Mastering AI as Agile Practitioners with the AI 4 Agile Course
$129 until October 20,2025: The ‘AI 4 Agile Online Course’
Hello everyone!
The AI 4 Agile Online Course launched yesterday, and I am proud that I avoided another delay. Scope creep happened despite my supposed expertise in preventing exactly that. The course expanded from a simple prompt collection to over 8 hours of video, custom GPTs, and materials that I’ll apparently continue to update indefinitely, as I’m still not satisfied that it’s comprehensive enough. (Also, the field is advancing so rapidly.)
At least the $129 lifetime access means you will benefit from my efforts to overcome imposter syndrome with perfectionism, as well as my inability to call a project “done.” I guess we are in for the long term. 🙂
🎓 🛒 The AI 4 Agile Online Course Is Available — Join Now at $ 129 until October 20, 2025: AI 4 Agile — Master AI Integration for Agile Practitioners.
Free: Test-Drive the AI 4 Agile Course
There are plenty of opportunities to test-drive the AI 4 Agile Course in advance:
📺 Check out the publicly available AI 4 Agile Course sessions on YouTube.
🎓 Test your AI judgment in Agile with 10 questions on outcomes, guardrails, and everyday decisions with the AI 4 Agile Quiz on Basic Principles. (Free sign-up to Accredia required.)
🎓 Test your AI judgment in Agile with 10 questions on navigating automation bias, validating outputs, protecting privacy, and resisting surveillance theater with the AI 4 Agile Quiz on Data Analysis. (Free sign-up to Accredia required.)
Disclaimer: Accredia is the platform for the AI 4 Agile certification program later this week.
Please note: All AI 4 Agile Course students also enjoy a 14-day no-questions-asked cancellation privilege. At $129, you’re also not committing to buying a new home, either. (Have I mentioned that it is a one-time fee, not a subscription, including all future course upgrades?)
🎓 🛒 The AI 4 Agile Online Course Is Available — Join Now at $ 129 until October 20, 2025: AI 4 Agile — Master AI Integration for Agile Practitioners.
Testimonials from The AI 4 Agile BootCamp Cohort
“The framework is immediately applicable to real workplace scenarios. I was using the prompt templates in my retrospectives within days of starting the course.” — Lauren Tuffs, Senior Scrum Master
“Stefan’s expertise in both agile and AI creates a unique learning experience. The 70/10/20 structure with real-world cases makes the learning stick.” — Fortune Buchholtz, Agile Coach
“Finally, an AI course that acknowledges agile practitioners need different approaches than developers. Accessible even for AI newcomers.” — Atticus Ryan, Product Owner
“This bridges the gap between AI capability and agile application. Stefan understands both domains deeply, and it shows in every module.” — Holger Dierssen, Digital Transformation Lead
“At the beginning, Stefan said that 𝘫𝘶𝘴𝘵 𝘴𝘪𝘨𝘯𝘪𝘯𝘨 𝘶𝘱 𝘢𝘭𝘳𝘦𝘢𝘥𝘺 𝘱𝘶𝘵𝘴 𝘶𝘴 𝘢𝘩𝘦𝘢𝘥 𝘰𝘧 𝘮𝘢𝘯𝘺 𝘱𝘳𝘢𝘤𝘵𝘪𝘵𝘪𝘰𝘯𝘦𝘳𝘴. That sounded like a big statement. But somewhere along the way, I noticed a shift... an emerging superpower in how I approach my tasks with AI.⚡ And now, as my AI-mutation continues, I catch myself wondering: 💭 𝘏𝘰𝘸 𝘥𝘰 𝘐 𝘶𝘴𝘦 𝘈𝘐 𝘵𝘰 𝘴𝘢𝘷𝘦 𝘵𝘩𝘦 𝘢𝘨𝘪𝘭𝘦 𝘸𝘰𝘳𝘭𝘥?” — Ilya Zaytsev, Leading Agility at HUGO BOSS
The Main Elements of the AI 4 Agile Course
Let me walk you through the main educational segments of Mastering AI with the AI 4 Agile Course:
Segment 1: Introduction — The Basic Principles
Most agile practitioners approaching AI make the same critical mistake: they treat it as just another tool in their toolkit, like Jira or Miro. This idea fundamentally misunderstands both the capabilities and limitations of AI.
The opening segment confronts this head-on by establishing where AI genuinely amplifies agile practice, continuous customer discovery, pattern recognition in team dynamics, data-driven Retrospectives, and where it threatens to undermine the very empiricism that makes Agile work. You’ll learn to distinguish between AI-augmented expertise and the superficial adoption that creates more problems than it solves.
