From Feeling to Fruition

Hi, I'm Christi Mahu, the human behind Rainbokeh: an indie consulting practice focused on Applied AI serving studios and creative-focused small to mid-sized businesses.

My career so far has looked more like a series of pivots than a single linear path. I started in technical support before moving into SEO and social media marketing, then web design, front-end engineering, and eventually back-end and systems engineering.

From there, I transitioned into game development, 3D design — including modeling, sculpting, and animation — as well as AR/VR software development.

Later, I led teams building cloud and data architectures alongside the supporting DevOps systems. Eventually this path led to directing product at a live data migration company, where I was responsible for the user experience, visual design, cloud architecture, software engineering, product marketing, roadmap strategy, and workflow systems behind a new flagship cloud migration platform.

Throughout it all, my work has always been about building bridges between technical systems and creative work, anchored by a hyper-focus on white-glove customer experiences. Whether I was architecting distributed systems or composing sound design in my studio, I found that these interests didn’t compete — they compounded.

From the outside, this kind of path is often stigmatized as nonlinear.

From the inside, for me, it never felt scattered; it felt like a system that didn’t yet have a name.

Feelings: Linearity

Yet like many people with broad interests, I constantly felt pressure to “pick a lane.” Modern professional culture rewards specialization. Résumés flatten identity into categories. Algorithms reward clarity, consistency, and optimization. The result is that many people quietly compartmentalize meaningful parts of themselves in order to remain professionally legible.

Some relationships between disciplines are difficult to explain until you’ve lived them.

A musician may quietly become better at leadership because they understand emotional pacing and tension. A photographer may become better at systems architecture because they think constantly about framing, composition, and perspective. A software engineer may become better at product strategy because years of creative practice trained them to recognize emotional patterns in human behavior.

The problem is not necessarily that these paths are disconnected; it may be that we lack language for describing how they reinforce one another.

Foundation: Link

The breakthrough came when I discovered If You're Ambitious But Unfocused, AI Makes You Dangerous by Sandeep Swadia. His framework — the Link Test — is a diagnostic for determining whether seemingly disparate interests are actually reinforcing systems. It asks:

• Language: Do these areas share a common vocabulary?
• Improve: Does improvement in one benefit the other?
• Need: Are the tools of one required to solve problems in the other?
• Cut: Would cutting one diminish the other?

This was the unlock I needed.

It reframed my interests in photography, electronic music, graphic design, software engineering, systems architecture, storytelling, and neuroscience-adjacent research from distractions into signals. They were not competing identities. They were participating in the same operating system.

The Link Test gave me language for something I had intuitively felt for years:

coherence can emerge through integration rather than reduction.

Formation: Rings

While the Link Test confirmed the existence of a reinforcing system, I wanted to visualize its depth and structure.

This led me to develop what eventually became LINC-Rings — a second interpretive layer built around the original Link framework.

The outer ring represents visible inventory:

• skills
• interests
• practices
• environments
• tools
• experiences

The inner ring represents recurring operating modes:

• perspective
• integration
• explanation
• reflection
• direction
• stewardship
• curiosity
• craftsmanship

The shift was subtle but profound.

I stopped asking:

“What have I done?”

And started asking:

“What do these experiences become when filtered through me?”

“What kinds of meaning, methods, and patterns emerge when these experiences pass through me?”

That distinction changed everything.

The screenshot below shows the original napkin-sketch version of the framework.

The framework itself is intentionally simple. It can be explored with nothing more than a notebook, a pen, and time to reflect. The app is not meant to replace that process. It simply creates another way to interact with the framework — one that can occasionally surface relationships or patterns worth sitting with a little longer.

Sometimes the connections feel immediately obvious. Other times, something unexpected appears and quietly lingers in your mind after you close the browser.

The goal isn’t for AI to tell you who you are. It’s to create moments where patterns you’ve quietly felt for years suddenly become visible.

Fruition: Purpose

One of the things I became increasingly aware of while building this framework was how often modern systems encourage people to disconnect from meaningful parts of themselves.

