
Humans Are End-to-End, LLMs Are Middle-to-Middle
Humans perceive and verify end-to-end, while LLMs reason middle-to-middle. How combining both creates a powerful two-layer PDCA loop for learning together.
Where Traditional Excellence Meets Modern Intelligence

Humans + AI > Problems
Sustainable improvement requires more than technology. It demands the right combination of advanced tools, disciplined behaviors, and committed management. When humans and AI work together, guided by Lean principles, we create solutions greater than either could achieve alone.
Exploring the practical intersection of Lean thinking and AI innovation

Humans perceive and verify end-to-end, while LLMs reason middle-to-middle. How combining both creates a powerful two-layer PDCA loop for learning together.

The signals surrounding AI couldn't be more confusing — warnings of massive unemployment, glitzy robot demos, yet quiet transformation happening in software and consulting. The key lies in understanding Big AI versus Narrow AI, and partnering AI with lean rather than treating it as an all-encompassing solution.

Drawing from 30 years of Lean implementation, this framework shows why successful AI adoption requires three elements working together: Technology, Behavior, and Management systems. When any element is zero, impact is zero. Learn how to multiply results instead of adding them.

After spending some time building various coaching tools with AI, I began to see clear patterns in how people collaborate with large language models. The result is a five-level framework for AI proficiency — from casual chat use to full system integration. It explains why some users create breakthrough results while others see only hype, and how Lean thinking can guide us toward smarter human-AI collaboration.

Tokens vs Torque: 4 Types of Situations and how Ai can augment our abilities.

How I went from a full blown skeptic to a believer in the positive use cases of Ai in conjunction with topics like problem solving and Lean Thinking