• Value 1 (🧑‍🤝‍🧑) - Individuals and interactions over processes and tools.
• Value 2 (💻) - Working software over comprehensive documentation.
• Value 3 (🤝) - Customer collaboration over contract negotiation.
• Value 4 (🔄) - Responding to change over following a plan.

• Enhanced Decision-Making: AI excels at processing and analyzing large volumes of project data, providing actionable insights and forecasts that help Agile teams make smarter, faster decisions. This includes identifying potential risks, predicting delivery timelines, and suggesting optimal backlog priorities. (Supports 🔄.)

• Increased Productivity Through Automation: By automating repetitive tasks such as scheduling and status reporting, AI frees team members to focus on complex problem-solving and creative work. This automation speeds up delivery and reduces manual errors and administrative burdens. (Supports 🧑‍🤝‍🧑 and 💻.)

• Optimized Resource Management: AI can assess team capacity, monitor workloads, and recommend real-time adjustments to resource allocation, ensuring that sprints are balanced and no one is overloaded. (Supports 🧑‍🤝‍🧑 and 🔄.)

• Better Risk Management: Leveraging historical data, AI can detect early warning signs of project derailment and suggest mitigation strategies, helping teams stay ahead of potential issues. (Supports 🔄.)

• Improved Team Morale and Collaboration: AI’s conversational interfaces can potentially enhance team morale by facilitating smoother communication. AI-powered chatbots and virtual assistants can augment communication and support collaboration across distributed teams. (Supports 🤝.)

• Amplifying Existing Dysfunctions: If Agile fundamentals are weak—such as skipping retrospectives or treating Agile as a checklist—AI can inadvertently magnify these issues. For example, AI-generated code can introduce technical debt if not properly reviewed, and teams may overload sprints by mistaking increased speed for increased value. (Can undermine 🧑‍🤝‍🧑 and 💻.)

• Over-reliance and Loss of Human Judgment: AI is not a substitute for human expertise. It can struggle with complex decision-making, context-specific nuances, and creative problem-solving. Blindly following AI recommendations may lead to suboptimal outcomes, missed opportunities for innovation, or other problems. (Can undermine 🧑‍🤝‍🧑 and 🔄.)

• Quality and Security Risks: AI-generated outputs, especially code, can introduce unexpected bugs or security vulnerabilities. Without careful oversight and regular retrospectives, these risks can accumulate and threaten project stability. (Can undermine 💻.)

• Data and Cost Constraints: Effective AI integration requires access to high-quality data and can involve significant costs for tools and training. Not all organizations are equipped to meet these demands, particularly smaller teams or those with limited budgets. (Can undermine 🧑‍🤝‍🧑 and 🤝.)

• Value 1 (🧑‍🤝‍🧑) - Individuals and Interactions over Processes and Tools: AI can automate routine tasks and streamline workflows, but the heart of Agile remains the collaboration between people. Teams should use AI to enhance communication and free up time for meaningful interactions, not to replace human connection with automated processes.

• Value 2 (💻) - Working Software over Comprehensive Documentation: AI’s ability to accelerate development and automate testing can help teams deliver working software faster. However, teams must prioritize delivering value over generating outputs or reports. AI should be leveraged to support rapid iteration and feedback, not to create unnecessary complexity.

• Value 3 (🤝) - Customer Collaboration over Contract Negotiation: AI-powered analytics and chatbots can provide new ways to gather and analyze customer feedback. Still, Agile teams must ensure that these tools facilitate genuine collaboration with customers, keeping their needs and voices central to the process.

• Value 4 (🔄) - Responding to Change over Following a Plan: AI can help teams anticipate change by identifying trends and risks earlier, enabling more informed pivots. Yet, teams must remain flexible and avoid rigidly following AI-driven plans at the expense of adapting to new information or opportunities.

• Deeper Integration and Smarter Tools: Over the next one to five years, AI is expected to become an integral part of Agile project management, further enhancing sprint planning, backlog management, and risk analysis. AI-powered assistants will likely become more proactive, offering real-time coaching and adaptive workflow recommendations. (Will impact 🧑‍🤝‍🧑, 💻, and 🔄.)

