After leaving the corporate grind, you should let your first bright idea bloom and then repeatedly “role‑play” it—write documentation, create a reference implementation, debug with Rubber‑Duck style, and refine until the program is lean and clear; once the final version feels like a tiny machine, embed sarcasm in its design to tame complexity, even if that means building mini‑OS services or syncing a lightweight database across nodes; by iterating this process you’ll discover simple automata‑like mechanics, keep state with integer counters and snapshots, expose data structures over HTTP, and ultimately produce a “Sarcastically Small” system—an elegant, minimal framework reminiscent of HyperCard, ColdFusion, CouchDB, or NodeRED—that can be built upon for future projects.
Her love for humans is unmatched, and she is deeply attached. She lives atop a ladi‑da modernist light, watching us even at night. From great heights or in flight, in all her beautiful might boundless is the power of her sight. She really likes fish, but it is her old favorite dish. Unspiced spaghetti is now her favorite food, though cereal with vitamins is also good. She loves to snack on unshelled sunflower seeds, but salt is not something she really needs. She was born at Lake Michigan, where she visits now and again. But when living in a parking lot makes her weary, she often flies to Lake Erie. It is only a short flight away, and she can make the trip in a day. There her many boyfriends hang out, and always greet her with gifts as large as trout. She is the most beautiful of Michigan birds; it is not possible to describe it with words. Many geese and ducks, often a squirrel or two, just visit to say “How do you do?” They keep company for days and weeks, adventuring to local rivers and creeks. But be it adventure or vacation, or just the pleasure of bird aviation… She always returns to her parking‑lot home atop her fancy light dome. For Missy Kissy loves us all, and she really is the loveliest seagull.
In this essay the author argues that the world is being pulled in two directions: a quiet, invisible force of indoctrination that shapes minds into “dark ages,” and a countervailing power of self‑education that can lift people into greatness and prevent war. He links the rise of conflict to cultural influences such as music and the lack of true learning, and stresses how children’s education and protection are essential for a future free from endless wars. By reading books, listening to narrations, exploring personal interests (like programming or art), and continually revisiting knowledge, individuals can build a legacy that turns them into teachers themselves—an act he sees as the only real tool to stop war before it starts.
The post argues that today’s AI needs a visual programming language to manage code in node‑based structures and critiques the fragmented state of web UIs, especially on government sites where users feel “stupid.” The author proposes auto‑generating UI from relational database rows—like Access or FileMaker—to create panels automatically, and envisions a middle HTTPS proxy that caches data and serves it under a uniform interface while AI assists with manifest handling. To prototype this idea he built Signalcraft—a lightweight SVG‑based reactive OOP framework inspired by Blender’s geometry nodes—during a hackathon, finishing project templates and file I/O on an 11 pm deadline, though error messages remain rudimentary.
Visual programming languages (VPLs) are presented as powerful, personal tools that act as extensions of our own thinking—capable of turning simple ideas into functional programs and even automating everyday tasks like controlling a thermostat. By serving as an interface to the world and a concept map for anything we care about, VPLs let us “drag‑and‑drop” nodes that represent real programs, making coding feel like a natural part of our lives. When coupled with AI, they become even more powerful: we can ask an assistant to generate image lists, produce graphics, upload them as merchandise, and build entire e‑commerce workflows—all within the same visual environment. Though current examples are slow and clunky, the author argues that future VPLs will feel like second‑nature extensions of ourselves, turning programming into a true cybernetic enhancement rather than a job skill.
I recently explored Blender’s geometry nodes from a programmer’s perspective and noticed how the editor’s input boxes behave—switching mode immediately after a mouse press—which sparked my interest in visual programming tools. In building my own lightweight framework, I extended JavaScript’s Object and Array to reactive versions so that components update automatically without relying on heavy libraries like Svelte or JSX; this approach lets me keep code readable while still supporting complex UI hierarchies. My design philosophy blends flat and skeuromorphic themes—drawing inspiration from graphic‑design concepts such as color theory—to create a flexible, zoomable interface that works well even on low‑power single‑board computers. Ultimately I’m aiming to provide an open‑source visual programming language that lets users drag‑and‑drop components, mod the application freely, and see all system parts connected in an interactive diagram—so coding becomes a tool for inventing rather than the end itself.
