AsianDadEnergy's Substack Podcast

AsianDadEnergy
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This is a very public journal of anxiety, existential dread, and way too much tech knowledge. Basically therapy, but with Wi-Fi. asiandadenergy.substack.com

  1. 4d ago

    AI Is About to Crash. Here’s Why.

    Hello world. I’m an unemployed ex Big Tech software engineer with 25 years of experience in the technology industry. And lately, I’ve been looking at the AI industry and thinking: Is it just me, or is this bubble looking extra bubbly? Because something feels different. The AI industry is still burning through enormous amounts of money. The companies at the center of the AI boom continue to require staggering amounts of capital to build data centers, buy GPUs, train models, and keep everything running. But suddenly, the tone seems to be changing. We’re seeing some of the most insanely valued companies in history preparing to go public. We’re hearing calls for government support. And we’re seeing AI executives who spent years predicting an imminent AI driven jobs apocalypse suddenly sounding a little more... cautious. Hmm. That’s interesting. To me, this looks a lot like peak bubble behavior. It reminds me of what happens near the end of every major financial mania. Everyone starts looking for the next investor willing to buy into the dream before the music stops. Or, as we like to call them in the financial world: Bag holders. But why is this happening now? I think there are several things happening beneath the surface that are starting to expose a fundamental problem with the current AI boom. And before the AI true believers come after me with pitchforks and flaming GPUs, let me be clear. I believe AI is going to be incredibly important. I just don’t believe we have Artificial General Intelligence. Not even close. We Don’t Have AGI. We Have Very Expensive Probabilistic Parrots. Yes, AI has gotten dramatically better. We have agentic systems. We have tool integrations. We have models that can write code, analyze documents, generate images, conduct research, and occasionally pretend to be a competent junior employee. But fundamentally, today’s large language models are still probabilistic systems predicting what comes next based on patterns learned from enormous amounts of data. They can do remarkable things. But they still struggle with consistency, reasoning, context, hallucinations, and knowing when they don’t know something. And because of that, I’m skeptical that today’s AI is suddenly going to invent the next Warp Drive and increase global productivity by 10,000 percent. Claude is not going to wake up tomorrow and announce: “Good morning, humans. I have solved faster than light travel. Also, I fixed the economy.” Sorry. But there is one thing AI could potentially do extremely well. It could replace human labor. And I think that’s the gigantic bet hiding underneath the entire AI boom. The AI Industry Has Made a Trillion Dollar Bet on Human Labor Think about the economics. The AI industry has attracted and consumed enormous amounts of capital. And whether we’re talking about investor money, corporate spending, or debt financing, the numbers are staggering. The basic premise behind much of this investment is that AI will eventually generate enormous profits by automating human work. Especially white collar work. And that’s the only economic story that really makes sense to me. Because if you are spending hundreds of billions, or potentially trillions, building the infrastructure required to run AI, eventually you need to make that money back. And you can’t do that by selling a $20 ChatGPT subscription to every person on Earth. You need something much bigger. You need to capture a meaningful percentage of the economic value currently generated by human workers. And that’s why, for years, we’ve heard predictions from some of the biggest names in AI about massive numbers of white collar jobs being automated. Software engineers. Lawyers. Accountants. Customer service representatives. Consultants. Researchers. Basically anyone who spends their day sitting in front of a computer. The logic is straightforward. If AI can replace millions of expensive human workers, the companies providing that AI can potentially capture a gigantic amount of economic value. And if you believe the more extreme AI predictions, we’re talking about tens of millions of workers eventually being replaced. That’s a massive opportunity. Except... There’s a problem. It’s not happening fast enough. The AI Productivity Revolution Is Taking Longer Than Expected For all the talk about AI replacing human workers, we’re not seeing anything remotely close to the scale necessary to justify the industry’s enormous financial commitments. We’re certainly not seeing millions upon millions of white collar workers being replaced every year. And my own experience as a software engineer has given me a front row seat to the problem. AI can be incredibly useful. But getting useful work out of AI is not as simple as typing: “Hey Claude, please build my