Question 1

How do I know if my multi‑agent workflow is too complex for DIY infrastructure?

Accepted Answer

Look for rising incident frequency, growing difficulty debugging failures, and significant engineering time spent on infra instead of features. If multiple teams are building their own ad‑hoc stacks and costs or latencies are becoming hard to explain, you’ve likely crossed the line where a dedicated orchestration layer would provide more value than continued DIY.

Question 2

Can I keep some workflows on DIY infra and move only critical ones to a platform?

Accepted Answer

Yes. Many organizations adopt a hybrid strategy: they keep low‑risk, experimental workflows on DIY setups while migrating core, customer‑facing or compliance‑sensitive workflows to a platform. This lets you prioritize where robustness and governance matter most and reduce migration risk.

Question 3

What are the biggest risks of running multi‑agent AI on self‑hosted infrastructure?

Accepted Answer

The main risks are reliability issues from cascading failures, uncontrolled cost growth from complex workflows, and limited observability that makes incidents hard to resolve. As you touch more sensitive data, gaps in access control, auditing, and policy enforcement also become serious governance risks.

Question 4

Which features should I prioritize when choosing a multi‑agent orchestration platform?

Accepted Answer

Focus on end‑to‑end observability, robust state and contract management, flexible routing and orchestration patterns, and strong security and governance capabilities. It’s also important that the platform integrates well with your existing stack (cloud provider, data stores, monitoring tools) and supports a gradual migration rather than an all‑or‑nothing cutover.