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How to Coordinate Intelligence Across Teams & Agents with Vijoy Pandey, SVP of Outshift at Cisco

Richie and Vijoy explore the Internet of Cognition, coordination failures in multi-agent systems, agent guardrails, tiny teams with tokens, measuring whether agents are actually better, and much more.
19 Eki 2026  · 65 dk. oku

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Guest
Vijoy Pandey
LinkedIn

Vijoy runs Outshift, Cisco's incubation department for agentic AI and quantum computing. He has two decades of experience as a technology executive across cloud computing, infrastructure, cybersecurity, AI, and quantum networking. Previously, he ran Cisco's strategic research division.


Richie Cotton's photo
Host
Richie Cotton

Richie helps individuals and organizations get better at using data and AI. He's been a data scientist since before it was called data science, and has written two books and created many DataCamp courses on the subject. He is a host of the DataFramed podcast, and runs DataCamp's webinar program.

Chat with AI Richie about every episode of DataFramed - all data champs welcome!

Key Quotes

There's a certain bit of a split between what agents can do and what they're capable of, versus the amount of trust and confidence individuals and enterprises can place on those agents. Sometimes there is this bifurcation in the path where you say, let me go with agent capability, sacrificing trust, versus, let me go with trusted agents, even though I might have to sacrifice some capability. That's where we stand today, but that's not how it should be. You can have it all. You can have trusted agents that provide the maximal capability from the best frontier model out there, and you should not have to choose.

What's happening is that since the productivity unit is shrinking, the coordination surface and the coordination tax is exploding. Smaller teams means intra-team coordination is tending towards zero, but inter-team coordination has just exponentially exploded, because now we have an N squared problem.

Key Takeaways

1

Connecting agents is not the same as coordinating them. Open standards like MCP, A2A and AGNTCY let agents discover each other and pass messages, but they still can't reliably align on intent, agree on terminology or negotiate, so plan for coordination as a separate problem from connectivity.

2

Smaller teams make coordination between teams harder. A tiny team with tokens (one to five humans plus agents) works because judgment, taste and accountability stay with people, but with many small teams you need a shared context layer and named people who keep intent consistent across teams.

3

Judge agents on “better”, not just faster and cheaper. Token costs and speed are easy to measure, but you also need to check that agents are aligned, grounded and completing the task, so add outcome checks alongside your cost and latency dashboards.

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