billion dollar software company.” Believe me. I’ve tried. The problem is that getting AI to produce consistently high quality work still requires a surprising amount of human intelligence. You have to manage context. You have to understand the limitations of the model. You have to work around gaps in the training data. You have to check its output. You have to catch hallucinations. You have to design workflows. And when the AI inevitably does something completely insane, you have to figure out why. In other words, AI doesn’t necessarily eliminate human work. Sometimes it just changes the kind of human work you’re doing. And this isn’t just a problem in software engineering. We’re seeing similar challenges in other areas that were supposedly easy targets for automation. Customer service, for example, has long been considered one of the obvious use cases for AI. But when AI agents make mistakes, misunderstand customers, or confidently give completely incorrect answers, companies have a problem. There have already been cases where AI automation initiatives had to be rolled back and human workers brought back into the loop. Oops. Turns out customers don’t particularly enjoy being gaslit by a chatbot. Who knew? The bottom line is that AI simply isn’t replacing human workers at the scale the industry’s financial model appears to require. And I think the AI industry is starting to realize this. Which brings us to another problem. The Open Source AI Problem The American AI industry has been built around enormous closed models. ChatGPT. Claude. Gemini. These companies control the models, the infrastructure, the data, and the computing resources. And the plan, at least in theory, is pretty familiar. Spend an insane amount of money. Build the best technology. Gain market dominance. Kill the competition. Then raise prices and enjoy enormous profits. Silicon Valley has used this playbook many times before. But there is one big problem. The rest of the world is not sitting around waiting for America to establish an AI monopoly. Open source AI models have gotten incredibly good. And companies outside the United States, particularly in China, have made remarkable progress developing powerful models with significantly fewer resources. These models can be downloaded. They can be modified. They can be run on your own infrastructure. And increasingly, they are becoming good enough for many real world use cases. That’s a huge problem for the AI industry’s dream of monopoly profits. Because if a company can download a capable open source model and run it locally for a fraction of the cost of paying an American AI company every time an employee asks a chatbot to write an email... Well. That’s not exactly great news for the people trying to build a trillion dollar AI toll booth. And this brings me to another trend that I think is even more important. The Rise of Local AI You don’t necessarily need a giant data center to run AI anymore. With techniques like quantization and distillation, massive frontier models can be compressed into smaller models that can run on increasingly affordable hardware. Your desktop. Your home server. Your laptop. Your own private infrastructure. And this has two enormous advantages. First, you don’t have to keep paying a Big Tech AI company every time you want to use the model. Second, your data doesn’t have to leave your computer. For businesses and individuals who care about privacy, that’s a pretty big deal. And as local models become more capable, something else happens. The value of premium AI models starts to decline. Why pay $100 a month for the world’s most powerful AI model if a local model running on your own hardware can handle 95 percent of what you actually need? It’s the same problem that open source software created for proprietary software companies. If the free alternative is good enough, the premium product has to work very, very hard to justify its price. And that brings us to the fundamental problem. The AI Industry Needs Productivity Gains. Fast. The AI industry has spent an enormous amount of money based on the assumption that AI will eventually generate enormous economic returns. But eventually isn’t good enough. The debt has to be serviced today. The data centers have to be paid for today. The GPUs have to be purchased today. The employees have to be paid today. The electricity bill, unfortunately, does not accept payment in future AGI promises. So the industry needs massive productivity gains. And it needs them soon. But what we’re seeing instead is a technology that is incredibly useful in some situations, moderately useful in others, and occasionally produces something that makes you stare at your monitor for five minutes wondering how a machine with a trillion parameters managed to screw up something a reasonably intelligent eight year old could have done correctly. That’s not AGI. That’s Tuesday. The technology will improve. I’m confident of that. But the question isn’t whether AI will eventually transform the economy. I think it will. The question is: Will it transform the ec

