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Software & DevOps

Build a team of Devin agents to triage and reproduce customer bugs

Ripple Treasury (Ripple's treasury management platform) used Devin playbooks to build a triage system called Guardians 2.0: four agents modeled on engineering roles investigate every customer-reported bug and deliver a technical analysis, steps to reproduce and a development plan. A fifth agent reproduces and fixes the bug in a real Windows environment.

How it works

  1. Map the steps of your real bug refinement process and who does each one.

  2. Create a Devin playbook for each role: an orchestrator that enforces your Definition of Ready, an investigating engineer, a tech lead who challenges weak conclusions and a QA engineer who hunts for edge cases.

  3. For every customer bug, require three artifacts: a technical analysis with the root cause, steps to reproduce and a development plan.

  4. Have the team review those artifacts before the ticket moves on, instead of investigating from scratch.

  5. Set up an environment with your stack once (Windows, in this case) and an agent that reproduces the bug, fixes it, tests it in the running app and attaches before-and-after videos to the PR.

  6. Open Devin to support and implementation teams so they can answer technical questions about the code without going through an engineer.

Prompt

Replace anything in [brackets] with your own details.

prompt.txt
You are the investigating engineer on our triage team. Read the customer ticket, analyze the code of the affected module and find a failure scenario you can reproduce. Deliver: 1) the root cause with evidence (files, lines, logs), 2) the steps to reproduce and 3) a development plan with the tests it needs. If the evidence isn't enough, say what's missing instead of guessing.

Reported result

The untriaged bug backlog fell 75%, the team went from 0.5 to 1.5 bugs fixed per day and dropped two weekly triage meetings. Across 4,600+ technical questions, the company estimates 2,300 engineering hours saved (figures from Cognition).

As reported by the source. Results depend on your setup and your data.