?? Can Agent Ops' best tools & practices bring order to Multi-Agent AI Chaos? 1?? Directly Solve 2?? Indirectly help 3??Cannot solve alone
George Polzer
Sr. Product Manager AI/ML | EU & US Go-to-Market / MVP Consultant | Emerging Tech - Agentic AI, Agent Ops Focus??
?? Multi-Agent Systems (MAS) using LLMs to tackle complex tasks often underdeliver. UC Berkeley found MAS frameworks have shockingly low success rates, with correctness as low as 25% across 150+ tasks.
They introduced MASFT—a failure taxonomy of 14 modes across 3 categories:
??Specification & Design Failures
??Inter-Agent Misalignment
??Verification Failures
These are not just bugs or early-stage quirks — they reflect fundamental design flaws in MAS construction.
?? Berkeley draws on High-Reliability Org (HRO) research (think nuclear plants, aircraft carriers), showing MAS errors mirror human org failures:
??unclear roles
??ignored expertise
??missing validation
MAS needs the same discipline as high-stakes teams.
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?? MAS Framework Failure Rates
AppWorld: 86.7% | HyperAgent: 74.7% | ChatDev: 75.0% | MetaGPT: 34.0% | AG2: 15.2%
?? Failure Mode Metrics by Category
??Specification & Design (37.2%):
??Disobey Task Spec: 15.2% | Step Repetition: 11.5% | Unaware of Termination: 6.5%
??Loss of History: 2.4% | Disobey Role Spec: 1.6%
?? Inter-Agent Misalignment (31.4%):
??Reasoning-Action Mismatch: 7.6% | Info Withholding: 6.0% | Conversation Reset: 5.5%
??Task Derailment: 5.5% | Ignored Input: 4.7% | No Clarification: 2.1%
?? Verification & Termination (31.4%):
??Incorrect Verification: 13.6% | Premature Termination: 8.6% | No/Incomplete Verification: 9.2%
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1?? Agent Ops Can Directly Address
- Loss of History (2.4%): Tracks LLM calls & metadata for replay/debug.
- Step Repetition (11.5%): Logs all events to flag inefficiencies.
- No/Incomplete Verification (9.2%): Detects skipped validations.
- Ignored Input / Misalignment: Captures full agent interactions.
- Errors / Premature Termination (8.6%): Logs failures, stack traces, reasons.
2?? Agent Ops Can Indirectly Help
- Disobey Role/Task Spec: Tags divergence; enables manual review.
- Reasoning-Action Mismatch (7.6%): Compare logs & actions.
- Task Derailment: Use tags/flows to catch goal drift.
3?? Agent Ops Can’t Solve Alone
- Poor Task Design/Prompts: Needs better human input/testing.
- Flawed Architecture/Topology: Requires external design review.
- Unstandardized Communication: Needs protocol enforcement.
- Missing Confidence Estimation: Devs must log confidence manually.
?? Source: Arxiv https://lnkd.in/dawYdhRG
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