AGNTCon + MCPCon and PyTorch Conference

AGNTCon + MCPCon
and PyTorch Conference

Building the open foundations for agentic AI

AGNTCon arrived as the agentic AI conversation moved from model capability toward the systems required to make agents work in the real world. Open protocols, shared standards, inference infrastructure, and compatibility are becoming essential pieces of an ecosystem where agents need to communicate, operate across tools, and scale beyond isolated demos.

Coverage from AGNTCon + MCPCon and PyTorch Conference explores the organizations and projects shaping that foundation: the Agentic AI Foundation, new open standards, open-source inference, PyTorch on Google Cloud TPUs, MCP client compatibility, and the governance questions surrounding generative AI. The common thread is interoperability. Agentic systems will need more than capable models; they will need a dependable, open ecosystem around them.

AGNTCon 2026 event floor
AGNTCon’s first edition brought the open agentic AI ecosystem into focus, from shared protocols to the infrastructure needed to put agents to work.
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Ecosystem foundation
Open protocols and shared standards
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Scaling agents
Inference, hardware, and deployment infrastructure
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Trust and adoption
Compatibility, governance, and open collaboration

The big picture

Agentic AI needs an open ecosystem, not another silo

AGNTCon 2026 Themes

From agent protocols to the infrastructure behind them

Agentic AI introduces a new integration challenge: systems must exchange context, invoke tools, coordinate work, and run reliably across increasingly diverse environments. Open protocols and standards can reduce fragmentation, while open-source inference and hardware frameworks help make deployment more accessible and scalable.

The coverage also examines the practical adoption layer. MCP compatibility, project governance, and the ability to understand how different clients behave all matter as developers move from experimentation toward production systems. The emerging question is how the industry can build agentic capabilities that are interoperable, governable, and usable across vendors and platforms.

Key takeawayThe agentic AI stack will depend on open interfaces, compatible implementations, and shared infrastructure as much as on model intelligence.

Continue exploring

Follow the open agentic AI ecosystem

Explore the full event coverage package for perspectives on the protocols, standards, infrastructure, compatibility, and governance shaping how agentic AI moves toward practical adoption.