Workflow · saas · workflow
Brex builds autonomous agents for technical tasks by closing CI and review-bot feedback loops
AI coding agents stalled on real production work because they could not read CI output, review-bot comments, or test-runner stack traces — so engineers had to manually relay that automated feedback back to the agents each afternoon.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Task received via Slack or scheduler
Tasks come in from Slack, Linear, GitHub, or a cron job.
Tools used
SlackLinearGitHubPython
Outcome
Closing the feedback loop with three Python scripts let migrations run from task submission to green PR without engineer intervention — no afternoon check-ins, no manual log copying.
What failed first
Standard isolated-environment agents failed on complex services with multiple client factories; the workaround of putting a human in the loop to relay CI and bot output was expensive and did not scale.
Results
Time savedMinimal engineer-hours spent relaying CI output
Volumeabout 30 minutes each
Grounding & classification
Source type: technical build writeup
24 fields verified against source quotes.
agentic workflowcode generationmulti agent workflowcode diff prbuilder submittedfailure mode describedhuman review describednamed customerproduction runtime claimedtools describedworkflow describedsoftwareautomation rateemployee productivitytime savedtechnical build writeupagentic task execution