Step 1 of 11
Define the affiliate agent scope and data model
Set the exact product scope, entities, relationships, and success metrics before building screens or AI features.
Keep version 1 narrow: one operator, manual affiliate offer entry, tracked clicks, recorded earnings, and AI content generation.
First time here? Paste the Context Pack first so the AI understands your project - open it from the header above.
Create the initial architecture for an AI affiliate marketing agent application. Include a concrete data model for affiliate programs, offers, campaigns, content assets, tracked links, click events, conversions, earnings entries, and compliance rules. Also define the main user flows: add an offer, create a campaign, generate content, use tracked links, record conversions or earnings, and view reporting. Generate the actual schema and wire it into the app foundation so later steps can build on real persisted data.
Quick is short. Full Build is recommended for most steps. Strict forces real logic when the AI keeps faking output.
Actual change check
Expected after this step
A working project scaffold with persistent data structures and clear app sections for offers, campaigns, content, link tracking, and analytics.
Should NOT happen
- An existing feature broke
- A button only logs to console
- Data disappears after refresh
- Errors fail silently with no visible state
This is what should exist before you continue. If reality does not match, do not move on.
Track what changed, failed, or needs follow-up. Notes export with the flow.