Enterprises racing to adopt artificial intelligence are quickly realizing that agentic frameworks are redefining how data, infrastructure and workflows must be orchestrated at scale. What once seemed like a backend plumbing issue is now core to strategic differentiation across cloud platforms and data ecosystems.

In a conversation at theCUBE’s NYSE studio, industry analysts Rob Strechay (pictured, left) and John Furrier (right) discussed the shift from isolated AI tools to composable, multi-agent ecosystems. Their analysis emphasized how protocol momentum, metadata innovation and cloud-native flexibility are fueling real-world deployments — and which vendors risk falling behind. Underlying it all is a growing consensus: Success in AI now hinges on how well companies embrace open protocols, catalogs and rapid migration strategies, according to Strechay.

TheCUBE Research’s Rob Strechay talks about agentic frameworks.

“MCP is really the protocol,” he said. “It’s a way to communicate via APIs and basically publish-subscribe. Bedrock is really looking to leverage that. I think you look at SageMaker and what they’re doing, making Nova part of that as well. I think how LLMs get utilized and how different pieces are the MCP, then are the agents using A2A to talk and communicate as you get into these multi-agentic frameworks — a lot of pieces that are moving around.”

During the event, Furrier spoke to experts from AWS, Nutanix and other companies at theCUBE + NYSE Wired: AI + Cloud Leaders Media Week event. They explore how agentic frameworks are reshaping enterprise AI strategies by driving innovation in data orchestration, metadata control, multi-agent systems and platform design across the cloud ecosystem. (* Disclosure below.)

1. Catalogs and control planes take center stage in agentic frameworks

Metadata catalogs are emerging as the control plane for agentic frameworks, centralizing tools, agents and data across stacks. The AWS SageMaker and Bedrock updates reflect this shift, while GSIs such as Deloitte Touche Tohmatsu Ltd. and Accenture PLC push enterprise adoption. Those clinging to legacy infrastructure risk falling behind as agent-to-agent protocols and vector tiering gain traction, according to Strechay.

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2. AI-driven migration accelerates partner innovation

Agentic frameworks are transforming cloud migration from a drawn-out ordeal into a fast, secure and value-driven process. Compressed timelines, cross-platform portability and AI-infused toolchains now empower partners to deliver tailored solutions with real business impact, according to Tarkan Maner, chief commercial officer of Nutanix Inc., and Chris Sullivan, partner sales senior leader, financial services, at Amazon Web Services Inc.

Check out theCUBE’s complete interview.

Nutanix’s Tarken Maner discusses the AI partner ecosystem with theCUBE.

3. Agent workflows and token economics are reshaping enterprise AI

Enterprises are chasing real productivity gains through agentic workflows, but execution is far more complex than hype suggests. Mark Castleman, managing director for Intel AI Cloud at Intel Corp., emphasized the rising importance of prompt-context-model frameworks, cost-aware compute strategies and API monetization as key enablers of scalable, sustainable AI transformation.

Don’t miss the full interview on theCUBE.

4. Neuro-symbolic AI meets the real world

AWS is harnessing the convergence of symbolic reasoning and machine learning to build practical, mathematically verified AI tools, including Bedrock guardrails and automated reasoning checks. This neuro-symbolic approach accelerates innovation while maintaining compliance, correctness and trust at scale, says Byron Cook, vice president and distinguished scientist at AWS.

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5. AWS unveils agentic future for developers

AWS is redefining agent development with Kiro, a spec-driven platform that helps developers build and evolve applications in collaboration with AI agents. Combined with AgentCore’s flexible toolset and protocols such as MCP and A2A, these new offerings simplify agent orchestration and foster scalable, multi-agent systems, according to Deepak Singh, vice president of developer agents and experiences at AWS.

Check out theCUBE’s complete interview.

6. Platform thinking matters in an AI-native world

Enterprises betting on a single AI model risk being outpaced by competitors, according to Randall Hunt, chief technology officer of Caylent Inc. With transformer architectures evolving rapidly, Hunt emphasized building flexible platforms that support tool orchestration, autonomous agents and context-driven evaluation workflows across diverse model ecosystems.

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Intel’s Mark Castleman speaks about agentic infrastructure.

7. Karini AI brings agentic workflows into enterprise reality

Karini AI LLC is cutting through gen AI hype by delivering real-world business process automation using agentic workflows deployed directly in customer VPCs. Its no-code, low-code platform empowers nontechnical users in fields such as law, HR and engineering to build and manage private AI solutions, explained Nitin Wagh, co-founder and chief executive officer of Karini AI.

Don’t miss the full interview on theCUBE.

8. Solving the data bottleneck in AI agent deployment

Enterprises seeking to unlock customer data for AI training often face regulatory, privacy and architectural challenges — but synthetic data offers a path forward. DataMasque Ltd. creates high-fidelity, synthetically identical datasets within clients’ secure environments to enable safe testing of AI agents, according to Grant de Leeuw, co-founder and chief executive officer of DataMasque.

Check out theCUBE’s complete interview.

Here the complete video paylist from SiliconANGLE’s and theCUBE’s coverage of theCUBE + NYSE Wired: AI + Cloud Leaders Media Week event:

(* Disclosure: TheCUBE’s coverage of theCUBE + NYSE Wired: AI + Cloud Leaders Media Week event is brought to you by Nutanix. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE