Agent and Loop Engineering Patterns

4. Tradeoffs and alternatives

Planning reduces ambiguity and delays feedback when the problem is exploratory. Parallel candidate generation improves search and increases cost and review load. A supervisor simplifies coordination and can become a single point of failure or excessive authority.

Strict iteration caps bound cost and may stop just before convergence. Adaptive budgets can allocate more effort to high-value work and require calibrated progress signals. Human escalation protects judgment and can become a queue bottleneck when decision packets are poor or trivial uncertainty is escalated.

5. Current Mission Control Implementation

At study commit d902fae, Mission Control has graph workflows, dependency validation, bounded concurrency, versioned agent records, model routing, Attempts, retry budgets, leases, reasoned retry, human-intervention events, separate verifier Attempts, learning signals, and explicit terminal completion states. The factory lifecycle also preserves plan approval and WorkOrder scope outside the agent loop.

The studied evidence does not establish a canonical library of orchestration patterns, a production-qualified Task-Specific Agent Profile registry, cross-pattern benchmark, general no-progress or oscillation detector, or automated conditional-routing calibration across production workflows. Implemented mechanisms support these patterns but do not prove them as a complete operating system.