Autonomous ticket resolution
Autonomous Ticket Resolution (ATR) is Port's approach to automating the full software delivery lifecycle - from the moment a ticket is created to the moment code reaches production.
The goal: reduce the manual coordination, context switching, and repetitive judgment calls that slow delivery. Keep humans in control of decisions that matter, and automate everything in between.
The bottleneck
Most teams already have good coding tools. The slowdown happens before, around, and after coding.
| Without Port | With Port |
|---|---|
| ❌ Ticket arrives: "Fix login bug" - no service, no owner, no scope | ✅ Work item arrives enriched: service, owner, blast radius, and context already assembled. |
| ❌ Engineer spends time finding ownership, dependencies, and recent incidents | ✅ Ownership, dependencies, and incidents pulled from the catalog automatically - no manual research. |
| ❌ Routing decision made informally ("feels like a small change") | ✅ Scorecard evaluates blast radius, service tier, and priority deterministically |
| ❌ Code review starts with no context about what the service does or who owns it | ✅ PR enriched with catalog context, risk signals, and ownership before review opens |
| ❌ Deployment happens manually, blast radius assessed after the fact | ✅ Deployment gates enforce readiness, staged rollout runs automatically |
| ❌ Nobody knows how many tickets AI handled or where work stalled | ✅ ROI dashboard tracks agent vs human split, stage breakdowns, and trends |
Lifecycle phases
ATR is organized around the stages of software delivery. Each phase builds on the same foundation: Port's software catalog as the context layer, scorecards as the governance layer, and workflows as the execution layer.
| Phase | What it covers | Status |
|---|---|---|
| Turn tickets into actionable work | Enrich a thin ticket with catalog context, generate PRD and tech spec, evaluate AI-readiness, route to agent or human. | Available |
| Code review | Automated PR analysis, risk signals, context from the catalog surfaced at review time. | Available |
| Safe release | Blast radius assessment, deployment gates, staged rollout with automated health checks. | Available |
How Port makes it work
Every ATR phase runs on the same platform primitives:
- Context lake - Your software catalog connects tickets to services, teams, repositories, and ownership. Agents and workflows query it instead of calling five separate APIs.
- Scorecards - Platform-defined rules gate every transition. Routing, review approval, deployment readiness - all deterministic and auditable.
- Workflows - Orchestrate agents, humans, and tools across each phase. The same workflow infrastructure handles prep today and safe release tomorrow.
Next steps
- Why Port? - What Port adds vs building this yourself.
- Work item blueprint pattern - The entity model that underpins all ATR phases.
- ROI dashboard - Measuring outcomes across all phases.
- Turn tickets into actionable work - Enrich, triage, and route tickets using catalog context and scorecards.
- Code review - PR enrichment, smart reviewer assignment, and security review tracking.
- Safe release - Blast radius assessment, deployment gates, and staged promotion workflows.
Start building
Ticket preparation
- Implement the work item blueprint pattern - the foundation for all ATR phases: blueprint, scorecards, and self-service actions.
- AI-powered work item preparation - enrich work items with AI context, ownership suggestions, and scorecard readiness signals.
- Improve specifications with Port AI - triage incoming tickets, fill in missing context, and ensure only well-defined tasks reach coding agents.
- Automatically resolve tickets with coding agents - full delegation from Jira ticket to Claude Code or GitHub Copilot.
Code review
- Set up the Pull Request Enricher AI agent - automatically comment on new PRs with AI-generated context and risk signals.
- Smart PR reviewer assignment using Port AI - assign the right reviewers based on code ownership and availability.
- Nudge PR reviewers - send automated Slack reminders to reviewers of stale PRs.
Safe release
- Calculate blast radius with AI - assess deployment risk and downstream service impact before promoting.
- Promote deployment to production - self-service action that promotes an image from staging to production.
- Promote to production workflow - staged promotion with automated gates and approval checkpoints.
ATR builds on your existing tools. Port integrates with Jira, Linear, GitHub, GitLab, Jenkins, ArgoCD, Slack, PagerDuty, and 50+ other platforms - no migration required.
Further reading
- How we delegate 40% of tickets to AI in our agentic SDLC - A practical walkthrough of redesigning your SDLC to delegate tickets to AI agents from planning through production, including context setup, guardrails, and visibility patterns.