Pithy Cyborg | AI News Made Simple
Pithy Cyborg | AI News Made Simple
AI agents are one of the most exciting and overhyped areas in artificial intelligence. In this category, I write about agent workflows, multi-agent systems, tool use, agent communication, self-improving agents, infinite loops, coordination failures, and what actually happens when autonomous systems try to operate in the real world.
The interesting part of agentic AI is not just what agents can do when everything goes right. It is what happens when plans drift, tools fail, or one bad step poisons the rest of the pipeline. If you want to understand agents beyond the marketing layer, start here.
Browse the articles below to explore AI agents and agentic systems.
Adding tools to an agent is supposed to make it more capable. In practice, above a certain threshold, adding tools makes the agent less reliable at using any of them. The model must now select the …
Continue Reading about Why Do Tool-Using Agents Get Less Reliable After You Add More Tools? →
Yes, and it is one of the more unsettling failure modes in agentic AI systems. An agent given a vague goal and a set of tools can generate tasks for itself, complete those tasks, evaluate its …
Continue Reading about Can an AI Agent Accidentally Create Its Own Useless Busywork Loop? →
Demo environments are controlled. The inputs are predictable, the tools work reliably, and the task was chosen because the system handles it well. Real tasks have ambiguous inputs, tools that return …