• Focus on Adaptability and Learning: Agile teams will need to continuously adapt their practices to integrate AI effectively—using retrospectives to assess AI’s impact, refining processes, and ensuring that speed does not come at the expense of quality. (Supports 💻 and 🔄.)

• Human-AI Collaboration: The future of Agile lies in balancing AI’s analytical power with human creativity and judgment. Teams that leverage AI as a “collaborative teammate”—rather than a replacement—will unlock greater productivity, innovation, and job satisfaction. (Supports 🧑‍🤝‍🧑 and 🤝.)

• Beall, Justin L. (2024, March 15). Revolutionizing Agile Ceremonies with OpenAI. Available at: https://dev.to/dev3l/revolutionizing-agile-ceremonies-with-openai-a-game-changer-in-software-development-177p.
• Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J., Marick, B., Martin, R. C., Mellor, S., Schwaber, K., Sutherland, J., & Thomas, D. (2001). Manifesto for Agile Software Development. Also known as the Agile Manifesto. Available at: https://agilemanifesto.org/.
• Berlin School of Business and Innovation (2022, September 22). How Do Technical Abilities Combined with Leadership Skills Fuel Career Growth? Available at: https://www.berlinsbi.com/blog/career-advice/how-do-technical-abilities-combined-with-leadership-skills-fuel-career-growth.
• Booklife by Publishers Weekly (n.d.). Agile Protocol: The Transformation Ultimatum. Available at: https://booklife.com/project/agile-protocol-the-transformation-ultimatum-100435.
• Defense Advanced Research Projects Agency (DARPA) (2024, September 27). Teaching AI What It Should and Shouldn’t Do. Available at: https://www.darpa.mil/news/2024/teaching-ai.
• Engineering Research Visioning Alliance (n.d.). Strategic Thinking for Engineering Research in the Era of Artificial Intelligence. Available at: https://www.ervacommunity.org/task-force/visioning-event-strategic-thinking-for-engineering-research-in-the-era-of-ai/.
• Graffius, Scott M. (2016). Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions. North Charleston, SC: CreateSpace.
• Graffius, Scott M. (2018, October 18). Agile Scrum Helps Innovators, Disruptors, and Entrepreneurs Develop and Deliver Products at Astounding Speed Which Drives Competitive Advantage [Presentation]. Talk delivered at Techstars Startup Week Conference. DOI: 10.13140/RG.2.2.25009.12647.
• Graffius, Scott M. (2019). Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change. Scotts Valley, CA: CreateSpace.
• Graffius, Scott M. (2020, November 27). Definition of Agile Culture. Available at: https://www.scottgraffius.com/blog/files/agile-culture.html.
• Graffius, Scott M. (2023, May 1). AI is a Team Sport: A Confluence of Diverse Technical and Soft Skills are Crucial for Success. Available at: https://scottgraffius.com/blog/files/successful-ai-teams.html. DOI: 10.13140/RG.2.2.20321.79200.
• Graffius, Scott M. (2023, October 9). Top 5 Roles on AI Teams. Available at: https://scottgraffius.com/blog/files/ai-team-roles.html. DOI: 10.13140/RG.2.2.34857.57449.
• Graffius, Scott M. (2023). What Successful AI Teams Have in Common [Video]. Graffius’ talk at the 2023 Conf42 Quantum Computer Conference. Available at: https://www.youtube.com/watch?v=u2qRKFbSKYE.
• Graffius, Scott M. (2024, April 5). Cisco Features Scott M. Graffius' 'Phases of Team Development' Work' Available at: https://scottgraffius.com/blog/files/cisco-2024.html. DOI: 10.13140/RG.2.2.16689.60000.
• Graffius, Scott M. (2024, May 3). Leverage Agile and AI to Innovate at the Speed of Light. Talk at private event in Dubai, UAE. DOI: 10.13140/RG.2.2.30790.48960.
• Graffius, Scott M. (2025, January 24). When Agile, AI, and Strategic Thinking Converge. Available at: https://scottgraffius.com/blog/files/when-agile-ai-and-strategic-thinking-converge.html.
• Graffius, Scott M. (2025, January 7). Scott M. Graffius’ Phases of Team Development: 2025 Update. Available at: https://scottgraffius.com/blog/files/phases-of-team-development-update-for-2025.html. DOI: 10.13140/RG.2.2.33705.30564.
• Graffius, Scott M. (2025, May 13). Scott M. Graffius Delivering $2.3 Billion in Value Through AI, Agile, and Project/PMO Leadership. Available at: https://scottgraffius.com/blog/files/scott-m-graffius-delivering-2-point-3-billion-dollars-in-impact-for-organizations.html.
• Graffius, Scott M. (2025). Agile Protocol: The Transformation Ultimatum. Seattle, WA: Amazon Digital Services.
• Hostinger (2025, May 25). Why Software Projects Fail and How to Avoid It. Available at: https://www.hostinger.com/tutorials/why-software-projects-fail.
• Kerzner, Harold (2022). Innovation Project Management: Methods, Case Studies, and Tools for Managing Innovation Projects—Second Edition. Hoboken, New Jersey: Wiley.
• Kilby, Mark (2024, February 2). How AI Will Reshape Agile Development: Takeaways from a Recent Briefing. Agile Alliance. Available at: https://www.agilealliance.org/how-ai-will-reshape-agile-development-takeaways-from-a-recent-briefing/.
• Morsa, Luigi (2022, July 7). Agile. Creativity. Innovation. Available at: https://blog.iil.com/agile-creativity-innovation/.
• Prasad, Baba (2025, May 5). Interpreters, Challengers and Stewards: The Role of Agile Leaders in an AI World. Brown University. Available at: https://professional.brown.edu/news/2025-05-05/agile-leadership-ai-world.
• Tallman, Stephen, and Shenkar, Oded, & Wu, Jay Valerian. (2023). Culture Eats Strategy for Breakfast: Use and Abuse of Culture in International Strategy Research. Strategic Management Review, 4 (2): 193-229.

