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Sotis is a Python library that detects and intervenes in agent meltdowns (loops, edit storms) within LangGraph/ReAct loops using entropy and loop detection, rolling back workspace and restarting the agent to recover cleanly.
A practitioner shares lessons from running 30 AI agents in production for 6 months, arguing that framework choice is less critical than a robust memory and observability layer to prevent loops, state loss, and cost spikes.
An experienced practitioner shares hard-won lessons from deploying 25+ AI agents to production, arguing that memory, orchestration, and auditability matter far more than model choice. The article details common failure modes like context loss and silent cost loops, and recommends a stack including Claude Sonnet 4, Pydantic AI, and dedicated memory layers like Octopodas.
OpenClaw is seeking early users to test their open-source model inference plans, sold by concurrency slot with high throughput and no shared pool, in exchange for free access and feedback.
The author argues that coding agents like Cursor and Claude Code aren't getting dumber but suffer from structurally blind agent loops that bloat context windows with redundant file reads and tool outputs, degrading reasoning and causing architectural damage. They call for open-source agents that parse code into ASTs or graph databases for efficient understanding.
This article presents a method for building self-repairing agent loops using OpenAI's Codex, where agents review, repair, and validate outputs iteratively, with a worked example of fixing stale API documentation.
This paper proposes an epistemic state graph representation and an order-gap termination criterion for recursive reasoning systems, addressing how to manage evolving reasoning states and when to stop iteration.