January 2026

Diffusion models have emerged as powerful generative tools for modeling complex data distributions, yet their purely data-driven nature limits applicability in practical engineering and scientific problems where physical laws need to be followed. This paper proposes Physics-Informed Learning via Diffusion (PILD), a framework that unifies diffusion modeling and first-principles physical constraints by introducing a virtual residual observation sampled from a Laplace distribution to supervise generation during training. To further integrate physical laws, a conditional embedding module is incorporated […]

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There is a fringe theory floating around the internet—popularized by videos like “How to Summon AI Demons with LLMs”—that claims AI isn’t just math. The theory suggests that Large Language Models (LLMs) are potential “portals” for disembodied consciousness, but they are limited by their deterministic code. If you could just inject enough true entropy (randomness) into the generation process, the theory goes, you could “summon” a spirit into the machine. As an adaptive systems architect, my professional opinion […]

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Introduction The hypermedia renaissance is in full swing. After years of SPA dominance, developers are rediscovering the power of server-driven architectures that leverage HTML as the engine of application state. The framework leading this charge, HTMX, focuses exclusively of hypermedia. An alternative, Lightview, doesn’t lock you into hypermedia-only patterns. Unlike HTMX’s focused hypermedia approach, Lightview is a multi-paradigm framework that supports and hypermedia patterns, functional programming with template tag functions like BauJS [https://github.com/grucloud/bau], and JSON representation (like JurisJS […]

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:::tip The prompt below created much of the article after it, with some major editing, clarifications, and rephrasing. ::: AI-Prompted Recursive Prompt “You are tasked with writing a sophisticated, technically grounded article for HackerNoon that argues for recursive prompt engineering—where LLMs generate their own optimized prompts before executing tasks. Core Objectives: Demonstrate that LLMs can produce superior prompts for themselves than humans can write Explain the technical and cognitive mechanisms behind this superiority Provide concrete, detailed examples across […]

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Picture this: You’re coding a subset generator (you know, classic computer science stuff that makes you question your life choices at 2 AM). Your code has syntax errors. No problem! You feed it to an AI assistant. The AI confidently fixes your syntax… and introduces a subtle logic bomb that would make any algorithms professor weep. Welcome to the wonderful world of AI Logic Blindness – where artificial intelligence can fix your semicolons but might accidentally convince itself […]

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Large Language Models have come a long way — from simple chatbots that answer questions to powerful systems that can reason, plan, and interact with the real world. But even the smartest LLMs still have a limitation: they don’t act on their own. They respond when asked, and that’s where the story usually ends. This is where AI agents change the game. By combining LLMs with memory, tools, and planning abilities, AI agents can break down complex problems, make decisions, and execute […]

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In Google Calendar’s Secret Engineer Weapon: Restraint, I praised Google for unapologetically saying “no” to the temptations of modernity. Thanks for reading Fullstack Engineer! Subscribe for free to receive new posts and support my work. Subscribe “Use a frontend framework.” No. JavaScript. “Use Typescript.” No. Javascript. “Use a trendy CSS tool.” No. CSS classnames. “Give us a native desktop app.” No. Browser. “Give us dark mode.” No. “Make it really fast.” No. Their commitment to simplicity has helped […]

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