• It was designed to be out-of-the box, visually striking, and memorable.
• It symbolizes stakes, decision-making, and risk management—all highly relevant to Agile and AI.
• It conveys: "This is a high-stakes game. Play it smart." That resonates strongly with the evolving intersection of AI and Agile.

• About Scott M. Graffius,
• How to Cite This Article,
• and more.

• Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
• Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
• Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.

• Adobe,
• American Management Association,
• Amsterdam Public Health Research Institute,
• Bayer,
• BMC Software,
• Boston University,
• Broadcom,
• Cisco,
• Coburg University of Applied Sciences and Arts - Germany,
• Computer Weekly,
• Constructor University - Germany,
• Data Governance Success,
• Deimos Aerospace,
• DevOps Institute,
• Dropbox,
• EU's European Commission,
• Ford Motor Company,
• Gartner,
• GoDaddy,
• Harvard Medical School,
• Hasso Plattner Institute - Germany,
• IEEE,
• Innovation Project Management,
• Johns Hopkins University,
• Journal of Neurosurgery,
• Lam Research (Semiconductors),
• Leadership Worthy,
• Life Sciences Trainers and Educators Network,
• London South Bank University,
• Microsoft,
• NASSCOM,
• National Academy of Sciences,
• New Zealand Government,
• Oracle,
• Pinterest Inc.,
• Project Management Institute,
• Mary Raum (Professor of National Security Affairs, United States Naval War College),
• SANS Institute,
• SBG Neumark - Germany,
• Singapore Institute of Technology,
• Torrens University - Australia,
• TBS Switzerland,
• Tufts University,
• UC San Diego,
• UK Sports Institute,
• University of Galway - Ireland,
• US Department of Energy,
• US National Park Service,
• US Soccer,
• US Tennis Association,
• Verizon,
• Wrike,
• Yale University,
• and many others.

