Скачать или смотреть The 45% Trap In Multi Agent Systems: Why More AI Agents Often Mean Worse Performance

Read the full article: https://binaryverseai.com/multi-agent...
Is the "more agents is all you need" heuristic dead? A massive new study from Google DeepMind and MIT analyzed 180 agent configurations, and the results are a wake-up call for AI engineering: adding more agents often degrades performance by an average of -3.5%.

In this deep dive, we unpack the "45% Trap"—the capability ceiling where coordination overhead starts to outweigh the benefits of collaboration. We analyze why Single-Agent Systems are beating Multi-Agent swarms in tool-heavy workflows, how independent agents amplify errors by 17.2x, and the exact architectural topologies (Centralized vs. Decentralized) you need to actually see gains.

If you are building Agentic AI in production, this is the engineering reality check you need.

In this video, we cover:

The Coordination Tax: Why "token debt" kills reasoning capacity.

The 45% Trap: The specific threshold where adding agents yields negative returns.

Topology Battles: Why Centralized orchestration wins in Finance (+80.9%) but fails in Planning (-70%).

The Tool Tax: Why complexity makes swarms dumber than single models.

Engineering Guide: A 3-step framework to audit your stack and fix your agent architecture.

Timestamps:
00:00 The "Add Friends" Myth in AI Agents
00:30 New Study: Google & MIT Stress Test
01:05 The Headline Result: -3.5% Improvement
01:40 Introduction to the "45% Trap"
02:25 Study Methodology: Controlling for Hype
03:20 Defining Single vs. Multi-Agent Systems
04:10 The Coordination Tax & Token Debt
05:10 Massive Variance: From +80% to -70%
05:55 Topologies Explained: Independent to Centralized
07:05 Why Collaboration Fails: Coverage vs. Variance
08:05 The Rule: Capability vs. Coordination Problems
09:00 The Tool Tax: Why Complexity Kills Performance
10:00 Practical Takeaway: Tool-Rich Environments
10:50 Error Amplification: 17.2x Risk Factor
11:55 Engineering Principle: Untrusted Inputs
12:40 Predictive Modeling & Topology
13:30 Decision Framework: Matching Task to Architecture
14:25 Case Study: Finance Wins vs. Planning Fails
15:25 3-Step Guide to Effective Agent Design
16:25 Conclusion: Audit Your Stack & Final Mantra

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