Big Agile with Lance Dacy

Inspired fades over the flight home. Changed shows up in your next planning session. Lance Dacy breaks down how to attend an Agile conference like an analyst instead of a fan, with three questions that turn a week on the floor into one real decision.

Two rooms, same company, same morning. In the boardroom: "We're all in on AI." Two floors down, in a standup, someone asks the only question that matters: "So what does that mean for us by Friday?" Nobody has an answer. That gap is the whole problem. 

The pressure to "get AI" has moved to the top of the org. BCG's AI Radar 2026 found 72% of CEOs now say they're the main decision maker on AI (double from a year ago), and half believe their own job depends on getting it right. Meanwhile Grant Thornton's 2026 survey found 78% of leaders aren't confident they could pass a basic AI governance check in 90 days. Ownership went up. Control didn't follow. 

In this episode, Lance Dacy explains why owning AI and controlling it are not the same skill, and walks through the four-part translation leaders can use to convert board-level pressure into something teams can safely act on: one observable outcome, a clear safe-to-try line, named decision rights, and a no-blame way to surface the misses. 

In this episode:

• Why "use AI to move faster" is useless to a team, and the one-sentence rewrite that fixes it
• How to draw a safe-to-try line so people stop guessing with customer data
• Who needs the authority to say yes, and why naming them unfreezes the team
• A one-sentence exercise to run in your next leadership meeting 

Resources mentioned:

• BCG AI Radar 2026 (Jan 2026)

• Grant Thornton 2026 AI Impact Survey — the "AI proof gap" 

Newsletter: https://big-agile.com/newsletter

Events & Consulting: https://big-agile.com/events

Connect with Lance: https://www.linkedin.com/in/lancedacy/

Somebody in your org just approved an AI budget on a chart that says productivity is up 30%. Compared to what? Measured how? That's the question most AI productivity numbers can't survive — and it's not because the people building them aren't smart. The number was never built to be pressed on.

In this episode, Lance Dacy breaks down why your green dashboard is measuring AI-flavored activity, not real progress. He walks through the 2025 METR study where experienced developers felt about 20% faster with AI while the clock showed them 19% slower, the follow-up that collapsed because developers refused to work without AI, and what DORA's latest research says about shipping more while breaking more. Then he hands you the "gut check": three questions every AI metric has to survive before you trust it, plus a 10-minute experiment to run on your own dashboard this week.

Your team bought the AI licenses, the demo looked incredible, and six weeks later you're shipping the same confusion, just faster. AI didn't fix your team. It made it louder. Lance Dacy breaks down why AI amplifies whatever your system already was, and how to read the results.