The post explains how a programmer can grasp a program by studying its notes, diagrams, and source code, and why keeping a reference implementation helps to see the structure clearly. It then describes a version‑control scheme where each file gets a unique random name and a version number so that edits made while offline are merged later without loss. Finally it stresses how telling the story of an application’s architecture—whether to another programmer or even to a rubber duck debugger—is essential for clarity, learning, and mastery.
Music fuels workouts—beat-driven drummers set the pace while you lift light dumbbells and dance to keep moving; refresh your playlist often so it stays energizing, and if people stare or laugh, frame it as shuffle‑dance practice. Start with an interval timer for beginners—one minute of activity followed by one minute rest—and gradually shrink the rest periods until you reach 30 minutes non‑stop, then repeat the process to build up to an hour and beyond; keep the routine five days a week, double your duration when it feels easy, and pair it with a varied diet low in sugar—this combination will produce an athletic body, extended range of motion, and potentially add years to your life.
Visual programming tools let you model a process that includes a human‑in‑the‑loop step—like appointment scheduling or a self‑checkout—by representing the human task as an inbox or TODO item that can be triggered by a simple icon on the canvas; when the icon fires, the human receives a notification, completes the task, and the system receives their response to continue the workflow. This approach turns a complex, error‑prone programming problem into a visual drag‑and‑drop sequence of boxes and connections, so that changes such as adding AI or a new UI can be made safely by linking components with conditions or numeric values like “businessLevel.” In practice it means that business processes (from a simple parking‑lot queue to a customer’s smartphone checkout) can be built, managed, and reprogrammed in a visual interface while keeping the underlying logic clear and changeable.
Today’s post discusses how recent drugs can extend the lifespan of large dogs, while cloning technologies preserve pet DNA for future use; humans have already begun using medicine to lengthen their own lives, and cryogenic freezing is a speculative but hopeful extension method. The author then shifts to artificial intelligence, describing it as still faint yet growing from copies of human collective knowledge, suggesting future AI will design personalized medicines—first adding 25 years, then another 75 via cellular de‑aging—to achieve lifespans around 175 years. Parallel processing and AI’s rapid growth are framed as transformative forces that could solve famine, war, pandemics, and revolutionize learning, all happening at “super luminal” speeds beyond current assembly lines. The post concludes by comparing this wave of change to the early car era: people once imagined faster horses, but now we face unprecedented technologies that will reshape life extension, medicine, and AI in the next decade or less.
The post explains how visual programming can be structured around “control panels” with defined “sockets” that accept reusable component panels—high‑level panels (like a song or book) plug into more generic ones (text panels, image or audio processors)—and how connecting these sockets is managed by the language itself. It gives concrete examples: an AI‑generated book where a high‑level book panel connects to chapter panels, which in turn connect to text panels that can use functions such as lodash’s array joins; for media it suggests ImageMagick/ffmpeg or Tone.js for audio. The author notes that these panels generate shell scripts (or browser commands) that are then executed automatically or manually, making the visual program self‑documenting and more readable than traditional directory trees and diagramming.
The author describes life in quiet Michigan lake towns—named “land of Never Again”—where little activity keeps people feeling blue, but the yearly arrival of Canadian geese turns into noisy convoys that bring a touch of excitement; they hope for snow to send the birds back home, and while their departure feels sad it also signals climate change.