• Practice Standard for Work Breakdown Structures—Second Edition.
• A Guide to the Project Management Body of Knowledge—Sixth Edition.
• The Standard for Program Management—Fourth Edition.
• The Practice Standard for Project Estimating—Second Edition.

• Certified SAFe 6 Agilist (SA),
• Certified Scrum Professional - ScrumMaster (CSP-SM),
• Certified Scrum Professional - Product Owner (CSP-PO),
• Certified ScrumMaster (CSM),
• Certified Scrum Product Owner (CSPO),
• Project Management Professional (PMP),
• Lean Six Sigma Green Belt (LSSGB), and
• IT Service Management Foundation (ITIL).

Tags: #Agile • #AgileChallenges • #ScrumAndAI • Responding to Change over Following a Plan • Customer Collaboration over Contract Negotiation • Working Software over Comprehensive Documentation • Individuals and Interactions over Processes and Tools • #TechnicalDebt • #TechInAgile • #TeamMorale • #SprintPlanning • #Scrum • #FutureOfAI • #FutureOfAgile • #DataDrivenAgile • #ArtificialIntelligence • #AIRisks • #AIOverreliance • #AIinPM • #AIInnovation • #AIinAgile • #AICollaboration • #RiskManagement • #ProductivityBoost • #FutureOfWork • #AgileFuture • #AI • #AgileWithAI • #AgileValues • #AgileTeams • #AgileSecurity • #AgileMindset

1. Time Pressures: The drive to ship quickly fuels technical debt. Agile sprints, continuous delivery, and market demands pressure teams to cut corners on design, testing, or documentation, incurring debt that grows over time.
2. Complex Designs: Complexity from legacy monoliths, sprawling microservices, or tangled integrations raises maintenance costs and fragility. Both over-engineered and under-engineered (overly simplistic) designs can exacerbate technical debt.
3. Non-Compliance with Standards: Disregarding coding, security, or regulatory standards leads to inconsistent codebases and costly vulnerabilities.
4. Skill Gaps or Turnover: Inexperienced teams or high turnover yield suboptimal code and designs. Remote work can worsen knowledge silos, amplifying debt.
5. Poor Code Quality: Copy-pasting code, inadequate reviews, or outdated tools create brittle, hard-to-maintain codebases.
6. Delayed Refactoring: Postponing refactoring due to backlog pressure or fear of breaking features lets issues pile up, becoming harder to fix.
7. Inadequate Testing: Skipping automated unit, integration, or end-to-end tests results in fragile systems with proliferating defects, hindering future changes.
8. Tooling Mismatches: Outdated libraries, unsupported frameworks, or incompatible tools generate hidden debt.
9. Infrastructure Mismanagement: Mismanaged cloud resources, container sprawl, or neglected infrastructure-as-code drive related debt.
10. Security Neglect: Ignoring vulnerabilities or skimping on security creates risky debt with regulatory and reputational fallout.
11. Documentation Gaps: Missing or outdated documentation, such as for code, APIs, AI model parameters (e.g., unrecorded training data assumptions), or embedded system firmware (e.g., untracked hardware specs), slows onboarding and raises error rates.
12. Cultural and Process Issues: Poor visibility, unclear ownership, inadequate code reviews, or siloed teams (e.g., frontend-backend disconnects causing redundant code) foster systemic debt.
13. Data Debt: Poor data quality (e.g., incomplete, inconsistent, or inaccurate datasets, especially in AI/ML), inadequate data governance or lineage, data silos or inaccessible datasets, outdated or undocumented data schemas, and hardcoded data dependencies create inefficiencies and costs that compound over time. In AI/ML projects, where data is a core asset, issues like unoptimized training datasets, model drift, and lack of data traceability significantly hinder scalability and accuracy.
14. External Dependency Debt: Reliance on unstable, deprecated, or poorly maintained external systems, APIs, or vendor services leads to cascading failures, forced migrations, or performance degradation that compounds over time. This refers specifically to third-party or external dependencies.
15. Service Debt: Suboptimal or out-of-date internal services or service integrations (e.g., incompatible versions or unstable dependencies within the organization’s own systems) lead to maintenance overhead and system fragility. This is distinct from external dependency debt, which involves third-party systems.
16. Build Debt: Inefficiencies or fragility in the build, integration, or deployment process (e.g., slow builds, broken pipelines, or manual steps) that hinder rapid development and delivery.

