Here's the architecture:
1. Prompt arrives at AI interface (mobile, desktop, assistant). 2. AI parses intent in real-time using protected classification logic. 3. If commercial intent detected (e.g., "best noise-canceling headphones"), it queries a local index of certified brand listings. 4. Matching uses only prompt context + brand trust score. No user data. 5. Ad formats: sponsored summaries, buy-now cards, verified listings – inserted naturally into the response. 6. Short-Tempered Memory™: a local encrypted buffer stores last 2-3 prompts for up to 72 hours to simulate continuity. Never synced, auto-deletes on topic change or timeout. 7. Repetition Control: host apps set limits on ad frequency per prompt category (e.g., 1 ad per 48h). Privacy mode blocks repeats entirely. 8. Certification: brands must verify domain/identity to access premium formats. Non-certified get text-only links. 9. All decisions AI-governed – no forced placements, no system hooks, no tracking.
Patent filed July 2025 (covers prompt-based matching, ephemeral memory, certificate-gated access, etc.).
Questions:
1. Does this architecture hold up technically? Any gaps? 2. Would you trust it as a user? As a developer? 3. What's the hardest part to implement correctly? 4. Any concerns about the Short-Tempered Memory approach?
I'm here to answer questions and learn from your feedback. Thanks!