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Meshack Mogire

Visualizing Agentic Workflows with Mermaid

·223 words·2 mins
Author
Meshack Mogire
Building production-grade platforms from Nairobi. Django · FastAPI · React · Docker
Table of Contents

Mermaid.js AI Architecture Documentation

Complex systems require clear visualization. I use Mermaid as Code to document the decision loops of my autonomous AI agents.
Pro Tip: Treating diagrams as code means your architecture documentation evolves in the same commit as your implementation. No more stale .png files!

Why Visualization Matters
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When building AI Agents that can use tools, query databases, and make decisions, the control flow can get complicated fast. Mermaid allows me to version-control my architecture alongside my code.

Agent Decision Loop
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Here is the actual logic flow for my Local AI Context Server:

sequenceDiagram
    participant User
    participant Gateway
    participant Agent
    participant MCP_Server as MCP Server
    participant VectorDB

    User->>Gateway: Query: "Summarize last week's logs"
    Gateway->>Agent: Route Request
    Agent->>Agent: Analyze Intent (Thinking...)
    
    alt Needs Context
        Agent->>MCP_Server: Call: fetch_logs(days=7)
        MCP_Server->>VectorDB: RAG Search
        VectorDB-->>MCP_Server: Relevant Chunks
        MCP_Server-->>Agent: Structured Log Data
    end
    
    Agent->>Agent: Synthesize Answer
    Agent-->>Gateway: Response
    Gateway-->>User: "Here is the summary..."

Infrastructure State Machine
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For my Self-Healing Infrastructure, I model the recovery states like this:

stateDiagram-v2
    [*] --> Healthy
    Healthy --> Degraded: High Latency / Error Rate
    Degraded --> Healing: Auto-Scaler Triggered
    Healing --> Healthy: Health Check Pass
    Healing --> Critical: Health Check Fail
    Critical --> Alerting: PagerDuty Trigger
    Alerting --> [*]: Manual Intervention

Conclusion
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Diagrams like these live directly in my markdown documentation, ensuring they never go out of date.