Peeling Back the Layers of Business Processes

When we think of iteration, most of us picture layering on new features, phases, or improvements. In software development and business projects alike, iteration usually means adding. But what happens when progress requires peeling things away instead of stacking more on top?

Iteration in reverse sounds a lot like reverse engineering. That may be a valid definition, but my process is so focused on improvement, and I don't typically use the word 'engineering' in my daily work (though it feels like that more every day).  Peeling back layers helps us get to the core functionality—the simple, essential actions—that we want to replicate and eventually scale. This approach has guided me as I create AI agents, and interestingly, it echoes a Japanese philosophy I adopted in my martial arts training: Kaizen.

Kaizen: Progress Through Small Steps

My teachers didn't use the word Kaizen (改善) often, which translates to “continuous improvement”  but that pattern was built into every training session. Kaizen is about making small, steady changes that compound into extraordinary results over time. Instead of striving for a massive leap forward, the focus is on incremental refinement—patiently breaking down a process, improving each piece, and then reassembling it into something better.

In martial arts, every technique was reduced into micro-movements (motion radicals): the twist of a wrist, the shift of a hip, the grounding of a heel. Each element was practiced in isolation, often tediously, until it became second nature. Only then could we put the movements back together into a seamless flow.

Creating AI agents feels the same way. Instead of racing to build a sophisticated, end-to-end solution, I’ve found myself slowing down, breaking a task into the smallest possible steps, learning from each bug, and layering improvements when the core works consistently.

Reverse Iteration in AI Development

When building AI agents, it’s tempting to aim directly for the big vision—an agent that schedules meetings, drafts emails, understands customer sentiment, or manages projects all on its own. But Kaizen reminds us that progress begins with the smallest building blocks. Think of your AI Agent project as a new white belt. Yes, they can move about the tatami mat, but new karate students need to be told where to put their feet. Exactly where - angle of foot, bend in ankle, and weight distribution. 

That’s where iteration in reverse comes in. Strip the idea down until you’re left with its absolute essence. Then, apply Kaizen: improve it in patient, deliberate increments.

At first, this feels slow,  painfully so. Because a lot of the code may be provided behind the scenes if you're using an AI Agent platform, testing and debugging become critical, and those are often the activities that try one's patience the most.  Each piece you perfect becomes a stable foundation, ready to support the next improvement.

A Business Example: Customer Support AI Agent

Let’s say a company wants to build an AI agent to handle customer support emails. The end goal might be a system that not only classifies emails but also responds intelligently with personalized answers. Here’s how Kaizen and reverse iteration apply:

1. Define the Big Vision: Fully automated customer support agent.

2. Peel Back to Core Functionality: Start with the smallest step—classify emails into “Billing,” “Technical Support,” or “General.”

3. Kaizen Step 1: Ensure the classification model works reliably for just those three categories.

4. Kaizen Step 2: Add basic detection of urgency words like “urgent” or “asap.”

5. Kaizen Step 3: Layer in short templated replies for one category, such as billing inquiries.

6. Kaizen Step 4: Improve with keyword recognition in the body of the message (e.g., “invoice,” “password,” “error”).

7. Kaizen Step 5: Expand response options with slightly more personalization.

By lunchtime on Day 1, you may only have an agent that sorts emails into categories and drafts one simple template response. That’s not the end goal—but it’s a working foundation. With Kaizen, each subsequent improvement builds on this small, functioning core until, step by step, the original vision becomes reality.

Patience as a Competitive Advantage

The hardest part of iteration in reverse is patience. Whether you’re debugging code or training an AI agent, progress can feel microscopic. But Kaizen teaches us to value the micro-step, because it’s only through small, steady improvements that lasting breakthroughs occur.

Reverse iteration strips away the clutter, Kaizen builds it back up, one improvement at a time. Together, they create a mindset that’s both disciplined and creative—focused on essentials but always moving forward.

Closing Thought

Innovation isn’t always about adding more. Sometimes, it’s about peeling back to the essence, then building upward with deliberate care. That’s the heart of iteration in reverse, and Kaizen gives us the framework to stay patient and purposeful as we work toward scalable, repeatable AI agents—or any ambitious project.