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Author name: Alex Chen

Alex Chen is a senior software engineer with 8 years of experience building AI-powered applications. He has worked at startups and enterprise companies, shipping production systems using LangChain, OpenAI API, and various vector databases. He writes about practical AI development, tool comparisons, and lessons learned the hard way.

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minimalism

My AI Needs More Than Just “Smart

March 12, 2026

The Quiet Rebellion: Why Our Agents Need More Than Just ‘Smart’

I was staring at the blinking cursor, again. It was 3 AM, and the pitch for the new “hyper-personalized” AI content assistant was due in five hours. My current AI assistant, a glorified autocomplete with a cheerful tone, had just suggested I

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I Built My Own Agent With a Spreadsheet (And So Can You)

March 12, 2026

The Quiet Revolution: Why Your Next "Agent" Might Be a Spreadsheet (and That’s a Good Thing)

We talk a lot about agents here at agntzen.com. Usually, it’s about the big, flashy stuff: AI agents making decisions, robotic agents navigating warehouses, software agents automating complex workflows. And don’t get me wrong, that’s all incredibly

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My Agencys Future: Embracing Decentralized AI

March 12, 2026

The Quiet Revolution: What Decentralized AI Means for Our Agency

I remember the first time I felt truly helpless in front of a computer. It wasn’t a blue screen of death or a lost file. It was a few years ago, trying to get a refund from a major airline for a cancelled

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AI agent simple state management

Imagine you’re developing a chatbot that manages customer inquiries for an online store. It needs to track past interactions to provide meaningful responses, but it shouldn’t require a sophisticated database or overly complex logic to remember whether a customer is new or returning. Managing this simple state can be a common challenge, but minimalist solutions

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Practical

Navigating the Future: Practical Tips for AI Alignment Basics

The Imperative of AI Alignment: Beyond Sci-Fi to Practicality
The rapid advancement of Artificial Intelligence (AI) has moved discussions about its potential impact from the realm of science fiction into immediate practical considerations. As AI systems become more autonomous, powerful, and integrated into critical infrastructure, ensuring they operate in a manner beneficial to humanity –

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minimalism

Minimalist AI agent logging

Imagine you’re building an AI agent that needs to run independently on edge devices with limited computing power. You’re faced with the challenge of ensuring that this agent performs efficiently without the extra baggage of thorough logging. In such scenarios, minimalist logging becomes paramount—not just to reduce the computational load but also to simplify your

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