Demo Theater

Transforming AI inference from a centralized bottleneck into an intelligent, globally distributed compute cache that instantly adapts to user demand.

Presenters:

• Duan Lightfoot — Senior Developer Advocate, Akamai

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How do you stop an AI agent from leaking API Keys, OAuth tokens, or secret credentials? “Hey, here is my API key, can you do this for me” an AI agent can easily ask another agent/API/MCP server. The answer is simple. Don’t give them any credentials. So how do they do any meaningful work then? Inject the credentials on egress. In this quick session, we’ll look at credential brokering for AI agents and how agent gateways can be used for this.

Presenters:

• Christian Posta — Global Field CTO, Solo.io

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Guardrails live inside the model, and a model can be talked out of them. This demo puts enforcement in the runtime instead, a single control plane that every agent tool call passes through. Your identity system and your own policies decide what each user’s agent can see and do, and the runtime applies those rules and logs every call it allows or blocks. Watch it hold a wire transfer for human approval, strip customer PII from a response before the model reads it, and shut down a user who borrowed a colleague’s connection to reach tools they were never granted.

Presenters:

• Shub Argha — Head of Forward Deployed Engineering, Arcade.dev

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See Device Connect in action as an AI agent discovers and interacts with real-world devices. We’ll demo the end-to-end flow live, showing how developers can connect agents to device capabilities and extend agentic experiences beyond the cloud and into the physical world.

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If you expose your APIs as MCP tools one endpoint at a time, you leave it to the agent to run a multi-step business process on its own. It decides the order of calls. It has to handle partial failures. It might skip a step you assumed was required.

This session shows a different way to build MCP tools. A composite tool wraps an entire multi-step process, including validation and rollback, into one action the agent calls once instead of five. We will build one live. A multi-step order fulfillment process becomes a single governed MCP tool, with every call tied to the real user making the request instead of a shared service account.

If you are building MCP servers by wrapping endpoints one at a time, this talk shows the problem with that approach and a way to fix it.

Presenters:

• Tyler Lamparter — Product Portfolio Strategist, Celigo

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An AI gateway is only as performant as the data layer powering it. Join Jerod Johnson, CData’s Director of Technology Evangelism, for a live walk through of the Connect AI Gateway, built to govern what agents do at the data layer, and ground them in context that spans the organization.

Presenters:

• Jerod Johnson — Director, Technology Evangelism, CData Software

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See Smartsheet’s AI-powered platform become the orchestration layer for your organization’s work. We’ll build a real-time operational dashboard live with Smartsheet AI: standardized reporting, exception-based alerts, and views that leadership trust.

Presenters:

• Brian Gann — Principal Solutions Engineer, Smartsheet

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Porting a frontier model to custom silicon requires deep Neuron expertise, days of iteration, and hard-won knowledge that rarely gets codified. Neuron Agentic Development automates this journey from Hugging Face model to optimized model running on AWS Trainium, AWS’ custom AI accelerator used by leading providers. In this session, we’ll demo using agentic loops to port a model, verify equivalence, and run optimization loops. We’ll also share learnings from building loop engineering in specialized domains.

Presenters:

• Mike Chambers — Senior AI Specialist DA, AWS

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Tokenomics covers the full path from energy and capital into AI, efficiently consuming it, and delivering measurable business outcomes. That path has three stages, and the Tokenomics Foundation is building an open framework to map this new territory. These are the lessons that came out of the working sessions and discussions behind that framework, from the people building and living these problems. Open, neutral, and community-built under the Linux Foundation.

Presenters:

• Stephen Arthur — Member of Technical Staff, Tokenomics Foundation

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AI agents are getting good at taking action. The hard part isn’t making them capable — it’s knowing when to make them stop.

This talk walks the full spectrum of human-in-the-loop patterns: inline confirmations, out-of-band permission gates, and handing your agent a wallet with real money in it. Each fits a different level of consequence. Built around live demos that escalate in stakes with every step, you’ll leave with a mental model and a reference architecture you can use the same day.

Presenters:

• Michael Liendo — Staff Developer Advocate, Okta

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Every organization has workflows buried in back-end systems – work orders, field reporting, asset tracking. They work fine. But AI agents can’t reach them. This demo shows what changes when they can.

The remarkable part: the underlying workflow already existed. It was built years ago. The only new step was exposing it to the AI, and that took under seven minutes – with no code written by anyone.

For enterprise, the message is simple. You don’t need to rebuild anything. Your business logic, your data rules, your integrations – they’re already done.
The missing piece was a way for AI to call them safely. That piece now exists, and getting there requires neither a developer nor any knowledge of the technology underneath.

The question isn’t whether your operations are AI-ready. It’s how quickly you can flip the switch.

Presenters:

• Matt Meeboer — Customer Solutions Specialist, Safe Software

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When people talk about “open source” in today’s AI & ML landscape, they likely think of open models and kick off another debate between “open weights” and truly “open source” models. But open source goes beyond models… it’s behind the most well-known and critical pieces of the ecosystem, from training to chunking data & embedding for RAG to inference to scaling, evals, observability, and optimization. Open source is everywhere and driving much of the AI ecosystem. For this session, we invite technical practitioners and engineering leaders to join Red Hat and open source expert Wesley Chun to learn what some of these critical pieces are, including but not limited to: PyTorch, vLLM, llm-d, OpenShell, OGX (formerly Llama Stack), Docling, and others.

