Match & Learn - Closing the AI Effectiveness Gap

AI tools are now part of everyday engineering: copilots, agents, automated reviews, generated tests. But outcomes aren’t consistent. Some teams are clearly moving faster with more confidence, while others feel more churn: heavier reviews, more uncertainty, and slower delivery.

This 1:1 Match & Learn is for engineering leaders who want to compare what’s actually working, spot the patterns behind uneven results, and leave with practical ideas to increase impact.

In these 1:1 conversations, we’ll explore:

1. Where gains really show up: Which parts of the SDLC improve first (and which don’t)
2. The hidden friction: Verification costs, review load, context switching, tool sprawl, and trust calibration
3. Adoption that scales: Enablement, guardrails, workflow design, and rollout strategies that stick
4. Measurement that reflects reality: What to track to understand true impact on speed and quality
5. Team norms that compound: Coding standards, testing expectations, review practices, and “definition of done” in the AI era

How it works:

1. In the course of the session, you'll be matched with other engineering leaders for a 10-minute video call
2. At the end of 10 minutes, you'll have the option to extend it or start another match.

Join if you:

1. Are rolling out AI tools or agents across an engineering org (or planning to)
2. Want to learn why results vary so widely and how to reduce that variance
3. Care about improving throughput and quality without increasing chaos
4. Enjoy thoughtful, practical conversations with peers (beyond hype)

This is a space for reflection, learning, and connection among leaders building the future of AI together.