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    AI agent development method

    Six stages. One closed loop. Production-grade AI agents.

    Every AI agent we develop in Irvine follows this six-stage architecture. The output of stage six feeds back into stages three and four — that's what makes the system actually learn.

    1. 01

      Capture

      Ambient, structured collection of every business signal.

      Explore stage
    2. 02

      Normalize

      Parse, enrich, embed and tag — turn signal into searchable structure.

      Explore stage
    3. 03

      Memory

      Working, episodic and semantic memory tiers — versioned and auditable.

      Explore stage
    4. 04

      Reason

      Stateful orchestration, sub-agent decomposition and human-in-the-loop checkpoints.

      Explore stage
    5. 05

      Act

      Write back into source systems through governed MCP servers.

      Explore stage
    6. 06

      Evaluate

      Trace every span, score every output, feed corrections back into the loop.

      Explore stage