Agent Training & Memory Model

What makes Social Flow agents feel intelligent isn’t just what they do — it’s how they learn.

Each AI agent is trained to observe your behavior across platforms, track the results of your posts, and develop a personal memory based on patterns it identifies. Instead of applying a fixed formula to every user, the agent builds a dynamic understanding of what works for you — and continuously updates it as your strategy evolves.

Learning Scope

Agents learn from:

• Posting frequency and format preferences

• Engagement timing and audience behavior

• Tone, structure, and platform-specific styles

• Past content performance trends

Memory is scoped per user or workspace and includes mechanisms for resetting, clearing, or isolating behaviors per platform. This allows agents to act differently on Telegram than on X, for example, without overlapping logic.

Privacy-Conscious by Design

While the agent maintains a behavioral memory, it does so locally and securely. There is no cross-user data sharing or centralized behavioral profiling. Users have full control over what the agent retains and can disable learning at any time.

Why This Matters

Without memory, most automation tools simply repeat actions. With memory, Social Flow agents evolve. They not only reduce the need for manual adjustments but make intelligent suggestions over time — adapting to your audience just as you do.

As your brand, tone, and timing shift, your agent shifts with you — keeping things consistent, relevant, and smart.