My beginning was a black MS-DOS screen.
It was the early 1990s. Before the word “Windows” had become commonplace, many of the computers in Japanese offices ran on an OS called MS-DOS. A dark screen with white text, where nothing would begin unless you typed in commands. In such an era, I began my career at a small software company as a programmer trainee.

At the time, I was in charge of developing measurement and control system software. This involved processing complex data used in factories and research institutions, and then visualizing it as graphs. Unlike today, I couldn’t just look up information on the internet or ask AI for code. I spent my days wrestling with C and assembly language, with thick manuals in hand. That was my first encounter with “technology.”
An Unexpected Turn: From the Development Room to Sales Nationwide
However, the gears of fate began to turn in an unexpected direction. Not long after joining the company, I was assigned to plan and handle nationwide sales for our company’s proprietary software. More than the confusion of “Why sales for a programmer?”, my curiosity to see how the software I worked on would be used in the world won out.

My clients were the research and development, design, production, and quality control departments of renowned major corporations. I was dealing with professionals in their fields, engineers and researchers. A young man in his early twenties presenting to people who supported Japan’s cutting edge. The pressure was immense, and it was there that I hit a “wall.”
Fighting Giants and What I Learned
At that time, our biggest rival was a giant American corporation, Texas Instruments (TI). We were a Japanese venture known only to a select few, facing an multinational company with overwhelming financial resources and name recognition. If we competed solely on feature comparison charts, our software, created by just a few people, stood no chance.

However, as I visited sites and listened deeply to the “troubles” of the researchers, I realized something. What they were looking for wasn’t ultimate multi-functionality, but a “straightforward solution” that would smoothly connect with the measuring instruments in front of them and immediately produce the desired graphs.

I worked closely with the Head of Development, absorbing feedback from the field and reflecting it in the software’s UI, and then heading to another major corporation the next day. How could we implement an intuitive graphical UI within the limited resources of MS-DOS? The “ability to translate technology into business” that I cultivated there became the underlying current of my career.
What “Technology x Sales” Taught Me
My greatest asset gained during those four tumultuous years was not programming skills themselves. It was the immense value of “a person who understands technology, knows the pain points of the field, and translates them into a marketable system.”

No matter how excellent the source code, if it doesn’t solve someone’s problem and return as compensation, it cannot sustain a business. Conversely, if you understand the core of the technology, you can make essential proposals, not just superficial sales pitches.
Returning to the Origin in the AI Era
Today, I run “Sparx,” a company that develops AI agents. Over 30 years have passed, and the tools have changed from MS-DOS to the latest LLMs. However, the essence remains unchanged.

My role is not to espouse the idealistic notion that “anything is possible with the latest AI,” but to create “systems” that enable AI to shoulder the burden for clients by understanding who is suffering from what in their business and how AI can alleviate it.

The journey that began as a programmer trainee in Chapter 1 has, through twists and turns, now reached a new stage in the AI era. I continue to learn the importance of “systemization,” which lies between technology and sales, from these formative experiences in my twenties.

Founder Principles 1: Build systems, not tasks.
What Sparx offers today is not merely an automation tool, but the very “working system” that allows people to concentrate on more human-centric decisions.