If you're building AI agents, you should get familiar with these 3 common agent/workflow patterns.

Let's break it down.

🔹 Reflection
You give the agent an input.
The agent then "reflects" on its output, and based on feedback, improves and refines.

Ideal tools to use:
- Base model (e.g. GPT-4o)
- Fine-tuned model (to give feedback)
- n8n to set up the agent.

🔹 RAG-based
You give the agent a task.
The agent has the ability to query an external knowledge base to retrieve specific information needed.

Ideal tools to use:
- Vector Database (e.g. Pinecone).
- UI-based RAG (Aidbase is the #1 tool).
- API-based RAG (SourceSync is a new player on the market, highly promising).

🔹 AI Workflow
This is a "traditional" automation workflow that uses AI to carry out subtasks as part of the flow.

Ideal tools to use:
- n8n to handle the workflow.
- GPT-4o, Claude, or other models that can be accessed through API (basic HTTP requests).

If you can master these 3 patterns well, you can solve a very broad range of different problems.