One question I’ve started asking myself is surprisingly simple.
If my AI generates a new architecture today, can it explain why it’s better than the previous one?
Not just describe the implementation.
Actually defend the decision.
Can it explain:
- Why the previous approach became a problem?
- Which constraints influenced the redesign?
- Which alternatives were considered?
- What trade-offs were accepted?
In many projects, those answers aren’t stored anywhere.
They’re scattered across chat history, meetings, GitHub issues, or someone’s memory.
Yet those decisions are exactly what future development depends on.
This is why I think the conversation around Vibe Coding is starting to evolve.
Generating code is becoming a solved problem.
Understanding engineering decisions isn’t.
That’s the gap I’m exploring with Contorium.
Not another coding assistant.
A Project Intelligence Layer that helps AI understand not only what the project is today, but why it became that way.
https://www.contorium.dev/
https://github.com/ContoriumLabs/contorium
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