Retrieval Augmented Generation (RAG) Retrieval Augmented Generation (RAG) Retrieval Augmented Generation (RAG) is an advanced artificial intelligence technique that enhances the capabilities of generative AI models-like large language models (LLMs)-by allowing them to fetch and incorporate up-to-date, domain-specific, or proprietary information from external data sources in real time. Rod Claar / Friday, May 16, 2025 0 202 Read more
AI-Enhanced Scrum: Transforming Agile Development with Artificial Intelligence Revolutionize Your Agile Development with AI-Enhanced Scrum Rod Claar / Thursday, August 14, 2025 0 109 AI-Enhanced Scrum Course Summary Overview AI-Enhanced Scrum is a comprehensive training program that transforms traditional Agile development by integrating Artificial Intelligence throughout the entire software development lifecycle. This course teaches teams how to leverage AI for enhanced productivity, quality, and consistency from initial requirements gathering through final deployment. What You'll Learn Students master a complete AI-driven development workflow starting with interactive PRD (Product Requirements Document) creation through intelligent AI questioning, progressing through advanced UI design generation using sophisticated non-traditional prompting techniques, UML visual modeling, and culminating in comprehensive technical specification generation that synthesizes all project artifacts. The course covers AI-enhanced Acceptance Test Driven Development (ATDD) and Test Driven Development (TDD) practices, showing how well-crafted tests guide AI development agents to optimal solutions. Students learn to maintain living documentation where PRDs, UI designs, UML models, technical specifications, tests, and code remain perfectly synchronized throughout development. Key Modules AI-Driven Requirements Gathering: Interactive PRD creation with intelligent AI interviewing Advanced UI Design Generation: Revolutionary prompting techniques for interface design Visual Architecture Modeling: UML diagram generation and refinement Comprehensive Technical Specifications: AI synthesis of all project artifacts into implementation guides AI-Enhanced Testing: ATDD and TDD practices with AI development agents Quality Assurance & Defect Resolution: AI-powered debugging and consistency validation Sprint Management: AI-enhanced planning, tracking, and retrospectives Target Audience Perfect for Product Managers, Scrum Masters, UX/UI Designers, Solution Architects, Technical Leads, Development Teams, and Organizations seeking to modernize their Agile practices with AI automation while maintaining high quality and comprehensive documentation. Instructor Expertise Led by an industry veteran with decades of software development experience, from early C++ development to cutting-edge AI implementation, with extensive expertise in teaching Scrum, TDD, software design patterns, and system architecture. Key Benefits Accelerated Development: Faster feature delivery through AI automation Enhanced Quality: Comprehensive testing and documentation consistency Improved Communication: Clear visual models and specifications for all stakeholders Reduced Technical Debt: AI-maintained synchronization across all project artifacts Modern Workflow: Integration of latest AI tools with proven Agile methodologies Course Outcome Graduates will transfo Read more
Critical AI Development - Meta Achieves Recursive Self-Improvement Critical AI Development - Meta Achieves Recursive Self-Improvement Meta announced on July 30th, 2025, that their AI systems have achieved true recursive self-improvement. Rod Claar / Thursday, September 4, 2025 0 78 The Breakthrough Meta announced on July 30th, 2025, that their AI systems have achieved true recursive self-improvement - what researchers call a "guttle machine." This isn't incremental optimization but rather AI that can access and rewrite its own code, making mathematically proven improvements to its own performance. Read more
Keeping Up With AI is a Struggle — But You Don’t Have To Do It Alone AI-Enhanced Scrum turns AI overwhelm into a practical, sustainable advantage for Agile teams. Join the November 5–7, 2025 live virtual course. Rod Claar / Monday, October 13, 2025 0 13 Keeping Up With AI is a Struggle — Summary Feeling overwhelmed by AI? You’re not alone. New models and “breakthroughs” land daily, but the goal isn’t to chase every tool—it’s to integrate the right ones, intentionally and sustainably, into your existing Scrum workflow. The Real Struggle Teams: Pressure to “use AI” without a starting point. Leaders: Noise, uncertainty, and fear of bad investments. Scrum Masters: How to add AI without breaking Agile principles. From Struggle to Strategy AI-Enhanced Scrum connects AI directly to Scrum practices so you can: Improve backlog refinement and sprint planning, reducing ceremony fatigue. Turn vague requests into crisp user stories with acceptance criteria in seconds. Automate repeatables (test cases, retro summaries) and free time for creativity. Measure real ROI in hours saved and increased velocity. Results reported: ~2× faster planning and 30–40% improvement in sprint throughput using these techniques. AI Won’t Replace Scrum—It Amplifies It Use AI to spot blockers early, surface patterns across months of work, and accelerate requirements discovery—while keeping human judgement at the center. Join the Live Program AI-Enhanced Scrum: Transforming Agile Development with AI November 5–7, 2025 — Virtual, Live Register now Final Thought Keeping up with AI isn’t about running faster—it’s about running smarter. Scrum teaches us to inspect and adapt; AI gives us sharper lenses to do it. Stop chasing the future and start building it—one sprint at a time. Read more