DAG-First Agent Orchestration: Why Linear Chains Break at Scale
Most multi-agent systems start as a chain. Agent A calls Agent B, B calls C, C calls D. It works fine in demos, and it works fine with five agents on toy tasks. Then you add a sixth agent, a seventh, and the pipeline that once ran in eight seconds starts taking forty. You add a retry on step three, and now failures on step three silently cascade into corrupted state at step six. You try to add a parallel branch and discover your framework was never designed for that.
The problem is not the number of agents. The problem is the execution model. Linear chains serialize inherently parallel work, propagate failures in only one direction, and make partial recovery structurally impossible. The fix is not adding more infrastructure on top — it is rebuilding the execution model around a directed acyclic graph from the start.
