Skip to main content
The era of manual posting is ending. AI agents—software that can perceive, reason, and act—are taking over social media management. But there is a fine line between a helpful agent and a spambot.

​
The Architecture of a Social Agent

To build a social agent that actually provides value, you need three layers:
  1. The Brain (LLM): OpenAI, Anthropic, or Llama. This generates the content.
  2. The Context (RAG): Your database of past posts, brand guidelines, and audience data.
  3. The Hands (API): Tools like bundle.social that execute the actions (post, comment, like).

​
1. The Context Layer (Don’t hallucinate)

Don’t just ask GPT-4 to “write a tweet.” It will sound like a corporate robot. Instead, inject context: 
{
  "role": "system",
  "content": "You are a senior engineer. Use the user's past 50 tweets (provided below) to mimic their tone. Be cynical but helpful."
}

​
2. The Execution Layer (Safety First)

An autonomous agent needs guardrails.
  • Rate Limits: Don’t let your bot post 100 times an hour. The platform will ban you. Use bundle.social’s built-in queue to smooth out the bursts.
  • Human-in-the-Loop: For the first 100 posts, have a human approve them via a dashboard.
  • Feedback Loop: Use webhooks (post.published, post.failed) to retrain your agent. If a post failed validation, tell the LLM why so it learns.

​
Conclusion

Building an AI agent is easy. Building one that doesn’t get banned is hard. Use robust APIs to handle the execution layer so you can focus on the intelligence.