI investment actually returns, and a live Q&A where the hard questions are welcome.

​What we'll cover in a nutshell: How to walk into your next renewal or board meeting with a defensible answer instead of a vibe.

• ​The measurement gap: why usage dashboards can't tell you what your AI spend actually shipped.

• ​The SURGE™ framework: Spend, Utilization, Recovery, Gains, Efficiency: one question each.

• ​Where the money goes: the waste patterns hiding in your org, idle seats, wrong models, overlapping tools, over-committed contracts.

• ​Measuring what survives: why merged code is not durable code, and what AI speed costs downstream.

​Who this is for

​CTOs, VPs of Engineering, and Directors accountable for AI tooling outcomes. CFOs and finance partners who own the AI line item. Platform and DevEx leaders running the rollout.

​Speakers

​Sudheer Bandaru
Founder & CEO, Hivel. Author of the SURGE™ framework. Sudheer works with engineering leaders across hundreds of organizations on one question: is the engineering system, now amplified by AI, actually converting effort into shipped output?

​Nathen Harvey
DORA lead, Google Cloud. Nathen leads DORA, the research program behind the industry's most widely used measures of software delivery performance, and co-authored the SURGE™ paper, which extends DORA and SPACE to the economics of AI.