Product Ops Automation
An agentic pipeline that eliminates manual triage — AI classifies, routes, and acts in under 3 seconds
Problem
Ops teams in large product organisations spend significant time each month manually reading and classifying incoming tickets — work that's repetitive, error-prone at scale, and grows linearly with volume. Could a PM, without raising a single engineering ticket, build and own an AI system that does this automatically?
What I Learned
Building an agentic pipeline taught me that orchestration is a product discipline, not an engineering one. n8n makes the workflow visible and ownable — any ops lead can modify routing logic or adjust prompts without filing a ticket. The harder insight was Jira's boundary behaviour: webhooks fire on every field change, so filter logic and event schema design matter as much as the AI step. Gemini Flash classifies; n8n executes; Jira acts. The PM's job was knowing exactly where each begins and ends.
Stack
Deep Dive
Key product decisions
Why n8n over a custom API?
No engineering dependency. The ops lead can update routing rules, fix prompts, and monitor the workflow without raising a ticket. The whole system can be iterated in an afternoon — which matters when routing accuracy improves incrementally through real-world testing.
Why a confidence threshold, not full automation?
Below a certain confidence level, the cost of a misroute (downstream SLA breach + ops time to fix) exceeds the cost of a human review. The threshold creates an explicit safety net: low-confidence tickets escalate to a human, high-confidence ones route automatically.
Why three routing paths instead of two?
Some tickets belong to a completely different team in a different system — not just a different queue. These need a distinct action (clone + close) rather than a simple assignment. Collapsing them into one path makes the accuracy metrics look good while the actual problem continues in the receiving teams.
Why AI classification over rule-based logic?
The domain boundary rules are too nuanced for deterministic if/else trees. Bug tickets describe symptoms in natural language and the correct owner depends on context — the same screen can have frontend or backend causes. Gemini Flash with structured org context handles this better than any decision tree the team could maintain.