Product Purpose
About AiBS
What I built, why I built it around ABS, who it is for, and what I want the product to become.
ByColby Reichenbach
I built AiBS to make ABS understandable, inspectable, and actually useful.
I built AiBS as an ABS-first baseball product for people who want the data, the context, and the explanation in one place. I did not want a workflow where someone has to bounce between X, league feeds, and half a dozen baseball sites just to understand one challenge sequence or one argument about an umpire.
I also built it for the way I follow baseball myself. I do not always want to sit through every broadcast. I do want to understand what happened, what changed, and what the evidence actually says. That pushed me toward a product that can surface the important moments quickly, show the supporting data, and make the baseball logic readable.
ABS was the right subject because it naturally produces disagreement. It changes strategy, changes how people talk about officiating, and creates very confident opinions that are often much less precise than the underlying evidence. I built AiBS to tighten that gap.
What I built
I built AiBS as a front door to ABS, not as another generic baseball dashboard.
I built AiBS as one place where a user can move from live context, to team behavior, to umpire exposure, to game-level events, to longer written analysis without leaving the product. I wanted the data, the explanation, and the baseball logic to live together.
I also wanted the product to be useful to more than one kind of reader. Some people want a clean visual front door into the subject. Some want deeper baseball logic. Some want technical details. I built the system so those readers can start in different places without needing different products.
Why I built it
I built AiBS because baseball conversation often moves faster than the evidence behind it.
A lot of baseball discussion now happens on X, but the supporting data is usually fragmented, delayed, or missing. People argue about whether a club is challenging well, whether an umpire is volatile, or whether ABS is helping the sport, but they rarely have the exact data point or visual frame needed to support what they are saying. I built AiBS to make those points easier to find and easier to test.
I also built it for people who care about the data and the dialogue even when they are not watching every game live. I wanted a system that lets someone stay current on the important challenge moments, inspect the numbers behind them, and understand the baseball logic without needing to search across multiple sites.
I am not trying to flatten baseball into charts. I am trying to make baseball discussion more accountable to the data.
Why ABS
I chose ABS because it forces baseball logic, technical logic, and public dialogue into the same place.
ABS is one of the few current baseball topics where rules, geometry, strategy, officiating, and fan reaction all collide in public view. That makes it a strong product subject and a strong modeling subject. It also means I have to build for more than one kind of reader at once: fans who want understandable visuals, baseball people who care about tactics, and technical readers who want to know whether the numbers hold up.
I also embedded AI into that system because the data becomes more useful when more people can actually read it. I use it to make the product more legible, not to replace the underlying evidence.