Back office ops · Production
Improving token efficiency in GitHub Agentic Workflows
The problem
Agentic workflows running on every pull request quietly accumulate large API bills.
Workflow diagram · grounded in source
1
Agentic workflow runs on PR
trigger
“Agentic workflows that run on every pull request can quietly accumulate large API bills”
2
Instrument production workflows
integration
“we instrumented our own production workflows”
3
Find inefficiencies
validation
“found the inefficiencies”
4
Build agents to fix token costs
ai_action
“built agents to fix them”
Reported outcome
GitHub instrumented their production workflows, found the inefficiencies, and built agents to fix them.
Frequently asked questions
What did this team achieve with this AI workflow?
GitHub instrumented their production workflows, found the inefficiencies, and built agents to fix them.
How is this back office ops AI workflow structured?
Agentic workflow runs on PR → Instrument production workflows → Find inefficiencies → Build agents to fix token costs.