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Surviving the AI Tsunami
An evidence-based course to help you and your team make GenAI work for you, instead of you working for the AI.
Reserve your seat
Beta cohort, this price for this cohort only: $599 CAD. The price goes up for every cohort after this one. Capped at 10 seats.
- 6 weeks, starting June 29
- Twice a week online — Mondays and Fridays, 1pm EDT / 7pm CEST / 10am PDT
- First session: learning-focused (60–90 minutes, recorded). Second: coaching and follow-up (60 minutes).
- Forum access between sessions
Why this course exists
You’re being told to use AI. It may be part of your performance review. This pressure just leads to more vibe-coded products and bigger problems later. Worse, even if an AI tool makes one person more productive, it may slow the whole team down. Generate so much code that you swamp review and testing, and the system breaks. You want to be the one in your team who can tell what’s hype, what’s actually useful, and what’s about to create six months of cleanup.
There is a lot of hype around AI. Many people proclaim that AI will replace software engineers in two years. (They’ve been saying that for more than two years now.) There’s so much noise (needed to justify the $500 billion to $1 trillion valuations Anthropic and OpenAI claim) that the actual value of the technology gets buried. It’s amazing that an AI can generate a code base from scratch in hours. However, that vibe-coded product won’t be coherent, usable, or maintainable. Vibe-coded products keep shipping with security flaws. How do I know? Because I’ve done it myself.
To make GenAI work for us and not us working for the AI, we need to adopt an evidence-based approach.
GenAI isn’t the villain. The villain is the speed-over-quality culture that’s using AI as cover.
If it feels like your team is being pushed into using AI faster than you can sustain, you’re not alone. I’ve been watching teams navigate this for the last two years, and it’s the same conversation everywhere: how do I tell what’s actually working? The numbers are going up, but we’re not creating more value.
What this course helps you solve
You don’t need more promises of magic. You need answers to the questions your team is dealing with right now. Here is some of what we will address:
- “Our Product Backlog is over 150 items, can we use AI to get through it faster?” You could. However, you end up with a Franken-product, a series of parts that barely fit together and no one wants to use.
- “It built a huge PR, we can’t review or test it reliably.” When AI generates a large feature in one go, the existing bottleneck just gets worse. Writing code was never the bottleneck. So writing code faster just makes the downstream problem worse. We’ll fix the refinement step that’s missing before the code: slicing the work small so every change stays reviewable and safe to ship.
- “We have a massive story, can we use AI to make it smaller?” We don’t need AI. We need practice splitting it. We’ll practice slicing work so it flows, with clear acceptance criteria (Specification by Example, BDD) that both your team and the AI can build against. When the team has done their first pass, the AI does a good job of pointing out missing edge cases.
- “Can AI foresee something we haven’t?” AI doesn’t think and isn’t imaginative. However, it can be fed a problem and iterate on it dozens of times without getting bored. As humans, we still need to do the hard work: discovery, refinement, planning, etc. It doesn’t replace us. It’s good at pointing out how systems might fail, with limits.
- “Can AI improve our forecasting and help identify our bottlenecks?” Velocity is a poor measure. It does a poor job with both forecasting and bottlenecks. We will look at the measures that will help: Cycle Time, Throughput, Mean Time Between Rollbacks, etc. We will learn to use those to make realistic forecasts and pinpoint the real bottlenecks. GenAI is a useful sparring partner once we’ve found the real bottlenecks.
- Telling hype from substance. You’ll get a fitness-for-purpose lens for where GenAI actually earns its place in your workflow and where it just adds noise.
- Protecting your team and your role. We’ll deepen the ScrumMaster and Product Owner roles and guard against cognitive debt, deskilling, and burnout, so a year of GenAI doesn’t leave the team unable to reason about its own code.
What past students say
The AI Tsunami course is brand new, so these reactions are from Mark’s earlier Scrum classes. They speak to how he teaches: lived experience, immediate value, no filler.
How it Works - Beta Course
Normally, I promise no PowerPoint; however, this is a first-time course, so some sessions will use slides. That lets me adapt the content as I learn what’s actually getting in your way.
- Sign up on Corsizio $599 CAD, beta pricing for this cohort only. The price goes up after this cohort. Capped at 10 seats so I can coach everyone properly.
- Do the foundations work before week one Pre-reading, the “right tool, right reason” checklist, and a quiz so we all start in the same place. The forum opens at the same time.
- Meet twice a week for 6 weeks Starting June 29 at 1 pm EDT/7pm CEST/10am PDT. Learning sessions are 60-90 minutes and recorded; coaching sessions aim for 60 minutes and can run longer if needed.
- Try the work in your team You plan and try at least one improvement per stage. The forum is where you share what worked, what didn’t, and ask for help.
Email me at mark@agilepainrelief.com with questions, or click register on your right.
