How Workrun works

Workrun is not about asking a model one more question. It is about turning a useful AI collaboration into a capability that can run again.

User input + workflow state
        ↓
Agent reasoning / Python code / external tools / human judgment
        ↓
Structured results, run records, evaluation results, and published versions

Workflows arrange steps and state transitions. Apps contain deterministic code and integrations. Agents handle tasks that require reasoning. MCP and Tool Apps give Agents the ability to act.

How this differs from a one-off chat

• A workflow can contain conditions, branches, subworkflows, termination, and human review.
• A run records node state, tool calls, logs, and traces.
• After a failure or pause, it can resume from a checkpoint instead of rerunning everything.
• Evaluation suites and quality gates let teams verify a change before they publish it.