The fictitious MegaBrain.io scenario grounds this learning in reality: a startup facing technical debt, leadership conflicts, team burnout, and funding pressure simultaneously. It is a messy, interconnected dysfunction you encounter daily as an agile practitioner in one form or another. At the same time, it provides a safe environment for practicing AI-enhanced interventions on real-world organizational problems.
More critically, you’ll develop the framework for recognizing when you’re committing a pervasive anti-pattern: applying probabilistic AI tools to deterministic problems. This category error erodes empiricism, compromises professional integrity, and creates technical debt that teams discover too late. The segment closes with a practical breakdown of frontier models, identifying which ones actually deliver value for your specific agile challenges and which are merely marketing hype, saving you months of expensive trial and error.
Segment 2 — From Dabbling with Prompts to Gaining a Strategic Partner in Solving Problems
The lessons on Prompt Engineering, Customization, GPTs, Projects, and Reports transform AI from a generic tool into a specialized extension of your agile practice through systematic skill development. The journey begins with diagnostic prompting, or moving beyond superficial requests to identify the root causes of team dysfunction, and generating interventions that build psychological safety and trust, rather than automating another performance of a mediocre ceremony.
Profile customization establishes your expertise level and professional focus at the system level, eliminating repetitive context generation while producing theoretically grounded analysis instead of tactical checklists. Memory management prevents quality degradation through strategic isolation using temporary chats, projects, and multi-account architectures, ensuring your coaching prompts don’t compete with unrelated queries.
Finally, the Agile Prompting Framework © teaches collaborative dialogue over one-shot queries, developing critical refinement skills through the Goldilocks context balance and model reflection. You’ll recognize when outputs are genuinely strategic versus polished mediocrity. Also, GPT-5 adaptations introduce staged reasoning, quality checkpoints, and the OpenAI prompt optimizer for benchmarking against official standards.
This foundational exploration of prompting will take you even further: Metaprompting elevates AI to a collaborative partner status, iteratively co-creating targeted interventions through prompt refinement and self-critique. Prompt inflation leverages extensive context and niche terminology to generate sophisticated, run-ready facilitation guides for high-stakes situations rather than generic templates.
The culmination involves building force multipliers: Custom GPTs with curated knowledge bases and isolated Projects for distinct value streams. These persistent workspaces combat knowledge decay, accelerate onboarding, and provide consistent analysis, creating scalable AI advisors that protect team focus on critical goals.
In other words, you’ll develop a systematic methodology for integrating AI into daily practice, generating actionable interventions that directly address your teams’ specific challenges while maintaining the rigor and depth your expertise as an agile practitioner demands.
🎓 🛒 The AI 4 Agile Online Course Is Available — Join Now at $ 129 until October 20, 2025: AI 4 Agile — Master AI Integration for Agile Practitioners.
Segment 3: Transforming Raw Data into Strategic Agile Intelligence
These lessons address a problem you already know too well: you’re drowning in data you don’t have time to analyze. Retrospective stickies pile up. Performance metrics contradict each other. Interview transcripts sit unread. Meanwhile, leadership demands insights, teams expect interventions, and you’re manually synthesizing patterns at an ungodly time because there’s no other way to do it.
Our educational work begins with Retrospective stickies, those cryptic Post-its that supposedly capture “what went wrong.” You’ll learn to extract the root causes behind dysfunctional Sprint Planning, rather than facilitating yet another conversation where everyone nods about reverse-engineered Sprint Goals, but nothing changes. The difference lies in uncovering the actual team misconceptions that drive a feature-factory-like task-first behavior, rather than running another Retro that produces more soon-to-be-abandoned action items.
Moreover, quantitative performance analysis moves you past subjective assessments that leadership dismisses as “soft skills concerns.” You’ll surface the systemic impediments buried in metrics, such as collaboration anti-patterns, dependency bottlenecks, and other organizational dysfunctions that everyone senses but nobody can articulate with evidence. This change gives you the ammunition to engineer Retrospectives that actually expose problems rather than rehearse comfortable narratives, preparing you for difficult change conversations with senior leadership.
Executive communication matters because data without influence is an academic exercise. You’ll translate team impediments into business terms that leadership understands: release probability, revenue risk, and competitive positioning. Not “the team feels burnt out.” That’s the bridge between Sprint reality and C-level decisions that release budget and authority.
Customer interview analysis and product discovery work apply the same capability: compress weeks of manual synthesis into hours. Generate testable hypotheses from dense requirement documents. Document learning before committing capacity. Stop pretending you have time for rigorous analysis when you’re already oversubscribed.