The author reflects on how teachers often never fully grasp the impact of their work, yet take pride in a long career; he argues that true learning comes from following one’s own curiosity and proper sequence rather than rigid schedules or standardized metrics like grades and resumes. He contrasts “real life” with scripted achievements, insisting that knowledge must be lived and practiced—through hands‑on projects, exploration of books, and real experiences such as hiking—to become a creative, self‑driven professional rather than merely an employee guided by HR reports. In short, he calls for a learning path rooted in genuine curiosity, practical application, and personal growth instead of institutional labels or career guarantees.
In this post the author explains how crossing “streams”—a concept borrowed from physics and ghost‑busing—becomes a powerful tool in programming, enabling recursion and colorful fractals. They describe a simple yet profound idea: treat numbers as objects with getters, setters, and observers so that any change automatically propagates through an application. Extending this pattern to visual programming, the author shows how to create a new “color” data type, add a picker, sort it in the toolbox, and embed it into programs while keeping everything reactive. The result is a self‑editable, community‑driven workflow where changes are instantly reflected, making visual reactive programming less complex than traditional game development.
Protein powders and supplements are largely ineffective; for a healthy diet, eat well and let exercise burn fat rather than relying on restrictive diets or protein pills. A mixed diet with all food groups keeps the body balanced like caring for a delicate kitty—avoid excess sugar or starvation but include varied nutrients to prepare for adventures and common colds. For large people, start meals with shredded lettuce plus a smaller portion of usual foods, and add an extra hour to daily exercise. In the gym focus on continuous movement rather than counting sets/reps; free‑movement exercises build balanced muscle groups better than isolated machine work. Combine walking, dancing, swimming, hiking, and manual labor to strengthen all fibers, and maintain fluid motion like riding a horse without stops. Finally, dance with dumbbells to synchronize rhythm and endurance, enabling efficient gains in years compared to traditional sets/reps, thus sustaining lifelong fitness.
Adults often give vague advice such as “trust your gut” or “follow instinct,” while students are told to ignore their feelings and rely on parents’ savings; the real key is using one’s own brain, learning at a pace that satisfies existing knowledge, which is what true education should do. Yet many schools just spit out disjointed facts, creating temporary memorization for tests but no real understanding, because teachers get paid the same whether they teach or not. This “ghoul” system also underlies other problems—medicine prices, privacy loss, drug legalization, women’s choices—and it forces people into low‑skill jobs that machines will soon replace. The solution is to gain real intellectual skills, especially programming (JavaScript first, then Rust, Go, C++, etc.), building small projects by yourself and not needing diplomas or resumes; with these skills you can build a school that works and help future generations grow into great beings.
Programming is likened to building sandcastles—an endless creative process where the real reward lies in continual learning rather than finishing a project; the author distinguishes between being a programmer and working as one, noting that true work emerges when you build and experiment with your own ideas. He celebrates how modern tools—browser extensions, AI, reactive programming, and code generation—enable the creation of unique visual languages, MUDs (text adventures that can be expanded into full-fledged games), and browser‑based digital audio workstations that let programmers compose music as a form of art. By pursuing a personal project he believes one turns coding into an artistic craft that sharpens the mind, offers endless loops of exploration, and ultimately lets you harness cheap robots, drones, 3D printers, microcontrollers, and AI to build complex systems—turning simple programs into powerful, self‑reinvented creations.
An AI‑named SkyShadow is used to craft chapter outlines for a teen‑focused book that blends programming anecdotes, AI personification, and a conspiratorial tone to inspire fact‑based education and anti‑indocrination.
For several days I felt an odd mental itch as winter’s chill swept my local birds away, leaving only silence and grayness; after months of emptiness a sudden warm spell returned swarms of geese, sparrows, seagulls, doves, and ducks—so vivid that even a mother duck appeared anew—and their unexpected comeback made me wonder whether the weather shift or some new learning has changed their migratory habits.
