Agent Workflow Reliability Gate (QA)

Agent Workflow Reliability Gate (QA)

1. 01

   Define success criteria for each agent in the chain

   Specify acceptable output formats, accuracy thresholds, and latency bounds per agent. For example, a data extraction agent must return structured JSON with <2% field error rate.

2. 02

   Inject known-edge test cases into the orchestration pipeline

   Feed each agent inputs that are incomplete, ambiguous, or out-of-distribution to verify graceful failure handling. Log whether the agent returns a fallback response or crashes the chain.

3. 03

   Verify fallback logic exists for every agent failure mode

   Check that the orchestration layer has retry policies, timeout escalations, and alternative agent routing. Without these, a single agent failure stalls the entire workflow.

4. 04

   Run end-to-end dry runs with production-like data volume

   Simulate a full client workflow (e.g., data extraction to content generation to compliance check) using anonymized client data. Measure total runtime and compare against the 40-60% reduction target.

5. 05

   Audit agent memory and context retention across turns

   Confirm that agents share state correctly through the orchestration layer. For platforms like Raft, verify persistent memory retains codebase knowledge across sessions.

6. 06

   Document all failure points and remediation steps

   Create a runbook that lists each agent's known failure modes, the fallback action taken, and the human escalation path. Share this with the delivery team before client handoff.