Have AI agents implement tickets on their own
Development teams have AI agents implement entire tickets on their own
Fits: IT & software development
An agent takes clearly described tickets such as small bug fixes, tests or dependency updates all the way to a finished pull request. The team checks and decides instead of writing every little thing themselves.
Is this for you?
- Your backlog has lots of small, well-defined tickets.
- There are automated tests and a pipeline that checks every pull request.
- Every change is already reviewed by a second person today.
First step today
Take a small, invented ticket with a short function and have the template below write the plan, change and tests. Run the tests yourself and check whether the agent openly states its assumptions.
How to go about it
- Define suitable tickets and the path to merge
- Clarify repository, pipeline and permissions
- Set up the agent with project rules
- Have a person check every pull request
- Gradually hand over more demanding tickets
- Analyse rejected pull requests and bugs
Templates to copy
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The complete guide
- 6 steps explaining exactly what to do
- 3 proven templates to copy into your own AI
- Safe use: data, checking, deciding, informing
- Pitfalls, effort and how to recognise success
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Same approach, other use cases
13 more use cases follow the pattern “Automating processes with AI agents”.
Plan a content calendar and publish approved posts automaticallyCreate activity reports and invoices from recorded activitiesHandle air passenger rights cases largely automaticallyHave AI agents fix standard incidentsHave AI agents handle routine processesHave AI match incoming payments to open invoicesHave AI prepare tax returns from last year and receiptsHave AI schedule meetings with several participantsHave AI send payment reminders in the right toneHave AI suggest time entries from calendars and documentsHave intercompany balances reconciled automaticallyHave AI sort online enquiries and arrange test drives
G-DT-03 · Legal status 08.10.2026