Big Agile with Lance Dacy

Big Agile
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Most agile advice is theater. Big Agile isn't. Enterprise agile consultant Lance Dacy takes the beliefs the agile world treats as settled, velocity, psychological safety, AI governance, org design, and pressure-tests them against how work actually moves inside real companies. No ceremony worship, no framework dogma. Just systems thinking, hard research, and two decades inside organizations where the standups are perfect and the roadmap still slips. For Scrum Masters, Product Owners, coaches, and leaders who want agility that's real, not performed.

Episodes

  1. 5d ago

    More Dashboards, Worse Outcomes: The Visibility Paradox

    Even the dashboards have a dashboard now. Somewhere in your organization a team added a batch of new ones this quarter, and meanwhile a monitor in IT ops has been frozen on a session-timeout screen since March that nobody has noticed. That contradiction is the whole episode. We've never had more visibility into how we build software, and the people running those systems say delivery keeps getting harder, not easier. Lance Dacy calls this the visibility paradox, and he walks through why both things are true at once. Drawing on Digital.ai's 18th State of Agile Report, two years of DORA research on AI and delivery stability, DORA's 2026 "instability tax," and Mark Graban's work on signal versus noise, he makes a simple case: a metric only earns its place if it changes a decision, and AI has removed the cost that used to kill the weak ones. The practical core is a tool Lance calls the dashboard-to-decision audit: one record per metric, five lines each. Name it, name who actually reads it, name the last decision it changed, ask what breaks if it disappeared tonight, then keep it, cut it, or merge it. He runs it live on the executive summary dashboard, makes the case that this is leadership work rather than team housekeeping, and closes with a challenge you can run before your next review. Subscribe to the Big Agile newsletter at https://big-agile.com/newsletter and explore workshops and consulting at https://big-agile.com/events.

  2. Aug 17

    Why More AI Code Made Your Delivery Slower

    Your team shipped more code last quarter than in any previous quarter, and delivery is slower than it was last spring. Both things are true, and they are related.  Nobody stopped working. The work stopped moving. It is sitting in the review column, and it has been sitting there long enough that nobody on the team remarks on it anymore.  In this episode Lance Dacy works through what happens when generation gets cheap and verification does not. GitClear's 2026 research puts roughly a quarter of detected commits as AI-assisted, with two-week churn running about 15% above its 2023 level. The 2025 Stack Overflow survey found that the number one developer frustration, at 66%, is output that is almost right but not quite, with 45% saying debugging AI-generated code takes longer. And DORA reversed part of its 2024 finding: throughput flipped positive in 2025, while delivery instability did not improve.  Lance's argument is that review is not a step in your process, it is a queue, and queues behave in ways that make this worse than it looks. Drawing on Donald Reinertsen's 2009 book The Principles of Product Development Flow, he covers why this inventory is invisible on every report you own, why queue size spikes rather than climbs as you approach full capacity, and what rate matching means when your fast sender is an AI and your slow receiver is a human reviewer.  Then the practical part: four numbers that tell you how many AI-assisted items your team can genuinely verify in a week, worked through with a real example, plus where to put the limit. The answer is counterintuitive. You cap generation to protect verification, and you set that cap light rather than tight.  Closing thought: verification is not overhead added to the real work. It is the work. The scarce person on your team is no longer the one who can produce a plausible change, it is the one who can look at a plausible change and tell you whether it is right.  Your homework is two numbers. What you generated last week, and what you can actually review. If they are not close, you do not have a productivity story. You have a queue.  Sources referenced: GitClear 2026 code quality research, Stack Overflow 2025 Developer Survey, DORA 2024 and 2025 reports, Donald Reinertsen, The Principles of Product Development Flow (2009).  Weekly newsletter: https://big-agile.com/newsletter Workshops and consulting: https://big-agile.com/events

  3. Aug 11

    Using AI Is Not Delegating to It

    84% of developers use AI. 46% don't trust it. Both can be true, because using a tool and handing it work are two different relationships. Lance Dacy breaks down a five-rung delegation ladder and the one question that decides which rung a task belongs on.

  4. Aug 3

    Human in the Loop Is Not a Strategy

    "A human will remain in the loop." It's in most AI policies, and it usually protects nothing. Lance Dacy explains why AI oversight fails at agent speed, the four postures every decision already falls into, and how to test whether your named human can actually stop the line.

  5. Jul 27

    Attend an Agile Conference Like an Analyst, Not a Fan

    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.

  6. Jul 20

    Owning AI Is Not the Same as Controlling It

    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 itHow to draw a safe-to-try line so people stop guessing with customer dataWho needs the authority to say yes, and why naming them unfreezes the teamA 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/

  7. Jul 13

    Why Your AI Productivity Metrics Can't Survive One Question

    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.

  8. Jul 6

    Why AI Made Your Team Louder, Not Better

    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.

  • 8 Episodes

About

Most agile advice is theater. Big Agile isn't. Enterprise agile consultant Lance Dacy takes the beliefs the agile world treats as settled, velocity, psychological safety, AI governance, org design, and pressure-tests them against how work actually moves inside real companies. No ceremony worship, no framework dogma. Just systems thinking, hard research, and two decades inside organizations where the standups are perfect and the roadmap still slips. For Scrum Masters, Product Owners, coaches, and leaders who want agility that's real, not performed.

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