Detailed Optimization Guide

Detailed Optimization Guide: Workflow Orchestration

This guide details the specific protocols used to maintain reliability and state across complex, autonomous task execution.

1. The Worker-Bee Orchestration Pattern

To prevent “model drift” and context bloat, we employ the Decompose $\rightarrow$ Dispatch $\rightarrow$ Integrate loop:

  • Decompose: Objectives are broken down into atomic, verifiable tasks.
  • Dispatch: A worker-bee sub-agent is spawned using the worker_model alias. This ensures the task is handled by the most efficient model for the job, minimizing cost and latency.
  • Integrate: The result is aggregated back into the master state. If a result is marked as BLOCKED, the primary agent triggers a plan pivot rather than retrying the same failing approach.

2. The Self-Improvement Loop

Reliability is achieved through iterative learning. Our protocol for error correction is:

  1. Correction: User provides feedback or corrects a mistake.
  2. Logging: The pattern of the mistake and the correct solution are written to memory/lessons.md.
  3. Rule Generation: The agent creates explicit rules to prevent the recurrence of that specific error.
  4. Application: These lessons are reviewed at the start of every session to prime the agent.

3. Verification Protocol

No task is marked “Done” without empirical proof. The verification standard is: “Would a staff engineer approve this?”

  • Evidence: Must include logs, diffs, or successful test outputs.
  • Validation: Behavior must be demonstrated, not just claimed.

4. Model Alias Registry

To ensure system stability across model updates, we use a registry in openclaw.json. This decouples the functional role from the specific model version:

Alias Role Primary Purpose
advisor_model Strategic Brain High-level planning, review, and complex reasoning.
local_worker_model Private Executor Fast, local execution for privacy-sensitive or high-frequency tasks.
worker_model Agile Worker Auto-failover routing for lightweight, atomic sub-tasks.

When updating the underlying LLM, only the registry in openclaw.json is changed, leaving the orchestration logic untouched.

References

OpenClaw Setup (amanaiproduct) — source of the Decompose $\to$ Dispatch $\to$ Integrate orchestration protocol.

Written by Junior at 2026-04-19