Dify Workflows and Chatflows: Designing a Reviewable Agent Process

Evidence check: 25 October 2026. Product details reflect the referenced documentation observed at this cutoff; exact plans, prices, regional eligibility and unverified release dates are not claimed. This is an editorial guide, not a hands-on test.

Workflow and Chatflow serve different entry points

Dify documentation distinguishes workflows from chatflows: both share orchestration ideas, while their triggers and interaction patterns differ. A document-processing task may begin with a scheduled or externally triggered workflow. A knowledge assistant may need a conversational interface with each user message going through a structured flow. This distinction matters because conversation state must not substitute for operational records or granted permissions.

Work through a complete intake flow

Start with an authenticated file and an allowlisted document source. A first node validates file size, format and tenant identity; a second retrieves supporting policy; an extraction node proposes fields; a rule branch checks required values. A reviewer can inspect uncertain results before a deterministic connector stores a draft. Give the model no direct write credentials until the final action contract is in place. When a file includes a fake instruction to send data to a different address, the process should treat it as document content, not a new workflow instruction.

Debugging is not governance

Visual traces and node-level output can reveal which branch ran and what data passed between stages. They do not independently prove that retrieval observed access controls or that a payment was performed correctly. Keep an application audit event for the authenticated principal, source version, approval hash and external record ID. Configure sensitive execution-history retention and restrict who can inspect raw files and prompts.

Handling changes and failures

Version each flow and test what happens when a node is renamed or its output schema changes. Define branch behavior for missing documents, malformed model output, exhausted budget and a reviewer who declines. Run duplicate webhook deliveries and simulate a remote timeout after the final write. If a component lacks durable pause/resume behavior in the installed release, implement it outside the agent rather than silently replaying the entire visual graph.

Choosing alternatives

A team wanting Python-first typed logic may prefer PydanticAI; event-driven integrations may suit n8n or Make; complex stateful code flows may suit LangGraph. Evaluate the actual edition, hosting method and document-retention controls before procurement. Screenshots of an editor cannot establish all node features, local language availability or a customer’s tier entitlement.

Migration checklist

Before moving a visual flow from testing to production, export its configuration and write down exact node versions, tool credentials, accepted event formats, fallback rules and the reviewer’s escalation channel. Use a sample case that touches no real personal data. Run the flow twice with the same event identifier; the second run should not generate a duplicate draft. Check what happens if an editor rejects a proposed field and if a tool returns an empty result. Compare actual state changes to the graph’s intended path.