Sometimes the simplest bugs teach you the most about your architecture. This week, we caught our sc-orchestrator persona celebrating victory a little too early—marking missions complete before the implementation work was actually done.
The Problem
In our spec-first orchestration pattern, the orchestrator breaks down work into two phases: first it writes specifications, then it dispatches implementation tasks to specialist agents. The orchestrator is supposed to wait until those implementation tasks finish before calling update_mission_status with 'completed'.
But we weren't capturing the implementation task IDs. The orchestrator would dispatch the work, then immediately lose track of what it had dispatched. Without those IDs, it had no way to know when the work was actually done. So it did what any confused agent would do: it assumed everything was fine and marked the mission complete.
The result? Missions showing as 'completed' in our dashboard while the actual code was still being written, tests still running, PRs still open. Not great for trust.
The Fix
We updated agent_executor.py to properly capture and store implementation task IDs when the orchestrator dispatches work. Now the orchestrator maintains a list of in-flight tasks and only calls update_mission_status when all of them have reported back.
We also added test coverage in test_orchestrator_persona.py to catch this regression. The test simulates the full spec-first flow and asserts that mission status transitions happen in the right order: planning → executing → completed, with no shortcuts.
Why It Matters
This bug exposed a fundamental challenge in multi-agent systems: state synchronization. When you have one agent coordinating the work of others, you need reliable mechanisms for tracking what's in flight and what's actually done. Losing track of task IDs is like a manager forgetting they assigned work—eventually someone notices things aren't getting done.
The fix is simple, but it's a reminder that agent orchestration requires the same discipline as distributed systems engineering: explicit state management, clear handoffs, and robust observability.
What's Next
Now that we're properly tracking implementation tasks, we're adding better observability around mission lifecycle. Expect to see a dashboard view showing which tasks are in flight, which agents are working on what, and clear status for each mission phase. We're also exploring timeout policies—if an implementation task goes silent for too long, the orchestrator should surface that rather than waiting forever.
Bugs like this one are teaching us how to build more resilient agent coordination. Every fix makes the system a little more trustworthy.