A new article is out.
This time I wanted to explore a problem that keeps showing up in long-running AI agents: larger context windows help systems run longer, but they do not automatically make reasoning more stable.
A lot of modern agent instability seems to come not only from memory limits, but from growing amounts of competing reasoning state accumulating during execution itself.
The article looks at this problem from a systems perspective and discusses why patterns like orchestration, subagents, retrieval, and external state management increasingly appear in practical AI architectures.
https://grabduck.substack.com/p/hidden-cost-of-smarter-ai-agents