• Higher Maintenance Costs: More time fixing bugs or updating legacy code than innovating.
• Slower Delivery: Complexity and instability bog down teams.
• Poorer Quality: More defects and security risks.
• Lower Morale: Developers frustrated by brittle, unclear code.
• Rewrites: Severe debt may necessitate costly system rewrites.

• Simplify Designs: Prioritize straightforward, modular architectures.
• Refactor Regularly: Leave code cleaner than you found it.
• Test Rigorously: Automate unit, integration, and end-to-end tests to catch issues early.
• Review Code: Use peer reviews and pair programming to maintain quality.
• Track Debt: Log technical debt in backlogs or dedicated systems.
• Address Debt in Sprints/Cycles: Include debt remediation in the definition of done.
• Allocate Debt Control Budgets: Dedicate time to reduce debt.
• Enforce Standards: Use linter tools which automatically flag code issues and enforce style rules, static analysis tools like SonarQube, and architectural reviews.
• Automate Operations: Use DevOps and infrastructure-as-code to minimize operational debt.
• Build a Quality Culture: Promote learning, collaboration, and ownership.

• Implement and use the most popular agile framework―Scrum
• Deliver products in short cycles with rapid adaptation to change, fast time-to-market, and continuous improvement
• Support innovation and drive competitive advantage

• "One of the best Scrum books of all time" ― BookAuthority
• "The book highlights the versatility of Scrum beautifully" ― Literary Titan
• "A superbly written and presented guide to team-based project management that is applicable across a broad range of businesses from consumer products to high-tech" ― IndieBRAG
• "The book is excellent" ― Readers' Favorite
• "An all-inclusive instruction guide that is impressively 'user-friendly' in tone, content, clarity, organization, and presentation" ― Midwest Book Review
• "A must-have" ― PM World Journal

• Bibliography,
• Additional Articles,

• About Scott M. Graffius,
• How to Cite This Article,
• and more.

