WorkerKitJoin the waitlistAI workers for Growth
AI workers for growth review campaign evidence, compare performance and watch funnel changes. Keep objectives, comparable measures and data limits together so the next experiment follows from evidence your team can inspect.
- Competitor Ad Monitor Language model Reports each week which ads your competitors are running in Meta's public Ad Library: what is new, what they stopped running, and what message they are testing.
- Web Research Relevance Filter Decision model Finds and reads web pages on your research topic and returns relevant sources with typed judgments.
- Daily Funnel Drop Watch Language model Reads yesterday's funnel in Google Analytics every morning, compares each step with the week before, and says which step dropped past your threshold and where the drop came from.
- Campaign Measurement Review Language model Explains campaign performance changes with comparable metrics and explicit data limitations.
- Campaign Brief Evidence Review Language model Checks campaign objectives, target audience and success measures in the approved brief.
- Campaign Learning Workflow Language model Combines campaign results and the campaign brief into a testable learning plan.
What is a Growth AI worker?
A growth AI worker is an AI worker assigned a specific research or measurement job for a growth team. It can review a campaign brief, compare campaign results, or report a drop between defined funnel steps. It works with the sources selected by its kit, such as an approved brief, public ad evidence or Google Analytics, and separates measured results from proposed next experiments.
What these workers do
Review a campaign brief's evidence
Check whether objectives, audience and success measures support the proposed campaign, and identify assumptions needing evidence.
Compare campaign performance
Explain measured changes using comparable periods and metrics, with data limitations stated beside the conclusion.
Watch a Google Analytics funnel
Review a defined sequence of funnel steps, compare the selected period, and report a drop with the source property and coverage.
How a Growth AI worker runs
Define the comparison
Choose the evidence source
Review the next experiment
Growth questions, answered.
Can a growth AI worker launch ads or spend money?
A measurement or research kit does not gain campaign writes merely by reading performance. The selected kit must explicitly grant any launch or change tools. Check those permissions before installation and keep spending decisions in the vendor's own approval and budget controls.
Can the worker see a competitor's ad results?
Public ad evidence shows the material a source makes visible, not private spend, conversions or return on investment. A useful review preserves the ad reference and observed changes, then labels any explanation of the competitor's strategy as an inference rather than a measured result.
How should a growth worker compare funnel results?
It should use the same step definitions, measures and comparable time windows, and identify the connected property. Missing records or a changed metric definition belong in the report. A drop is a measured observation; its cause and the proposed next experiment need separate evidence.