Presenters:

• Wesley Chun — Technical Program Manager – AI, Red Hat

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Learn how to deploy and operate a resilient, air-gapped AI agent platform tailored for harsh industrial environments, including smart factories, offshore oil rigs, and cargo ships. This session demonstrates a production-grade, open-source stack built on Red Hat, Kubernetes, ArgoCD, Keycloak, APISIX, Temporal, and Hitachi Agentic Runtime designed for 24/7 operational continuity without internet connectivity. Discover how to run, orchestrate, and observe stateful LangGraph and Agent Development Kit (ADK) agents directly on the plant floor and remote edge locations with zero telemetry leaks and industrial-grade reliability.

Presenters:

• Georgy Okrokvertskhov — Vice President, Engineering, GlobalLogic

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See how organizations can bring trusted, practitioner expertise directly into AI workflows like Claude, Copilot, and coding environments. We’ll demonstrate how grounding AI in authoritative sources improves technical decisions, code quality, and confidence without slowing teams down.

Presenters:

• Ro Recio — Sales Engineer, OReilly

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One agent invocation fans out into dozens of model calls and tool calls, across shared inference, shared retrieval, and shared infrastructure. By the time it shows up on a bill it is one anonymous number billed to whoever provisioned the cluster. Tags cannot decompose it, and a gateway only sees the traffic that went through the gateway. This session shows a different approach: read the runtime instead of the invoice. We will put a live agent workload on screen and break a single shared pod down to the team, feature, and customer that actually caused the spend, with no tags, no SDKs, and no code changes.

Presenters:

• Amit Kinha — Field CTO, DolT

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Many agentic AI projects risk cancellation due to spiraling inference costs and unmanaged execution. Connecting AI agents to tools via MCP enables powerful workflows, but ungoverned access leads to tool bloat, context rot, and runaway token consumption. In this session, we’ll discuss how Nutanix Agent Gateway – built by maintainers of the AgentRouter open source project – establishes unified runtime control across MCP tool servers and LLM endpoints for enterprises. Learn how to eliminate credential sprawl, enforce function-level tool filtering using MCP Connectors, and apply token rate limiting to prevent bill shock while balancing public and private models.

Presenters:

• Ashwini Vasanth — Group Product Manager for Enterprise AI, Nutanix
• Laura Jordana — Principal Technical Marketing Engineer, Nutanix

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Most agent memory does not need a graph. If a saved value only has to point back to its source message, an ID could be sufficient. But when the same entities appear in different conversations and connect to other parts of the agent’s history. investigating that history is no longer as simple as following a single predefined lookup. It means traversing through the connections in memory from whichever part of the system raised the question.

In the live demo, I’ll connect an agent to an open source agent memory workspace through MCP and retrieve context from conversations outside its current session. I’ll then inspect the resulting context graph, following the connections between the retrieved entities and the earlier messages in which they appeared. Along the way, I’ll distinguish the links agent memory workspace creates during extraction from the provenance an application has to record deliberately.

Presenters:

• Nyah Macklin — Sr. Developer Advocate, Artificial Intelligence, Neo4j

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See how Kong’s unified API and AI platform takes agents from experiment to production: governing a real multi-agent system with A2A communication, MCP tool calls, and multi-provider LLM routing, all with end-to-end observability across the full data path.

Presenters:

• Deirdre Anderson — Solutions Engineer, Kong

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What happens when your AI agent or MCP server goes down mid-task? What about when the API or database it depends on starts dropping connections? Your agent probably won’t give up, because LLMs are persistent. But chances are high that it will redo everything over and over. Re-running tool calls, re-spending tokens, even for work that already finished. You’ll still get your result, just slower, and at a higher cost.

In this live demo, we’ll show what changes with Durable Execution. You’ll join in the fun to become the chaos that breaks our demo. We’ll watch the full execution path (Agent, MCP server, APIs and storage) while Temporal keeps resuming from where things left off, not starting over.

You’ll walk away knowing how durable execution works in both agent code and MCP server code, how retries and replays prevent unnecessary rework and token spend when services fail and recover. Come see how “what if this other system goes down?” stops being a question you need to build custom handling for within your code.

Presenters:

• W. Ian Douglas — Staff Dev Advocate, Temporal
• Melissa Herrera — Senior Developer Advocate, Temporal

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An agent can have the right credentials, stay inside its sandbox, and still do the wrong thing.

Give an agent a box and, like a gas, it will expand to fill every dark corner. The walls define where it CAN go, not where you WANT it to go.

In this live demo, we’ll give an off-the-shelf agent a task and access to ordinary MCP servers. Then we’ll explore the gap between what it can do and what we actually intended. See intent-based authorization at work, without replacing the agent or rewriting the tools.

Presenters:

• Geoff Goodman — Member of Technical Staff, Keycard

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Every application ever built needs to be rebuilt – with agentic AI at the core.

Moving from cloud-native to ai-native means a new architecture for unlocking enterprise data to safely and securely deliver personalized experiences and services at scale.

Delivering business outcomes requires delivering those experiences to employees and customers globally, wherever they live and work.

To build the Agentic Enterprise, enterprises need to rethink their infrastructure strategy, own their data, and own their AI stack.

In this session, we’ll explore a new infrastructure approach to unlock enterprise AI – and how agents can help.

Presenters:

• Kevin Cochrane — Chief Marketing Officer, Vultr

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A look at the future of agent authorization beyond coarse OAuth scopes. A live demo of agent intent governance and where nondeterminism belongs in authz.

Presenters:

• Aaron Tainter — Software Engineer, WorkOS

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