AI Studio agent builder: Turning agentic AI into operational capability
As CSPs accelerate toward autonomous networking, the question is no longer whether to adopt AI, but how to embed it inside network operations. What if network engineers could design and deploy AI agents themselves? Blue Planet AI Studio agent builder empowers OSS experts to transform domain expertise into governed, multi-agent automation.
Autonomous networking will not be powered by a single AI platform.
Let’s start with reality: no single agentic platform or AI agent can manage the full complexity of a modern communication service provider (CSP) network. The path to autonomous networking requires a coordinated, multi-agent ecosystem built on open standards, where agents collaborate across domains instead of isolated silos.
This approach is already being validated in the industry. As recently announced, Lumen Technologies is adopting Blue Planet AI Studio and AI agents across its network operations to embed AI directly into real-world operations support systems (OSS).
Blue Planet AI Studio provides Lumen and other CSPs with an open, multi-agent, OSS-native environment to operationalize agentic AI today, not as isolated pilots but as production-ready AI. Operations teams can deploy pre-built Blue Planet AI agents, integrate third‑party or partner agents, or create their own using the low-code Blue Planet AI Studio agent builder, while maintaining interoperability through open standards that allow agents to coordinate across vendors and domains.
I’ll dive into the details on AI Studio agent builder below, but let’s first take a step back and look at what makes for effective agentic AI operations.
Building operational AI agents that deliver outcomes
Effective AI in telecom operations does not begin with building agents. It begins with identifying operational friction. The strongest initiatives target manual or repetitive tasks that consume experts’ time and slow execution. These are often activities that require a level of reasoning that can be delegated to well-governed AI agents.
Trusted OSS data does not define the value of the use case, but it makes execution possible. When rich, structured OSS data is accessible through APIs, agents can operate with accurate operational context. Unlike generic AI platforms that rely on heavy data staging or custom integrations, AI Studio connects directly to network OSS data and APIs through Model Context Protocol (MCP) servers.
By focusing first on high-friction tasks and then leveraging accessible OSS data to ground agent behavior, CSPs can deploy AI that delivers measurable impact while reducing complexity.
AI Studio agent builder: Empowering OSS experts to build their own AI agents
To give OSS subject matter experts and developers a direct path to automation, we’ve introduced Blue Planet AI Studio agent builder. It's a low-code, drag-and-drop environment that allows SMEs to build and refine AI agents using OSS-native data, APIs, and workflows they already understand.
Network engineers and operations teams can design, test, and deploy AI agents inside their OSS environment without waiting for data science teams or large IT transformation projects.
This is not AI in a lab. It is AI integrated directly into operational processes.
AI Studio embeds governance at every layer. Its LLM gateway enforces model access and role-based access control to govern who and what agents can access, and AgentOps provides full traceability of agent decisions and API actions.
The result is a practical, controlled path to automation. Engineers can target high-friction repetitive tasks, deploy narrowly scoped agents, measure impact, and iterate quickly. AI Studio turns operational expertise into executable automation, accelerating time to value while keeping control firmly in the hands of OSS teams.
AI Studio does not operate as a standalone tool. It is part of Blue Planet’s broader agentic AI framework, organized into three layers: agentic tooling, the agentic core, and agentic channels. AI Studio serves as the unified control center that bridges AI, human operators, and governance across the Blue Planet portfolio. Agent builder sits within the agentic core of AI Studio, providing low-code capabilities to create, manage, and integrate AI agents with OSS-native data.
How AI Studio agent builder works
Within AI Studio agent builder, agents are constructed using structured flows that combine LLM reasoning, domain-specific tools, APIs, and operational logic into governed, executable automation.
Agent builder operates within the broader AI Studio environment, which includes the AI agent hub, MCP toolbox, knowledge base, LLM gateway, and AgentOps. Together, these components form a complete operational framework for building, orchestrating, and governing AI agents. This ensures that agents are not created in isolation but managed as part of a coordinated, multi-agent ecosystem.
Once deployed, agents are registered within the agent hub and become discoverable by the Supervisor Agent. Through Blue, the conversational AI assistant embedded in Blue Planet applications, operations teams can invoke all available agents directly within existing OSS workflows. This allows CSPs to introduce AI-driven automation into daily operations without rebuilding their integration stack or disrupting established processes.
How to start operationalizing agentic AI
Operationalizing agentic AI does not require a broad transformation initiative. It starts with focus.
The most effective starting point is a clearly defined, high-impact workflow where OSS-native data is already accessible, and the process is well understood by domain experts. Once the target use case is identified, teams can use the MCP toolbox to connect directly to relevant OSS data and APIs, ensuring the agent operates with the right and accurate operational context.
From there, engineers model the workflow in agent builder’s visual, low-code interface, defining how the agent reasons, selects tools, and executes actions within established guardrails.
After validation, the agent is deployed into Blue Planet OSS applications through AI Studio and becomes immediately accessible within operational workflows. Built on open standards such as Agent2Agent (A2A) protocol and the Model Context Protocol (MCP), each agent integrates into a multi-agent environment. Early deployments deliver measurable improvements while reinforcing the architectural foundation for a scalable, governed agentic operating model.
Building the operational foundation for autonomous networks
Blue Planet AI Studio gives CSP teams a practical path from automation strategy to operational execution. It transforms automation ideas into governed, production-ready AI agents built on the OSS-native data and tools teams already rely on.
With a low-code design, embedded governance, and open standards such as Agent2Agent communication and the Model Context Protocol at its foundation, AI Studio enables agents to operate within a coordinated, multi-agent ecosystem that scales with network complexity.
The journey to autonomous networking does not begin with large-scale transformation. It begins with focus. Identify a high-impact workflow, deploy a narrowly scoped agent, measure the outcome, and iterate. This is how agentic AI moves from concept to capability inside real OSS environments.
If you are attending Mobile World Congress, I invite you to see AI Studio agent builder in action. Visit the Blue Planet team to explore how CSPs, like Lumen, are embedding agentic AI directly into OSS workflows and building the operational foundation for autonomous networks.