Before going any further, I’ll name the product I’ve been circling to and hinting at the past several posts.
The system I’m building is called CoffeeBreak. It’s a human-in-the-loop AI teammate designed to assist across the entire software development lifecycle.
I’ve avoided leading with the name because this problem exists whether CoffeeBreak ever ships or not. It’s a pattern I’ve seen repeatedly across teams, tools, and organizations.
Many teams ship software that technically works, but only if people know how to compensate for it.
A missing step here. A manual workaround there. A shared understanding that certain things “just need a human to smooth them out.”
Over time, that invisible work becomes normalized.
The problem is that partial workflows don’t fail loudly. They fail quietly. Users adapt. Teams move on. And the cost shows up later as friction, mistrust, and operational drag.
This is especially risky with AI-powered systems.
When a system can generate output but can’t reliably carry context from start to finish, the burden shifts back to the user. They review more. They correct more. They fill in gaps the system was supposed to handle.
From the outside, it looks like progress. From the inside, it feels like babysitting.
CoffeeBreak exists because I don’t think that’s acceptable.
Before adding more tools or features, it’s worth asking a simpler question:
Can one workflow complete cleanly without human glue?
Until the answer is yes, speed doesn’t matter. Coverage doesn’t matter. Demos don’t matter.
End-to-end reliability is the foundation. Everything else is noise.