  2. 6d ago

    Time Is Going By Too Fast... Here's Why

    One of the strangest things about getting laid off from Big Tech is realizing that, for the first time in decades, I actually have time. And as strange as this new chapter has been, I’ve noticed something surprisingly wonderful. Time has slowed down. Not literally, of course. The Earth is still spinning at roughly the same speed. My clocks haven’t suddenly become defective. Monday still becomes Tuesday whether I like it or not. But my perception of time has changed dramatically. And honestly? It feels a little bit like I’ve been given a life extension for free. Where Did All the Time Go? When I was working, time seemed to fly. Days disappeared. Weeks blurred together. Months would pass, and I’d suddenly realize that an entire season had come and gone. I’d look back and think, Wait. That was six months ago? It feels like it happened three weeks ago. The older I got, the faster it seemed to happen. I remember being a kid and feeling like summer vacation lasted forever. Now, somehow, I’ll blink and it’s Thanksgiving. I’ll blink again and it’s Christmas. I’ll blink one more time and I’m wondering why the grocery store already has Valentine’s Day decorations. What happened? Why does time seem to accelerate as we get older? I never really thought about it when I was working. I was too busy. There was always another meeting. Another deadline. Another project. Another email. Another fire to put out. I didn’t have time to stop and ask why I didn’t have time. Now that I have more time, I finally got curious. And after doing some reading and thinking about my own experiences, I came across a few explanations that made a lot of sense. The Aging Brain The first explanation is probably the least surprising. We’re getting older. Our brains change as we age, and those changes may affect how we perceive the passage of time. One way I’ve come to think about this is through the analogy of a video game. Imagine playing a first person shooter when your computer is capable of rendering 120 frames per second. Everything feels incredibly smooth. Now imagine that, as the computer gets older, it can only process 60 frames per second. The game is still running at the same speed in the real world, but you’re receiving fewer visual frames. The experience feels different. Some research into the perception of time suggests that something similar may happen in the aging brain. As our neural networks change, the brain’s processing of information can change as well. The details are considerably more complicated than my video game analogy, but the basic idea is that the way our brains process and encode experiences changes as we age. And this may contribute to our subjective experience of time. But I think there’s another factor that’s even more interesting. The Problem With Autopilot Think back to childhood. Almost everything was new. Your first day of school. Your first time riding a bicycle. Your first trip on an airplane. Your first video game console. Your first crush. Your first time getting in trouble for doing something incredibly stupid. When you’re a child, your brain is constantly encountering experiences it hasn’t seen before. As we get older, that changes. We become experts at navigating the world. We know how to drive to work. We know how to make coffee. We know how to check email. We know how to sit through meetings. We know how to do our jobs. We know how to drive home. And then we do it again tomorrow. And the day after that. And the day after that. This is one of the great advantages of having an experienced brain. We don’t need to consciously process every little detail of our lives. Our brains can recognize patterns and automate familiar behaviors. That’s incredibly useful. But I suspect there’s a downside. When you’re operating on autopilot, you’re not creating as many distinct memories. Think about a typical commute. You drive the same roads you’ve driven hundreds of times. You pass the same buildings. You stop at the same traffic lights. You arrive at work. You might remember the commute as a whole, but you probably can’t tell me what you saw at 8:17 AM on Tuesday three weeks ago. Your brain didn’t consider that information important enough to preserve. Now imagine doing that for years. Same commute. Same desk. Same meetings. Same projects. Same routines. Eventually, you look back and realize that five years have somehow disappeared. The days were full of activity. But your memory contains relatively few distinct markers separating one day from another. And when you look backward, those years can feel incredibly short. This might explain one of the strangest paradoxes of getting older: You have more years behind you, but those years can feel like they’re passing faster. Then We Added Social Media As if living on autopilot wasn’t enough, we now have another problem. Digital overstimulation. For many of us, when the workday