The practical outcome is evidence-based interventions that address root causes, building credibility through rigorous analysis rather than charisma or seniority.
Segment 4: Mastering AI Requires Recognizing AI Adoption Issues Before They Damage Your Teams
You’ve watched this exact failure pattern before. Organizations bought Jira licenses and declared, “We are Agile!” Waterfall phases got renamed to Sprints, while nothing changed. Now leadership demos AI in all-hands meetings, celebrates “87% adoption rates,” and expects magic. Meanwhile, you’re the ones struggling when the pilots collapse in production.
The lessons of Segment 4 confront several anti-patterns that you may already recognize from past Agile adoption failures:
AI Theater: Impressive demos that never integrate into actual work, more time showcasing tools than solving problems.
Shiny Tool Syndrome: Endless evaluation matrices while IT drives adoption instead of delivery teams, the same waste as the Great Jira Configuration Quest of 2015.
Integration Illusion: Pilots that work in controlled environments but collapse when they hit approval workflows, security policies, and the legacy systems nobody mentioned.
Metrics Theater: Dashboards tracking prompts and interactions while business outcomes remain unchanged, just like story point inflation and velocity gaming.
So, are you solving documented problems or impressing stakeholders? Did you identify customer pain points before shopping for solutions? Did you plan integration with existing systems from day one, or are you building another Agile island surrounded by waterfall? Are you measuring value delivered or just usage statistics that leadership likes to see?
What actually works mirrors your Agile transformation experience: Document specific problems solved, start with your biggest pain point, test simple solutions before complex ones, map affected systems and organizational antibodies early, measure outcomes, not outputs. Moreover, your pattern recognition sense, developed over years of Agile failures and organizational politics, is what prevents you from repeating the same mistakes with different tools.
Going through Segment 4, you can lead AI adoption that delivers value instead of theater, such as wasting another transformation cycle on tools that look good in demos but never survive contact with organizational reality. And while we are at it, rest assured that AI ethics and AI risk mitigation are critical parts of what makes the curriculum of the AI 4 Agile Course so valuable.
🎓 🛒 The AI 4 Agile Online Course Is Available — Join Now at $ 129 until October 20, 2025: AI 4 Agile — Master AI Integration for Agile Practitioners.
Mastering AI: What Is Part of the AI 4 Agile Course?
I developed the self-paced AI 4 Agile Online Course for agile practitioners, including Product Owners, Product Managers, Scrum Masters, Agile Coaches, and delivery professionals who want to integrate artificial intelligence into their workflows with clarity, ethics, and purpose.
You don’t need to become an AI expert. However, you do need to understand how LLMs like ChatGPT, Claude, or Gemini can support real agile work and where their limitations lie. Like Jim Highsmith said, AI isn’t just a tool, but a new context for agility.
What’s Included:
8+ hours of self-paced video modules
A cohort-hardened, proven course design
Learn to 10x your effectiveness with AI; your stakeholders will be grateful
Delve into classic agile use cases of AI
Help your team create more customer value
All texts, slides, prompts, graphics; you name it
Access custom GPTs, including the “Scrum Anti-Patterns Guide GTP”
Guaranteed: Lifetime access to all course updates and materials; there is a lot more to come
Certificate.
Conclusion
The question isn’t whether AI will reshape your agile practice; your leadership already decided that when they bought the licenses. The question is whether you’ll lead that integration competently or watch another transformation cycle fail.
At $129 for lifetime access to all course materials, updates, and community support, the real cost is continuing to manually synthesize data at midnight while your organization wastes budget on tools that collapse in production. You are already familiar with these failure patterns from Agile adoption. Now, you can learn to prevent them with AI before you explain another expensive pilot failure to stakeholders who expected magic.
🎓 🛒 The AI 4 Agile Online Course Is Available — Join Now at $ 129 until October 20, 2025: AI 4 Agile — Master AI Integration for Agile Practitioners.
📖 Mastering AI — Related Posts
AI Risks: Why Product Professionals Are Sleepwalking Into Strategic Irrelevance
Ethical AI in Agile: Four Guardrails Every Scrum Master Needs to Establish Now
Generative AI in Agile: A Strategic Career Decision
Contextual AI Integration for Agile Product Teams
Stefan Wolpers: The Scrum Anti-Patterns Guide (Amazon advertisement.)
Love this commitment to continuous improvement. That 'inability to call a project done' sounds less like imposter syndrome and more like essential agile for AI's pace. It's a feature, not a bug, especially with lifetime access. We all graple with scope creep, it's a beast.