Short:
AI has upended software engineering, and the hype couldn't be louder. Token spend is highly visible on the CFO's radar, and CEOs read about 2x, 5x, and even 10x velocity gains all over social media.

Meanwhile, engineering leaders struggle to provide tangible proof of these leaps. They face mounting pressure from executive leadership to replicate those hyped results while justifying spiraling token costs.

This session breaks down why proving impact is so difficult, delivering a curated set of metrics and industry benchmarks to measure true AI adoption and output.

Attendees will get a rare look into advanced analyses for AI-assisted coding - covering session efficiency, human/agent friction, skill utilization, and token optimization.

Finally, walk away with a practical blueprint for combining deterministic automation with AI flows to neutralize bottlenecks, secure delivery guardrails, and unlock genuine engineering velocity.

Long:
AI has upended software engineering, and the hype couldn't be louder. Token spend is highly visible on the CFO's radar, and CEOs read about 2x, 5x, and even 10x velocity gains all over social media.

Meanwhile, engineering leaders struggle to provide tangible proof of these productivity leaps. They face mounting pressure from executive leadership to replicate those hyped results while justifying spiraling token costs.

Achieving and proving a 2x boost is notoriously difficult, and for good reason. In this talk, we unpack the art of Developer Productivity, showing how engineering metrics evolved through the AI revolution. We map where AI productivity shines, where it falls short, and where AI creates new bottlenecks that can even result in net-negative productivity.

This session reviews best practices and key metrics for measuring AI adoption and productivity, backed by industry benchmarks. Attendees will gain a rare look into advanced analyses for AI-assisted coding - covering session efficiency, human/agent friction, skills utilization, and token optimization.

The session concludes with a practical blueprint for combining deterministic automation with AI flows. This approach delivers the compliance and quality guardrails modern engineering organizations require, directly neutralizing new AI bottlenecks to unlock the real productivity boost everyone is chasing.

Key Takeaways:

Discover a curated set of metrics to measure AI adoption, productivity, and ROI.

Compare your team's data against current industry benchmarks to anchor leadership expectations.

Learn advanced analysis methods to uncover hidden inefficiencies in how teams use AI, including session effectiveness and tool utilization.

Walk away with an automation blueprint to successfully integrate AI flows with deterministic guardrails.