Work becomes disconnected from craft.

Technology becomes disconnected from curiosity.

Creativity becomes disconnected from livelihood.

Rest becomes disconnected from worth.

People begin optimizing themselves for visibility rather than meaning.

And technology increasingly accelerates that pressure.

Many modern systems are built to:

• maximize engagement
• flatten identity into metrics
• automate attention
• reduce reflection
• and optimize human behavior into predictable patterns

But technology does not have to function that way.

There was a time when technology often behaved more like a companion to life rather than a replacement for participation in it.

Cameras helped preserve memory rather than perform identity for algorithms. Synthesizers invited experimentation. Computers encouraged curiosity. Early creative software felt exploratory rather than extractive.

That relationship to technology deeply shaped Rainbokeh’s philosophy.

I’m not interested in AI replacing human creativity, emotional growth, craftsmanship, or connection.

I’m interested in AI helping humans:

• think more deeply
• create more intentionally
• preserve meaningful practices
• reduce unnecessary friction
• and reconnect with what actually matters to them

That distinction is extremely important to me.

Why Rainbokeh Exists

In early 2025, I left the traditional 9-to-5 world and gave myself a challenge: complete the University of Washington’s intensive nine-month Machine Learning Certificate program without manually typing a single line of code.

That statement tends to provoke reactions, so it’s important to clarify what I mean.

I was not trying to avoid learning engineering fundamentals. Quite the opposite. I wanted to see what happened when implementation syntax became less central than systems thinking, orchestration, architecture, and conceptual understanding.

While LLMs were permitted in the program, they were often treated like advanced search engines. I wanted to push further and explore them as collaborative technical companions.

By orchestrating multiple models — relying on custom GPTs to maintain my voice in documentation, leaning into Gemini’s massive context window for proofing complex systems, and using Claude to generate testable, expandable code — I shifted my energy away from repetitive implementation and toward:

• architecture
• systems thinking
• reflection
• synthesis
• and understanding core concepts deeply

Fast forward to today’s landscape of agentic AI.

We’ve moved far beyond chatbots discussing code theoretically. Tools like ChatGPT Codex, Claude Code, and Gemini CLI are now operating directly in terminals, handling:

• cross-file integrations
• DevOps workflows
• infrastructure scaffolding
• Git operations
• testing
• and architectural iteration

This level of automation is becoming increasingly common in technical fields.

But creative industries present a very different challenge.

How do we use these systems to:

• organize massive libraries of creative assets?
• preserve artistic intent across scaling workflows?
• generate designs that remain emotionally and stylistically coherent?
• help musicians iterate without flattening experimentation?
• support craftsmanship rather than replacing it?
• help humans remain connected to meaning while increasing capability?

That is the space Rainbokeh is interested in exploring.

Creative organizations move through taste, iteration, emotion, and ambiguity — not just enterprise process.

I help these teams navigate the AI era by building systems that respect the creative process rather than flattening it into optimization alone.

Because ultimately, I don’t think the future question is:

“How much can AI automate?”

I think the more important question is:

“What kinds of human lives do we want AI to help us build?”

Some people may want highly ambitious, fast-moving, intensely productive lives.

Others may want slower, simpler, more craft-oriented lives centered around:

• family
• art
• music
• community
• ecology
• contemplation
• or embodied living

I believe AI can help support either path.

The technology itself is not the value system.

Humans choose the values.

Rainbokeh exists because I believe AI should help humans flourish more deeply — not become more disconnected from themselves.

The LINC-Rings Framework

Ready to begin exploring the through-line of your own experiences and interests?

Some people may immediately recognize patterns they’ve quietly felt for years.

Others may simply enjoy exploring the relationships between their interests.

Both outcomes are valid.

Get In Touch

If your organization is exploring how to integrate AI while preserving:

• creativity
• emotional authenticity
• craftsmanship
• intentionality
• and meaningful human experience

I’d love to talk.

You can reach out through the Contact page or the social links below.

Thanks for reading.