Memory safety for 17-subagent workflows and 100+ skills.
When 17 subagents share memory, drift and consensus collapse risk compounds. A planner agent's assumption becomes an executor's fact. An error in one agent's memory propagates silently through the chain.
from sgraal import SgraalClient client = SgraalClient("sg_demo_playground") # Collect outputs from multiple subagents agent_outputs = { "planner": "Deploy feature X to production", "reviewer": "Code review passed for feature X", "tester": "All tests green for feature X", } # Validate cross-agent consensus before executing result = client.preflight( memory_state=[ {"id": f"agent_{name}", "content": output, "type": "semantic", "timestamp_age_days": 0, "source_trust": 0.85, "source_conflict": 0.05, "downstream_count": 3, "provenance_chain": [name]} for name, output in agent_outputs.items() ], domain="coding", action_type="irreversible" ) if result["recommended_action"] == "USE_MEMORY": deploy()
Track which subagent produced each memory. Detect circular references.
Catch 17 agents agreeing on the same wrong fact from a single source.
Detect subagent authority creep across the orchestration chain.