Show HN: RLM-based local debugger for AI agent traces

The HALO tool introduces a novel approach for debugging and optimizing AI agents using RLM-based analysis of production traces. Its ability to identify failure modes and suggest improvements in real-world deployments makes it a valuable asset for enhancing AI reliability and performance. This development signifies a step forward in self-improving AI systems, offering both industry and consumers more robust and efficient AI solutions.

• HALO uses RLMs to analyze AI agent traces for self-improvement.
• It automates the identification of failure modes in production environments.
• The tool supports recursive, self-improving agent optimization cycles.