Add Human Approval Checkpoints to Agentspan Workflows

Agentspan is presented as an execution layer for Python-defined AI agents that compiles agent definitions into server-side workflows with durable state, tool histories, and UI-based execution status. The walkthrough demonstrates a production-change agent that retrieves rollout context and requires human approval before invoking an `execute_rollout` tool, using the `approval_required=True` setting to pause the existing workflow rather than create a separate approval process. Tested with Agentspan 0.1.3 and a local server, the example deploys and starts an agent execution, displays the waiting run in the UI, and allows a reviewer to approve the pending tool call so the same execution resumes and completes under its original ID. This approval-gated pattern is intended for higher-risk actions such as production deployments, publishing, refunds, and financial operations, where human review is needed without losing workflow state.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.