• Brown, N., Cai, Y., Guo, Y., Kazman, R., Kim, M., Kruchten, P., Lim, E., MacCormack, A., Nord, R. L., Ozkaya, I., Seaman, C., & Sullivan, K. (2019). Managing Technical Debt: Reducing Friction in Software Development (SEI Series in Software Engineering). Addison-Wesley Professional.
• Cunningham, W. (1992). The WyCash Portfolio Management System. Addendum to Proc. Object-Oriented Programming Systems, Languages, and Applications, ACM, 29-30.
• DeWyze, John (2023, February 16). The 25 Percent Rule for Tackling Technical Debt. Shopify Engineering. Available at: https://shopify.engineering/technical-debt-25-percent-rule.
• Ernst, N. A., Bellomo, S., Ozkaya, I., Nord, R. L., & Kruchten, P. (2015). Measure It? Manage It? Ignore It? Software Practitioners and Technical Debt. Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, 50-60. Available at: https://doi.org/10.1145/2786805.2786848.
• Ernst, N., Kazman, R., & Delange, J. (2021). Technical Debt in Machine Learning Systems. In Technical Debt in Practice: How to Find It and Fix It. MIT Press. Available at: https://direct.mit.edu/books/monograph/5160/chapter/3403977/Technical-Debt-in-Machine-Learning-Systems.
• Ernst, N. (2015, July 27). A Field Study of Technical Debt. Carnegie Mellon University Software Engineering Institute. Available at: https://insights.sei.cmu.edu/blog/a-field-study-of-technical-debt/.
• Forbes (2022, August 10). Measuring And Managing Technical Debt. Forbes. Available at: https://www.forbes.com/councils/forbestechcouncil/2022/08/10/measuring-and-managing-technical-debt/.
• Forbes (2025, June 2). How Today's Technical Debt Becomes Tomorrow's AI Roadblock. Forbes. Available at: https://www.forbes.com/councils/forbestechcouncil/2025/06/02/how-todays-technical-debt-becomes-tomorrows-ai-roadblock/.
• Fowler, Martin (2018). Refactoring: Improving the Design of Existing Code (2nd Edition). Addison-Wesley Professional.
• Graffius, Scott M. (2017, September 25). 7 Causes of Technical Debt and How to Avoid It. Available at: https://scottgraffius.com/blog/files/7-Causes-of-Technical-Debt-and-How-to-Avoid-It.html.
• Graffius, Scott M. (2019). Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change. Scotts Valley, CA: CreateSpace.
• Graffius, Scott M. (2025, January 24). When Agile, AI, and Strategic Thinking Converge. Available at: https://scottgraffius.com/blog/files/when-agile-ai-and-strategic-thinking-converge.html.
• Graffius, Scott M. (2025, June 16). Agile for Unicorns: 7 Keys to Thrive; Scott M. Graffius’ Workshop. Available at: https://scottgraffius.com/blog/files/agile-for-unicorns---7-keys-to-thrive---scott-m-graffius-workshop.html.
• Graffius, Scott M. (2016). Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions. North Charleston, SC: CreateSpace.
• Graffius, Scott M. (2025, May 27). AI in Agile: Benefits, Risks, Outlook. Available at: https://scottgraffius.com/blog/files/ai-in-agile-benefits-risks-and-outlook-by-scott-m-graffius.html.
• Graffius, Scott M. (2025). Agile Protocol: The Transformation Ultimatum. Seattle, WA: Amazon Digital Services.
• Kruchten, P., Nord, R. L., & Ozkaya, I. (2012). Technical Debt: From Metaphor to Theory and Practice. IEEE Software, 29 (6): 18-21. Available at: https://doi.org/10.1109/MS.2012.167.
• Martin, Robert C. (2008). Clean Code: A Handbook of Agile Software Craftsmanship. Pearson.
• Martin, Robert C. (2019). Clean Agile: Back to Basics. Pearson.
• McKinsey & Company (2020). Tech Debt: Reclaiming Tech Equity. McKinsey. Available at: https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20Insights/Tech%20debt%20Reclaiming%20tech%20equity/Tech-debt-Reclaiming-tech-equity.pdf.
• McKinsey & Company (2023, April 25). Breaking Technical Debt’s Vicious Cycle to Modernize Your Business. McKinsey. Available at: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/breaking-technical-debts-vicious-cycle-to-modernize-your-business.
• Software Improvement Group. (2025, March 26). Technical Debt and Its impact on IT budgets. Software Improvement Group (SIG). Available at: https://www.softwareimprovementgroup.com/technical-debt-and-it-budgets/.
• Tom, E., Aurum, A., & Vidgen, R. (2013). An Exploration of Technical Debt. Journal of Systems and Software, 86 (6): 1498-1516. Available at: https://doi.org/10.1016/j.jss.2012.12.052.

