Building Clad in Public
Building Clad in public is not marketing. It is a way to ship earlier, learn from real reactions, and keep the AI honest about what it actually does for people.
I build Clad in public because the alternative — building quietly until it is "ready" — hides the only feedback that matters until it is too late to act on it.
Clad is an AI personal color service. Building it in the open means I show the decisions, the rough edges, and the reasoning while they are still changing, not after they have hardened into a finished story.
What building in public actually means
It does not mean posting every commit. It means making the decisions visible.
- What I chose to build next, and what I deliberately dropped.
- Where the AI is confident, and where it is still guessing.
- What a real result looks like before it is polished.
The point is accountability. When the reasoning is public, I cannot quietly paper over a weak result with a nicer screenshot.
It forces the product to be honest
An AI demo can look impressive in private. A product used in public has to survive a stranger's first reaction.
That pressure is useful. It pushes Clad away from "look what the model can do" and toward "here is a result you can trust and act on." Building in the open keeps the gap between the demo and the product small, because other people can see it.
If a result only works in a screenshot, it does not work.
The loop gets shorter
Building quietly stretches the loop between a decision and its feedback to months. Building in public compresses it to days.
Someone replies that a palette felt confusing. Someone asks what they should actually do with a result. Those reactions are the real spec — and they arrive while the decision is still cheap to change.
For an AI product especially, that loop is everything: the model improves, but the product only improves when real people tell you where the result stops being useful.
What I am learning
Building in public is not about performing progress. It is a forcing function.
It makes me ship earlier, describe results in plain language, and treat "is this actually useful to a person?" as the question — not "is the model impressive?" For Clad, that is the difference between an AI experiment and a product.