Multi-Agent Systems · Production System
Multi-Agent SDLC Orchestration & Jira Triggers
Autonomous agent execution embedded into enterprise development lifecycles
TypeScript Playwright Azure DevOps Jira API Docker Node.js
01 // The Problem Space
Manual verification across high-velocity marketing campaigns and enterprise content pipelines was creating multi-day bottlenecks and vulnerability to defect escapes.
02 // The Solution & Architecture
Architected an end-to-end multi-agent pipeline where Jira issue transitions trigger autonomous agent workflows for marketing operations, content consistency, accessibility audits, and regression verification.
▸ Event-driven webhook listeners hooked into Jira status transitions and Azure DevOps CI/CD triggers.
▸ Specialized agent roles: SEO validator, a11y auditor (WCAG 2.2 AA), copy compliance agent, and Playwright test orchestrator.
▸ Centralized orchestration bus managing agent state, tool execution, and PR validation comments.
03 // Execution Sequence & Workflow
01. Jira Issue Transition Ticket moved to 'Ready for AI Validation' triggers an event webhook containing issue metadata.
02. Agent Swarm Dispatch The orchestrator provisions specialized worker agents based on ticket labels (e.g. #marketing, #seo).
03. Tool Execution in Sandbox Agents run Playwright tests, validate schema structures, and check WCAG compliance in isolated containers.
04. Evidence Synthesis & PR Report Results are aggregated into a structured markdown report and posted back to Jira and GitHub/Azure PRs.
04 // Risk Analysis & Calculated Mitigations
How we engineer deterministic trust and governance around non-deterministic probabilistic operations.
⚠️ Calculated Risk: Uncontrolled agent loops or infinite tool execution
✓ Engineered Mitigation:
Strict recursion depth limits (max 5 hops), timeout boundaries, and deterministic token quotas per task.
⚠️ Calculated Risk: Drift in accessibility compliance (WCAG 2.2 AA)
✓ Engineered Mitigation:
Automated Playwright axe-core audits executed in headless CI/CD before any agent-generated PR merge.
⚠️ Calculated Risk: Security & prompt injection via user-supplied Jira tickets
✓ Engineered Mitigation:
Input sanitization layer and scoped system prompts with strictly non-executable payload wrappers.
05 // Verified Impact Proof
✓ Reduced QA cycle time across squads by 20%
✓ Automated validation for 100% of marketing and content releases
✓ Near-zero accessibility defect escape rate
Explore Next System Brief
Principal QA Automation Engineer · Morningstar