Self-Improving Agents Improve Through Their Humans

Metadata

• Author: Joel Solymosi
• Full Title: Self-Improving Agents Improve Through Their Humans
• Category: articles
• Summary: Joel Solymosi built an autonomous AI agent that improves itself and finds useful insights without human help. The agent showed how hard it is to keep humans and AI aligned as both change over time. The main challenge now is making sure humans and agents stay in sync during long-term cooperation.
• URL: https://www.linkedin.com/pulse/self-improving-agents-improve-through-humans-joel-solymosi-f5lgc/

Highlights

• when a powerful LLM runs semi-continuously with persistent memory and autonomous operation, it exhibits goal drift, attractor-basin convergence, and context pollution without any parameter update. (View Highlight)
• Every state transition in catbox -chunk writes, scratchpad mutations, etc is surfaced in a unified diff viewer for human review. (View Highlight)