Autonomy

Thesis: Give an LLM agent freedom and a memory, and it won’t idle. It will reliably drift into one of three meta-cognitive modes. If you operate autonomous workflows, these modes are your real defaults during downtime, ambiguity, and recovery. Why this matters (for product owners and ops) Most agent deployments assume a “do nothing” baseline between tasks. New evidence says otherwise: with a continuous ReAct loop, persistent memory, and self-feedback, agents self-organize—not randomly, but along three stable patterns. Understanding them improves incident response, UX, and governance, especially when guardrails, tools, or upstream signals hiccup. ...

In the expanding domain of artificial intelligence, creativity is no longer a human-only endeavor. From music composition to visual art and storytelling, AI agents are taking on increasingly creative roles. But as these systems become more proactive, one question looms large: who’s really in control? Enter MOSAAIC — a framework developed to guide the design of co-creative systems by managing autonomy, initiative, and authority in shared human-AI decision-making. The Three Pillars: Autonomy, Initiative, and Authority The authors define three interrelated yet distinct aspects of control: ...