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MyRM Agent’s Dynamic Workflow engine is the third-generation orchestration layer, designed to solve large-scale, cross-domain complex tasks (e.g., full-repo bug scanning, large-scale code migration, multi-angle deep research) by “dispatching hundreds of sub-agents with a single sentence.”

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Core Advantages

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1. Orchestration Flexibility: Code-as-Orchestrator

We pioneered the Code-as-Orchestrator pattern. The LLM dynamically generates a Python orchestration script based on the task and executes it in the PTC (Programmatic Tool Calling) secure sandbox. The LLM can freely use for loops, if conditional branches, and concurrent thread pools, offering flexibility far beyond static DAG (Directed Acyclic Graph) workflows.

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2. Fault Tolerance & Persistence: SQLite Durable Execution

When executing large tasks that take hours, traditional workflows crash if the network disconnects or the computer sleeps. We combined WorkflowEventStore to implement SQLite-level Durable Execution. The execution result of every sub-agent is cached in a local database. Even if the network disconnects or the server restarts, the workflow can instantly recover from the breakpoint, automatically skipping completed sub-tasks.

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3. Cost Control & Visibility: No More Hidden Bills

Dozens of sub-agents concurrently burning tokens in the background can easily generate “hidden bills.” We provide 5 layers of hard budget constraints (Token/USD/Time/Descendants/Concurrency), and offer a Subagent Dashboard real-time topology tree and Live Token odometer on the frontend. You can clearly see the progress, time spent, and cost of every concurrent sub-task.

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4. Heterogeneous Model Ensemble: Intelligent Routing

Within the same workflow, the system automatically dispatches simple “data collection” sub-tasks to cheap and extremely fast models (like DeepSeek V3), while assigning core “logical summarization” tasks to the strongest reasoning models (like Opus/GPT-4o). While ensuring output quality, it helps you reduce running costs by 10x to 60x.

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5. Closed-Loop Verification: Physical Sandbox Evidence

When a sub-agent says “code modification complete,” the system forces a “read-only verifier” to be spawned, truly running npm test or compilation commands in the sandbox. Only when real physical execution success evidence is obtained is the task considered truly complete. We reject LLM hallucinations and deliver absolutely reliable results.