Guest Application Flywheel
Two agents that screen incoming podcast guest applications, draft personal declines for weak fits, and send leadership a monthly view of the pipeline.
For a businessCuts hours of manual screening so strong podcast guests aren't lost in the pile, while a person keeps the final say on every decision.
01 · ContextThe problem
Guest applications arrive through a form and were screened by hand. Strong fits got buried among weak ones, and every decline deserved a personal reply that took time to write.
02 · PipelineHow it works
- New application
The screening agent starts the moment a form is submitted.
- Research the applicant
It looks the applicant up online for context the form doesn't give.
- Score against the rubric
Five criteria, scored out of 15, plus the agent's own judgment.
- Write the record
The result is written to a Google Sheet that both agents share.
- Recommend
Leadership gets a pass, consider or fail recommendation within moments of submission, and can overrule any score.
- Monthly digest
A second agent reads the sheet each month and summarizes the pipeline for leadership.
03 · ChoicesDesign decisions
Safety by limiting tools
Each agent holds only the actions its job needs, and nothing more.
Applications are data
Application text is treated as untrusted input, with defenses against instructions hidden inside it.
No half-written rows
Writes happen in a fixed order so the sheet never shows a partly processed application.
People keep the final say
Any score can be overruled, and decline emails are drafted, not sent automatically.
04 · EvidenceHow I tested it
Shipped with a written build sheet and test plan, and a step budget per run.
Want to see this one run?
I'll screenshare the workflow, the test set and the results, including what didn't work.