ends, we don’t actually stop. We pick up our phones. We open social media. We scroll. And scroll. And scroll. One video becomes another. One post becomes another. One outrage becomes another. One argument becomes another. And before we know it, an hour has disappeared. The irony is that this content is incredibly stimulating, but the experience itself often leaves very little behind. Think about what humans experienced for most of our existence. There was a lot of boredom. A lot of boredom. You might spend hours walking somewhere. Working in a field. Gathering food. Making something by hand. Sitting around a fire. Waiting. Waiting some more. Modern humans have largely eliminated this kind of boredom. Instead, we have created an endless stream of content specifically engineered to capture our attention. And there’s something interesting about this. Our brains have to decide what information is important enough to remember. But what happens when we’re exposed to thousands of stimulating pieces of information every day? Everything is urgent. Everything is shocking. Everything is outrageous. Everything is designed to trigger some kind of emotional reaction. Eventually, nothing is special. Your brain becomes overwhelmed by the sheer volume of information. And the result may be that relatively little of it becomes a meaningful, lasting memory. You spent an hour scrolling. But what do you remember? Maybe nothing. And yet that hour is gone forever. This is where I think the combination becomes particularly dangerous. Repetitive routines during the day create fewer memorable experiences. Digital overstimulation during our free time creates an endless stream of forgettable experiences. And then we wonder why life feels like it’s flying by. So How Do We Slow It Down? Here’s the interesting part. After getting laid off, my perception of time changed dramatically. I don’t think it’s because unemployment magically alters the laws of physics. It’s probably because my lifestyle changed. I started doing things differently. And I think some of those changes are things that almost anyone can try. 1. Switch Things Up The first thing I’ve found helpful is introducing novelty into my life. Nothing dramatic. You don’t need to quit your job and become a professional skydiver. Sometimes it’s as simple as taking a different route to the store. Going to a different grocery store. Learning something new. Changing the order of your daily activities. I have a bunch of different hobbies and projects. Journaling. Software development. Drone piloting. Coaching. Gardening. And I’ve noticed that when I change what I do from day to day, the days feel longer. I’m not necessarily doing more. I’m just doing different things. The brain has to pay attention. And when the brain pays attention, it creates more distinct experiences. Those experiences become memories. And when I look back on the week, it feels like a week actually happened. Not just one generic Tuesday that somehow got copied and pasted seven times. 2. Be Where You Are The second thing I’ve found helpful is focusing intensely on the present moment. This can be difficult. Our minds are constantly trying to escape the present. We’re thinking about something that happened yesterday. We’re worrying about something happening tomorrow. We’re mentally composing an email while someone is talking to us. We’re sitting at dinner while scrolling through our phones. We’re physically somewhere. But mentally, we’re somewhere else. I’ve found that activities requiring complete attention can dramatically change my perception of time. One example is my daily 15 minute meditation. When I’m meditating, I have to pay attention to my breathing. My posture. My thoughts. My mental imagery. And something strange happens. Fifteen minutes feels like a long time. Not in a bad way. It feels like I’ve actually experienced those fifteen minutes. Another example is swimming. I recently started taking swimming lessons. This is a big deal for me because I had a pretty bad experience with water as a child, and as a result, I’ve spent most of my life avoiding learning how to swim. Now I’m trying to overcome that. And let me tell you something. When you’re in the deep end of a pool, you’re trying to float, your face is underwater, you’re blowing air out of your nose, and your brain is screaming, This is a terrible idea! You are very much in the present moment. There is no thinking about your email. No worrying about tomorrow’s meeting. No doomscrolling. Just you, the water, and the immediate question of whether you’re about to embarrass yourself in front of the swimming instructor. And here’s the weird part. Those moments seem to last forever. But they also become incredibly memorable. I can remember specific moments from my swimming lessons days later. Which makes me wonder if a certain amount of fear and discomfort might actually be necessary for a satisfying life. Not constant terror,