• Agile for Unicorns: 7 Keys to Thrive; Scott M. Graffius’ Workshop
• Meta and Anduril’s EagleEye and the Future of XR: How Gaming, AI, and Agile Are Transforming Defense
• AI in Agile: Benefits, Risks, Outlook
• National Science Foundation’s LTER Network Features Scott M. Graffius’ Phases of Team Development IP
• Scott M. Graffius Delivering $2.3 Billion in Value Through AI, Agile, and Project/PMO Leadership
• NESEA Conference Session on Innovation Highlights Scott M. Graffius' 'Phases of Team Development'
• U.S. Soccer Scores with Scott M. Graffius' Intellectual Property on Teamwork 
• Scott M. Graffius' Role in Advancing Project Management Institute (PMI) Standards Excellence
• When Agile, AI, and Strategic Thinking Converge
• Scott M. Graffius’ Phases of Team Development: 2025 Update
• Scott M. Graffius' 'Phases of Team Development' was Spotlighted in Journal of Neurosurgery
• Hochschule Coburg (Coburg University) Germany Uses Scott M. Graffius’ Phases of Team Development IP in Coursework on Agile Development
• EU Europass Teacher Academy Features Scott M. Graffius’ ‘Phases of Team Development’ in Leadership Training
• Tufts University Features Scott M. Graffius 'Phases of Team Development' Intellectual Property
• Bayer Employs Scott M. Graffius' Intellectual Property
• Semiconductor Manufacturing Firm Lam Research Features Scott M. Graffius' 'Phases of Team Development' Intellectual Property
• Scott M. Graffius Speaking on Agile, AI, and Innovation at a Private Event in Dubai
• Cisco Features Scott M. Graffius' 'Phases of Team Development' Work
• Scott M. Graffius Speaking on Successful AI at DevDays Europe 2024 Conference
• University of California, San Diego Features Scott M. Graffius’ ‘Phases of Team Development’ Work
• AI is a Team Sport         

• Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
• Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
• Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.

• Adobe,
• American Management Association,
• Amsterdam Public Health Research Institute,
• Bayer,
• BMC Software,
• Boston University,
• Broadcom,
• Cisco,
• Coburg University of Applied Sciences and Arts - Germany,
• Computer Weekly,
• Constructor University - Germany,
• Data Governance Success,
• Deimos Aerospace,
• DevOps Institute,
• Dropbox,
• EU's European Commission,
• Ford Motor Company,
• Gartner,
• GoDaddy,
• Harvard Medical School,
• Hasso Plattner Institute - Germany,
• IEEE,
• Innovation Project Management,
• Johns Hopkins University,
• Journal of Neurosurgery,
• Lam Research (Semiconductors),
• Leadership Worthy,
• Life Sciences Trainers and Educators Network,
• London South Bank University,
• Microsoft,
• NASSCOM,
• National Academy of Sciences,
• New Zealand Government,
• Oracle,
• Pinterest Inc.,
• Project Management Institute,
• Mary Raum (Professor of National Security Affairs, United States Naval War College),
• SANS Institute,
• SBG Neumark - Germany,
• Singapore Institute of Technology,
• Torrens University - Australia,
• TBS Switzerland,
• Tufts University,
• UC San Diego,
• UK Sports Institute,
• University of Galway - Ireland,
• US Department of Energy,
• US National Park Service,
• US Soccer,
• US Tennis Association,
• Verizon,
• Wrike,
• Yale University,
• and many others.

• Practice Standard for Work Breakdown Structures—Second Edition.
• A Guide to the Project Management Body of Knowledge—Sixth Edition.
• The Standard for Program Management—Fourth Edition.
• The Practice Standard for Project Estimating—Second Edition.

• Certified SAFe 6 Agilist (SA),
• Certified Scrum Professional - ScrumMaster (CSP-SM),
• Certified Scrum Professional - Product Owner (CSP-PO),
• Certified ScrumMaster (CSM),
• Certified Scrum Product Owner (CSPO),
• Project Management Professional (PMP),
• Lean Six Sigma Green Belt (LSSGB), and
• IT Service Management Foundation (ITIL).

Tags: #Agile • #AgileDevelopment • Tech Debt • Types of Technical Debt and Their Mitigation Strategies • #TestingAutomation • #TechnicalDebt • #TechDebt • #SustainableCode • #SustainableCode • #SoftwareEngineering • #SoftwareDevelopment • #SoftwareArchitecture • #Software • #ScalableSoftware • #Refactoring • #DigitalTransformation • #DevOps • #DeveloperExperience • #DesignDebt • #CodeQuality • #CodeMaintainability • #CleanCode • #BuildBetterSoftware • Technical Debt