Self-Correction & Reflection Agents
Learn how to build agents that can critically evaluate their own outputs and iteratively refine their responses or actions.
Agents That Think Twice
Ever wished your AI agent could check its own work? That's exactly what self-correction and reflection agents do!
These agents are designed to not just generate an output, but also to critically evaluate it and make improvements. Think of it as an agent having an internal "editor" or "critic".
The Reflective Cycle
The core idea of reflection is an iterative process:
- Generate: The agent produces an initial response or action.
- Reflect: It then uses another prompt (or a different LLM) to analyze its own output against specific criteria.
- Refine: Based on the reflection, the agent adjusts its original output, aiming for better quality or accuracy.
This cycle can repeat multiple times until a satisfactory result is achieved.