Originally published on tamiz.pro.
The Gap Between Demo and Day One
Every team that builds a multi-agent system starts the same way: three agents chatting in a Jupyter notebook, orchestrator routes hard-coded in YAML, output rendered by print(). The demo works. The stakeholders nod. And then someone tries to hit the endpoint with 50 concurrent requests and the whole stack collapses into recursive loops, unbounded token consumption, and a Postgres table that forgot its indexes.
Multi-agent architectures are not harder than monolithic ones because the code is more complex. They are harder because the system's failure modes are emergent — they live in the interactions between agents, not in any single component. A well-tested single agent can still produce a broken system when paired with another well-tested agent whose output format assumptions don't match the receiver's input contract.
This article is not about whether to use multi-agent patterns. It is about what actually breaks when you move from prototype to production, and the concrete engineering work required to stop treating production as an afterthought.
