i stopped judging these agents by what they do in a demo and started counting how many of my open loops they close
Summary
The author argues that the true measure of an AI agent's utility is how many open loops it closes autonomously, rather than demo performance or integration count, and cites Runner as a desktop tool that effectively closes such loops by pulling cross-app context.
Similar Articles
no-code agent tools nail the demo and miss the boring part
The article critiques no-code AI agent tools for their ability to create impressive demos while neglecting the essential, mundane aspects of real-world deployment and maintenance.
the agent demos look amazing because nobody films the 90% that's error handling
The author contrasts polished AI agent demos with the reality of production systems, noting that most agent code is for error handling and guardrails rather than the core intelligence.
Are AI agents finally crossing the line from demos to real tools?
Discussion on whether AI agents are transitioning from impressive demos to genuinely useful tools in research, coding, operations, and personal productivity.
AI agents are useful, but agent loops still make me nervous
The article discusses the usefulness of AI agents while expressing concerns about the potential risks of agent loops.
Are we actually any closer to reliable agents, or is it still mostly demos?
A community discussion questioning whether AI agents can reliably perform multi-step real-world tasks, or if most agent capabilities remain limited to impressive demos that break down in practical use.