I agree with one core idea:AI is irreversible. We can’t go back. But where I disagree is the assumption that creativity must remain a protected, human-only zone, while AI should stop at being a “support tool.” That framing belongs to an older workflow. Today, creativity is no longer defined by who writes the first sentence or who sketches the first draft. Creativity lives in how systems are designed, how intent is translated, and how decisions are made across an ecosystem of tools. Using AI at an advanced level — RAG, automation, orchestration, feedback loops — is not intellectual laziness. It is system thinking. The real danger isn’t “letting AI create.”The danger is confusing raw output with authorship. When someone blindly copies AI-generated content, that’s not working smart — that’s poor execution and weak judgment. But that’s not an argument against AI-driven creativity. It’s an argument against bad operators. A film director doesn’t personally draw every frame.A composer doesn’t build every instrument.Yet we never say the work lacks a soul — because the soul comes from intent, taste, and constraint, not manual labor. AI is no different. When creativity is guided by: - clear vision - ethical data boundaries - strong human taste - deliberate system design …the result is still deeply human. The future isn’t human vs AI. It’s humans who understand systems vs humans who don’t. Creativity was never about doing everything yourself. It was always about knowing what to say, what to choose, and what to reject. AI doesn’t remove the soul.Poor thinking does. And in this era, building intelligent systems is a creative act.

Construction Industry Professionals Often Misunderstand AI Agents I recently came across a post on my newsfeed introducing some AI tools for office documentation work targeting construction professionals. What caught my attention was the author's use of the term "AI Agent" to describe these AI tools. As someone who directly researches and applies AI in general and ChatGPT in particular in my work, I find this extremely problematic, as it will have serious consequences for foundational thinking during this early stage of AI development. The Fundamental Misunderstanding The tools the author mentioned are essentially Custom GPTs - a feature of ChatGPT. Simply put, these are ChatGPT instances enhanced with user-provided knowledge so that the AI (more precisely, LLMs - Large Language Models) can find and retrieve information more accurately according to requirements. So how do Custom GPTs differ from an AI Agent? According to the definition (from ChatGPT), an Agent must both receive information and take actions based on the process of receiving and processing that information. While Custom GPTs do take actions (producing results), when most other AI platforms also have the action of producing text-based results, why do people need to "force" additional terminology unnecessarily? The Growing Divide: Beginners vs. Professionals From here, we begin to see differentiation in AI usage between beginners and professionals: Beginners: - Input simple commands - Receive crude results - Follow "Ctrl C + Ctrl V" repetitive workflows - Work with isolated, disconnected AI types Professionals: - Use true AI Agent systems where AI directly intervenes - AI "thinks through" implementation approaches on their behalf - AI directly executes multiple simultaneous tasks within permitted workspace and resources - No need for specific guidance - goal is final results and products - Eliminates intermediate steps Real AI Agent Example Scenario: You receive a notification that it's your business partner's birthday today. You're lying on My Khe Beach in Da Nang and don't want to open your laptop to write and send an email. So you command your AI Agent through your phone's chat box to investigate information about partner A, write a personalized birthday email, and send it, then put your phone down and continue sunbathing.

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