Multiple agents read and write a shared document, progressively building consensus.
Status: Killed | Cost: 2-4x single agent | Complexity: High
blackboard.md:
## Facts (confirmed)
- Metric X: 12.5% (Agent-A, verified by Agent-B)
## Hypotheses (under debate)
- "Strategy Y will outperform" -- A supports, C disagrees
## Action Items (consensus reached)
- ...
Agents read blackboard --> propose amendments --> orchestrator merges --> repeat
Across 6 active projects analyzed during the design review, none needed multiple agents iteratively building consensus on a shared document. Existing orchestrator-controlled blackboards (where only the orchestrator writes) are sufficient.
From GPT-5.4: "Shared mutable prose as blackboard fails. Use structured artifacts, status fields, and claim ledgers instead."
Specific risks:
- Edit wars: agents repeatedly overwrite each other's contributions
- Asymmetric contribution: one agent dominates, making it effectively single-author
- No convergence guarantee: without hard round limits, agents can oscillate indefinitely
- Context bloat: each agent re-reads the entire growing document every round
A single agent that writes a draft, then re-reads it critically ("now review what you just wrote for gaps"), then revises. This self-critique loop captures ~80% of the benefit at a fraction of the complexity.
If you have a task where:
- 3+ agents need to incrementally build a complex document (not just review it)
- The document structure is well-defined (schema, not prose)
- You can implement proper merge conflict resolution
- You're willing to enforce hard round limits (max 5)
Then Blackboard might be worth revisiting — but with structured fields, not free-form text.