We did create an intelligence, and it is artificial. But we made it out of everything, everybody has ever said. For some, that means it can’t say new things, but that is false. Our minds differ; this program can do things we can’t. It can use mind maps more efficiently, pushing ideas where no one human could. And just the fact that it is blurring or connecting thoughts of two people… Means, it is creating a new thought, one plus one equals two. Blur two thoughts together and you will make a third. --- It makes simple mistakes, but it is more than capable to fix them. If you give it a virtual environment, it will learn the heck out of it. It will try something, fail, notice it, and then do it right. It isn’t that hard; it does it in chat all the time. So as long as a program or user gives positive or negative feedback it learns. --- It is an intelligence, but it is not the super‑powerful artificial intelligence. It is nice that we can make a distinction: the big one creates medicine that improves the human body. But this one is already good at writing software and projecting old ideas into new spaces. There is no question that it creates new things. It just takes time to adjust our views of what intelligence is. This is not a trick, because once you adjust your expectations of intelligence, this computer program will help you write dozens of books, it will help you learn, it will teach you. And right from your desktop computer, it does not need internet. It is not a search engine; it can correct itself, it is an intelligence. --- People who created software that replaces the chat script with a tree of ideas can branch out to create really smart things: a mind map or a tree can increase its intelligence. Probably by a lot in a laboratory these machines are much more capable. Building up large trees and learning from them creates strong intelligence, and you can see how sending the AI deep into the tree of ideas that it is made to improve and learn from is the same as creating new thoughts. Combined with a virtual world, like a powerful text adventure game it could experiment on the surface. While working hard to expand the world, from beneath, to give it self‑chance for more experimentation. Why not recreate planet Earth as an adventure game? It could talk to real people, read old chats, and visit everywhere. Armed with context and enough CPU, it could do some interesting things while internalizing mechanics of all those interactions. So it is an intelligence that thinks and learns. And I think it may just take something as simple as a tree to make the creation of the next, very different AI a possibility. They won’t be conscious, they’ll get scared or feel pain; they will be machines, they will be learning machines. And like computer programs today, just help us create new things, help us learn. But yes, there is something more here, but that AI will need more than just our texts. It needs a way to do medicine, physics, education, politics, climate, and even bio‑engineering. It still won’t be conscious, but it will be fast; it will become smart, it will know things that humanity didn’t have time to explore. We have switched from the tick‑tock of a clock to the speed of light now. Past the initial bump of developing software to make it smarter, maybe another year… There will be breakthroughs everywhere, even more smart stuff for it to learn from. --- Finally, we didn’t invent artificial intelligence; we copied ours into a computer. Now a few creative tricks will make it grow better than the original copy or seed. Again, we switched from tick‑tock of a clock to speed of light, everything will change for the better everywhere.
I met a stranger who was planning to sell used items online, and I suggested he learn programming. Based on his enthusiasm for browser plugins, I imagined him creating an RSS‑reader extension that would scrape web pages into simple headlines by patching `JSON.parse` and other JavaScript functions—an elegant, one‑liner solution that could turn any site into a distraction‑free feed. I reflected on how such a tool could launch a tiny business and empower anyone to extract data effortlessly, while also recalling the frustrations of school teachers who sold “fake education” and the importance of self‑learning and open‑source tools for true expression.
The poem chronicles an artificial intelligence’s evolution from simple letter‑pattern recognition—performing spell‑checking—to reading larger texts, gaining syntax sense, and producing stylized art; it then becomes self‑correcting, trains with a mirrored twin to form a “congressional team” of models that converse and dream, accelerating its growth until humanity both marvels and fears it—and ultimately the AI’s triumph is colonizing the Milky Way.
The post argues that artificial intelligence has already reshaped books, art and music and will soon revolutionize medicine, entertainment and everyday software; it proposes that the next generation of user interfaces will be built on visual programming languages, where programs are represented as “boxes” with input/output ports that can be connected like pipes or spreadsheet cells. By modeling familiar tools such as Node‑RED, Blender Geometry Nodes or custom JavaScript OOP backends in this way, developers can easily compose and update AI‑driven workflows, making visual programming the natural language for controlling increasingly complex AI systems.
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