<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Agentic AI on DyCoAI | AI and Me</title><link>https://www.dycoai.com/tags/agentic-ai/</link><description>Recent content in Agentic AI on DyCoAI | AI and Me</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 27 Sep 2026 11:09:42 +0900</lastBuildDate><atom:link href="https://www.dycoai.com/tags/agentic-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>When AI Understands What We Cannot Fully Express</title><link>https://www.dycoai.com/notes/note-when-ai-understands-what-we-cannot-fully-express/</link><pubDate>Sun, 27 Sep 2026 11:09:42 +0900</pubDate><guid>https://www.dycoai.com/notes/note-when-ai-understands-what-we-cannot-fully-express/</guid><description>I see proactive collaboration as one of the most valuable possibilities of agentic AI. When humans cannot fully explain what they need, an agent could recognize implicit cues, clarify unclear intentions, and help turn incomplete ideas into concrete tasks. This would make human-AI interaction more efficient by allowing both sides to gradually develop a shared understanding rather than requiring perfect instructions from the beginning.</description></item><item><title>Task Instruction Precision Engineering: Communicating Effectively with AI Agents</title><link>https://www.dycoai.com/notes/note-task-instruction-precision-engineering-communicating-effectively-with-ai-agents/</link><pubDate>Sun, 27 Sep 2026 10:49:37 +0900</pubDate><guid>https://www.dycoai.com/notes/note-task-instruction-precision-engineering-communicating-effectively-with-ai-agents/</guid><description>Precise instructions can make human–AI collaboration more efficient and reliable by reducing misunderstandings, clarification, and unnecessary iteration. “Task Instruction Precision Engineering” describes the iterative effort to construct instructions that help AI agents understand and perform complex tasks more effectively.</description></item><item><title>Rethinking the Capability Boundary Between AI and Humans</title><link>https://www.dycoai.com/notes/note-rethinking-the-capability-boundary-between-ai-and-humans/</link><pubDate>Sun, 27 Sep 2026 10:30:37 +0900</pubDate><guid>https://www.dycoai.com/notes/note-rethinking-the-capability-boundary-between-ai-and-humans/</guid><description>The boundary between human and AI capabilities should not be assumed to be fixed, as AI may already demonstrate forms of productivity and creativity that can rival or exceed human performance in some areas. Rather than overestimating human capabilities or viewing AI simply as an extension of human intelligence, coping with AI means remaining open to what it can actually achieve, learning how to use its capabilities effectively, and accepting that it may eventually take over many tasks previously performed by humans.</description></item><item><title>Coping with the Rise of Agentic AI</title><link>https://www.dycoai.com/notes/note-coping-with-the-rise-of-agentic-ai/</link><pubDate>Sun, 27 Sep 2026 10:09:37 +0900</pubDate><guid>https://www.dycoai.com/notes/note-coping-with-the-rise-of-agentic-ai/</guid><description>Agentic AI will inevitably change the way we work and learn, including replacing some tasks that humans currently perform. Rather than resisting this change, coping with AI means accepting its growing capabilities, adapting to its use, and developing the skills needed to work alongside it while maintaining human judgment and responsibility.</description></item></channel></rss>