What matters most when orchestrating multiple AI agents?

The answers emphasize different priorities—decentralization, alignment, guardrails, system thinking, and context—highlighting a split in focus between technical architecture, coordination, safety, and operational context.

5 answers

Answers

  • Kishan Pandey

    Technical Leader · Cisco

    Decentralized Design

    Kishan Pandey says decentralized design is the answer, since a single giant orchestrator isn't scalable and scalable designs are always decentralized and distributed.

    DataCamp · Watch on YouTube

  • Andrew Somervell

    Founder (Product + Technology) · Hamster

    Alignment

    Andrew Somervell says alignment matters most because it ensures the team moves together toward a shared goal, preventing disjointed efforts and maintaining cohesion in the product.

    Supra Insider · Watch on YouTube

  • Mihai Criveti

    Distinguished Engineer, Agentic AI · Ibm

    Guardrails

    Mihai Criveti says he has personally been calling for guardrails for large language models, for agents talking to other agents, and for MCP servers, and says he implemented Context Forge, an MCP gateway with guardrails applied before and after agent calls.

    The answer starts at 5:57.

    Mixture of Experts · Listen on Apple Podcasts

  • Angie Jones

    VP Engineering, AI Tools & Enablement · Block

    System Thinking

    Angie Jones says a lot of what is needed now is system thinkers, because that is the skill and level people are operating at: building the system in which agents operate.

    Quality Remarks - The Podcast · Quality Remarks - The Podcast · Listen at 40:57

  • Deepak Ramaswamy

    CTO at LightSpun · Lightspun

    Context

    Deepak Ramaswamy says context is one of the two big things to talk about, along with memory, and says to start with context.

    FinStrat Management, Inc. · Watch on YouTube

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