Full course outline
At each stage, you’ll pick at least one improvement to plan and try with your team between sessions. The forum is where you’ll share what worked, what didn’t, and ask for help when you’re stuck.
Foundations
Self-paced pre-work, plus forum access, before the cohort begins. You’ll cover:
- Basics of GenAI: How it works and what its limitations are.
- The fitness-for-purpose checklist: A checklist to make sure that GenAI is being used in the right place and for the right reasons.
- How GenAI Fails: There are a number of failure modes for GenAI, beyond hallucinations. We need to understand how they fail, to know what to guard against.
Measurement and Flow
- Improving Measurement: We will set up a measurement process that includes Cycle Time, Throughput and Mean Time between Rollbacks. We will use these measurements throughout our work to understand the impact of AI on our team and the system.
- Improving Forecasting: We will learn to use Cycle Time and Monte Carlo Simulation to improve forecasting. Oddly enough, this is one area where AI isn’t all that helpful.
- Code was never the bottleneck: Why writing more code faster isn’t delivering more value and what to do about it.
- Finding the Real Bottlenecks: Code was never the constraint to delivering value. We will learn how to identify bottlenecks and how GenAI can help.
Role Evolution
- Scrum Events: What AI Can (and Can’t) Help With: The Scrum Events (Sprint Planning, Daily Scrum, Sprint Review and Retrospective) are designed to help build a shared understanding of the work and improve collaboration. Our use of GenAI should be to help improve these benefits and not eliminate them. Too much focus is placed on using the AI to speed up the events, instead of focusing on using the AI to ask better questions. For example, use the PreMortem technique to ask questions about a team’s Sprint Plan, to test before we start the Sprint.
- Deepening the ScrumMaster Role: Introducing Systems Thinking puts the emphasis on coaching the team and the system. We will use GenAI as a sparring partner for Systems Thinking exercises, not as a replacement for human thinking.
- Evolution of Product Ownership: Product Owners need to focus more on experimentation and validating user needs. Innovation still requires human creativity. Don’t use the GenAI to replace your innovation; instead, use it to critique your ideas and build tests that validate your hypotheses.
Technical Realities
- Vibe Coding promises a miracle: Building applications without needing engineers, or so we’re promised. GenAI can be very useful; it’s not magic.
- Agentic AI: Everyone calls their tools “agentic”. What’s hype, what’s practical? Hint: Boasting about TokenMaxing and the number of agents you can run at the same time isn’t focused on delivering value.
- Instead of Vibe Coding: How teams actually ship in this world: validate features with experiments, then use BDD or Specification by Example to create clear acceptance criteria, through collaboration, before any code gets written.
Human Wages of AI
- Cognitive Debt: If technical debt is the cost of hard-to-maintain code, cognitive debt is code that we don’t understand, usually because it was written by GenAI.
- Deskilling and Knowledge Cliffs: What happens to a team’s ability to debug, design, and reason about code once GenAI has been doing the work for a year?
- Burnout and other human costs: Spending hours a day interacting with GenAI is leading to burnout.
AI is already coming for the shallow work. ScrumMasters who are viewed as JIRA jockeys are ripe for replacement. Product Owners who just transmit feature requests from disgruntled users will be replaced (badly) by AIs.
By the time we’re done, you’ll be the person in the room asking the questions that keep your team out of trouble when the next AI claim arrives. You’ll understand how GenAI is changing the way we work and you’ll be able to help your teams navigate the changes we can already see.
You will understand that the real issue is, and always has been, helping people collaborate more effectively. You will know there is no point in trying to compete on speed. In our changing world, the advantage goes to quality and product-market fit.
FAQ
Who is this for?
ScrumMasters, Product Owners, Managers and Agile Coaches who work in software delivery. People who want to adapt to the new reality, without the hype. Comfort with the basics of Scrum or Kanban is assumed.
Why isn’t this a certification course?
Because the certification courses that exist today are focused on better prompt engineering. Better prompts will get you better output from a chatbot. They won’t tell you whether the system around you is getting better or worse.
Why listen to me?
I am not coming at this as a cheerleader or a doomsayer. I am coming at it as an explorer. I don’t want to sell you tokens, nor do I need to justify hundreds of billions of dollars in GPU investments.
I have survived every tech hype cycle since before Gartner started tracking them (4GLs, Apple Newton, CORBA, Java Applets, Segway, No Code, the Metaverse, and on). In many of those cases, I even had to survive with the technology. We were promised the moon, and we spent years, in some cases, trying to make it work. (Hello CORBA, Newton and Java Applets.) GenAI is the loudest hype cycle I’ve ever witnessed. Trillions of dollars in investments, yes. Trillions of dollars of value? No evidence of that.
Refunds
If, at the end of the first session, you realize this isn’t for you, we will offer a full refund.
Access
You will have lifetime access to the course materials and any updates.
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