Agentic AI Lab

How an agent system actually runs

A request comes in. A planner decomposes it, an orchestrator routes the work to specialized agents, those agents call tools and consult memory, and everything is traced for observability and safety. This is the shape of the systems I design.

reference architecture · live

hover a node to trace its links

PLANNER

Breaks the goal into a sequence of steps.

ORCHESTRATOR

Routes work to the right specialized agents.

AGENTS

Research, act and review — each with a job.

TOOLS · MEMORY

Reach external systems; remember context.

OBSERVABILITY

Trace every step; evaluate; keep it safe.

The approach

Four things I never skip

Multi-Agent Orchestration

Coordinating specialized agents — planners, doers, reviewers — into reliable workflows with watsonx Orchestrate and its Agent Development Kit.

Interoperability & Protocols

Letting agents, tools and systems speak the same language with open standards — MCP for tools, A2A for agent-to-agent, and the wider protocol landscape.

Operations & Observability

Monitoring, evaluation and telemetry so you can see what agents actually do — the part most AI projects overlook, and the one that decides success at scale.

Secure & Governed

Treating safety, identity and governance as first-class: agentic systems that are secure, observable and scalable from day one.

Interoperability

The protocol landscape

MCP

Model Context Protocol

Agents ↔ tools, data and APIs through one standard interface.

A2A

Agent-to-Agent

Direct, discoverable collaboration between specialized agents.

ACP

Agent Communication

Structured, session-aware messaging for multi-turn workflows.

ANP

Agent Network

Decentralized, peer-to-peer networks of interoperable agents.