Why AI Engineers Are Building Multi-Agent Systems From the Wrong Direction — and What Great Engineers Do Differently

An architectural argument that multi-agent AI systems should be designed by modeling the domain first — its rules, state, and invariants — rather than starting with agent workflows. Business logic embedded in prompts (e.g., 'never approve claims above €10,000') is fragile because models can misread or ignore natural-language rules. Encoding those constraints as domain errors instead gives agents a feedback loop: when an action is rejected, the agent can reason, retry, or request human approval. This is presented as the design direction behind the next version of Mozaik, a framework introducing shared runtime state that agents can act on concurrently while the domain model enforces rules. The piece ends with a newsletter plug and a hackathon announcement for the Mozaik framework.