So why this, why me, why now?
Tl;dr: because I’ve felt this pain acutely. As a trained Computer Scientist turned Applied Artificial Intelligence (AI) Engineer I spent most of my time focused on writing algorithms, focusing intensely on the code and not really paying attention to what happens to that code when it leaves my Jupyter notebook. One consequence of this was that most of my code was written in a way that was not reliable, and not reproducible. If a software engineer or a devs ops colleague wanted to turn my code into a product, it would have involved a lot of back and forth because they would have to go on the journey of discovering all the implicit dependencies (code, machine, third-party APIs, data, and so forth) that my code needed to work as I envisioned it. Furthermore, if product people wanted to do functional testing on that code, it would have been next to impossible for them to do so.
I founded Fimio to apply machine learning to difficult problems, and realizing that what foundational tooling does exist for shipping AI is mostly focused on training AI and exclusively aimed toward AI engineers, the product we have come to affectionately call VCoW (Version Control over Workflows) began immediately taking shape. From my experience, I knew that shipping AI products involved multiple organizational functions from product management, to developer operations, to infrastructure engineering, and more. And all those teams had to collaborate to ship a product, and all those teams needed to interact with the process at different times. We knew if our goal was to make it straightforward and easy to ship AI products, we had to close the gap that existed between code and deploy phases.