Architecting Intelligence: A Comprehensive Guide to LLM Agent Patterns and Behaviors
48 mins
Large Language Models are transforming the way we interact with information—but their real potential is unleashed when they're embedded in agents that can reason, plan, and adapt. This guide explores the emerging architecture patterns behind modern LLM-based systems: from stepwise planning and research workflows to memory-aware decision-making, simulations, and autonomous behaviors. Whether you're building intelligent assistants, automated researchers, or multi-agent systems, this collection distills the key concepts, tools, and interaction models that make LLM agents truly capable. Through detailed explanations, structured pattern summaries, and illustrated diagrams, you'll learn how to compose powerful, reliable, and adaptive agent systems that go far beyond simple prompting.
Running JupyterLab Behind an Apache Reverse Proxy
2 mins
Want to access your internal JupyterLab instance securely over HTTPS? This quick guide shows how to set up Apache 2.4 as a reverse proxy for JupyterLab 4.2.5, with working websocket support and proper configuration on both ends. Learn how to avoid common pitfalls like broken kernels or missing output—and get your lab running smoothly behind your own public facing reverse proxy
Python Logging: A Beginner-Friendly Tutorial and Practical Reference
20 mins
Whether you're debugging a simple script or building a scalable application, this article walks you through the fundamentals of logging, the use of named and hierarchical loggers, configuration via dictConfig, and advanced handlers like HTTP, syslog, and rotating files. Learn how to go beyond print() and implement a long-term, structured, and maintainable instrumentation layer for your software — one that helps today and scales for tomorrow.
Social Media Algorithms and Harmful Content: Societies mirror vs. Intent
24 mins
Is social media really fueling hate on purpose? Contrary to popular belief, there’s no solid evidence of deliberate harmful intent. Instead, algorithms amplify whatever sparks the most engagement—often divisive or emotional posts—simply because we, as users, pay more attention to them. This dynamic functions more like a mirror of society’s existing biases than a direct manipulation scheme. The real tension emerges when the rush for clicks collides with long-term user well-being, revealing that negativity thrives largely through our own online behaviors rather than calculated corporate strategy.
Goth Subculture Visibility and Economic Crises: Comprehensive Analysis
28 mins
Could the goth subculture's prominence serve as a hidden barometer of economic crisis? Throughout recent history, waves of goth style, music, and aesthetics have seemingly risen alongside financial downturns. This comprehensive analysis dives deep into academic insights, media narratives, anecdotal histories, and comparisons with other subcultures, examining whether goth truly reflects societal anxieties during tough economic times—or if it's merely coincidental. Explore the intriguing relationship between dark fashion and economic gloom, as we uncover whether the goth aesthetic is more than just a style choice, but possibly a cultural reflection of deeper societal undercurrents.
How I Use Large Language Models (LLMs) in My Daily Work and Hobbies
14 mins
In this article, I explore the various ways I integrate large language models (LLMs) like ChatGPT and LLAMA into my daily work and personal projects. From summarizing scientific papers and refining research communication to enhancing creativity through AI-generated artwork and automating everyday tasks, LLMs have become invaluable tools in my workflow. I also discuss how AI can assist in coding, structuring complex ideas, and even helping friends navigate social and emotional challenges. Whether you're a researcher, a maker, or simply curious about AI's capabilities, this article offers insights into practical, real-world applications of LLMs.
Running Ollama on a CPU-Only Headless FreeBSD 14 System
4 mins
This mini guide walks through compiling and running Ollama on a headless, CPU-only FreeBSD 14.2 system with an Intel Alder Lake-N97 processor. It covers why one might opt for CPU-based inference, the Vulkan-related issue preventing execution without a GUI, and how to disable Vulkan by recompiling from ports. The article provides step-by-step instructions for extracting, modifying, compiling, and installing Ollama, along with details on running inference and transferring models to air-gapped systems.
Do LLMs Feel? Exploring the Boundary Between AI Simulations and True Emotion
6 mins
Large Language Models (LLMs) exhibit behavior that appears empathetic, leading to discussions about whether they genuinely feel emotions or merely simulate them. This article explores how LLMs generate emotionally resonant responses, relying on statistical pattern recognition rather than subjective experience. It presents arguments from functionalism and behaviorism that suggest LLMs may be functionally equivalent to emotional beings, while critics highlight the lack of neurochemical processes and self-initiated emotional states. The discussion also raises philosophical questions about human cognition, given that psychology often models human emotions statistically. As AI progresses, distinguishing between true emotional experience and advanced simulation will remain a key debate in both science and ethics.
FDM Printed PLA in Cryogenic Environments
6 mins
Can 3D-printed PLA handle extreme cryogenic conditions? In this article, I explore how FDM-printed PLA performs when exposed to liquid nitrogen at 77K (-196°C). I tested two different crucible designs, with (not so) surprising results—one even allowed safe handling with bare hands! Learn about the experimental setup, design insights, and what this might mean for using PLA in unconventional cryogenic applications.
Deepfakes: The Unstoppable Technological Shift and Its Societal Implications
13 mins
Deepfake technology is no longer a futuristic threat—it is an unstoppable reality that is reshaping the way we perceive media, trust information, and engage with digital content. From hyper-realistic videos to AI-generated images that even experts struggle to distinguish from real ones, these tools are now widely accessible to anyone with a consumer-grade computer. Governments attempt to regulate and control the spread of such technologies, but like encryption before it, deepfakes cannot be banned or contained. Instead of resisting the inevitable, society must adapt by enhancing critical thinking, questioning sources, and moving beyond blind trust in media appearances. The implications of deepfakes reach far beyond political manipulation and misinformation; they have the potential to impact personal lives through blackmail, fabricated scandals, and AI-generated smear campaigns. Society must not only acknowledge these risks but also actively counteract their effectiveness by changing how we evaluate and react to digital content. Education in media literacy, the rejection of personality cults, and a stronger emphasis on factual verification over emotional reactions will be essential in mitigating the disruptive influence of deepfake technology. The future will not be about stopping deepfakes—it will be about learning how to navigate a world where seeing is no longer believing.