    Time Is Going By Too Fast... Here's Why

  3. Jul 15

    Your Job Won’t Remember You. Your Family Will.

    Hello World! Last week, my family and I spent several wonderful days exploring New York’s Finger Lakes. There wasn’t anything particularly extraordinary about the trip. We went sightseeing. We ate good food. We laughed. We wandered around. We took far too many pictures that will probably never leave our phones. But somewhere in the middle of it all, while watching my kids run around and seeing everyone genuinely happy, I was reminded of something that I think many of us spend years forgetting. Time is our most valuable resource. Not money. Not status. Not promotions. Time. Once it’s gone, it is gone forever. There Will Always Be Another Meeting Modern life has a funny way of convincing us that everything is urgent. Another meeting. Another deadline. Another sprint. Another quarter. Another performance review. There is always one more project that absolutely must get finished. The problem is that while work can always generate another task, life doesn’t generate another childhood. Your son is only twelve once. Your daughter only wants to hold your hand for a surprisingly short number of years. Your parents only have so many healthy summers left. Those opportunities don’t get rescheduled. They simply disappear. The Lesson I Learned After Being Laid Off Getting laid off after twenty five years in the technology industry changed far more than my employment status. It changed how I value my time. For most of my career, I believed what many professionals believe. Work hard. Do a good job. Be dependable. Earn promotions. Climb the ladder. None of those things are inherently bad. Work gives us purpose. It pays our bills. It provides structure. It allows us to care for the people we love. But somewhere along the way, many of us quietly allow work to become the center of our identity. Then one day the company restructures. Management changes. Budgets get cut. Artificial intelligence reshapes the business. Or someone you’ve never met decides your position no longer exists. Just like that, years of loyalty are reduced to a brief HR meeting and a severance package. The company moves on. Eventually, everyone does. What Actually Lasts That realization can feel depressing at first. It can even make the universe seem strangely indifferent. But I think there is another way to look at it. If careers are temporary, then maybe we should stop expecting them to provide permanent meaning. Because when our lives are over, nobody is going to gather around our hospital bed to admire our LinkedIn profile. Nobody is going to remember that one presentation you finished at two in the morning. Nobody will care how many meetings you attended. Instead, people remember something much simpler. The laughter around the dinner table. The road trips. The vacations that almost didn’t happen because everyone was “too busy.” The conversations that lasted late into the night. The traditions that only your family understood. The times you showed up when someone needed you. Those become the stories that get told long after we’re gone. The Real Return on Investment As someone interested in financial independence, I spend a lot of time thinking about investing. Stocks. Real estate. Cash flow. Retirement simulations. Compound interest. Those things matter. But there is another investment that compounds in a very different way. Experiences. A weekend camping trip. A family vacation. Teaching your child to fish. Watching a sunset together. Sharing an ordinary dinner without everyone staring at their phones. Unlike financial assets, these experiences appreciate in a way that can’t be measured on a spreadsheet. Years later, they become treasured memories. Sometimes they become family stories that get passed down for generations. That is a return no investment portfolio can match. Redefining Success I don’t think success is about rejecting work. We all need to earn a living. We all have responsibilities. But perhaps success isn’t maximizing every dollar. Perhaps success is maximizing the moments that money makes possible. Financial independence isn’t valuable because it lets you stop working. It’s valuable because it gives you more control over your time. And time is the one resource that every billionaire, every CEO, every janitor, and every retiree receives in exactly the same way. None of us knows how much remains. Protect What Matters Most If there is one lesson I hope my layoff has taught me, it is this. Protect your time with the people you love. Guard it just as fiercely as you guard your savings account. Invest in experiences, not just assets. Take the trip. Go to the family reunion. Call your parents. Eat dinner together. Watch the sunset. The emails will still be there tomorrow. The meetings will still be scheduled next week. The corporate ladder will still exist. But today’s memories can only be created today. At the end of our lives, our greatest legacy won’t be our job title. It won’t be the size of our investment portfolio. It won’t be the number of promotions we earned. Our legacy will be the happiness we created, the love we shared, and the memories that continue to live in the hearts of the people we cared about. That, I think, is a life well lived. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

  4. Jul 8

    The College System Is About to Collapse?

    Over the Fourth of July weekend, my dad, my son, and I went on one of our annual boys club fishing trips. Between catching countless panfish, my dad brought up a topic that instantly transported me back to my teenage years. He told me that I needed to do everything possible to get my son into a prestigious Ivy League university. To him, this was obvious. To me, it was deeply unsettling. I spent most of the conversation trying to explain that artificial intelligence is fundamentally changing the economics of higher education. A degree from an elite university simply does not offer the same value proposition that it did thirty years ago. Unfortunately, that argument went nowhere. Instead, it reminded me of just how much pressure I experienced growing up. Like many Asian kids, I was told that admission into a top university would determine the entire course of my life. My childhood became an endless cycle of SAT preparation, Advanced Placement classes, extracurricular activities, and constant competition. The message was simple. Get into a top university and success would follow. Fail, and your future would be ruined. Even today, decades later, thinking about college admissions still raises my blood pressure. As a father, I now find myself asking a question that my parents never had to consider. What is the purpose of a university in the age of AI? The University Was Never Just One Thing When people think about universities, they usually imagine classrooms, professors, lectures, exams, and diplomas. But universities have always been several different institutions bundled together. They conduct research. They train workers. They certify credentials. They provide networking opportunities. They help young adults develop socially. For decades, this bundled model worked remarkably well because every one of these functions reinforced the others. Graduates earned valuable credentials. Employers trusted those credentials. Students accepted enormous tuition costs because those credentials led to high paying white collar careers. The system made economic sense. At least it used to. The Cracks Started Before AI Even before large language models appeared, higher education was already showing signs of stress. Universities competed for students by building luxury dormitories, massive recreation centers, and professional quality athletic facilities. Tuition exploded. Student loan debt exploded. Education increasingly shifted away from intellectual development and toward vocational training. Instead of asking students how to think, universities increasingly focused on preparing students for specific careers. Then AI arrived. AI Breaks The Educational Model Artificial intelligence does not simply improve education. It undermines many of the assumptions that higher education has relied upon for generations. AI can explain existing knowledge more effectively than many lecturers. AI can tutor students individually. AI can write convincing essays. AI can solve homework assignments. AI can pass many college examinations. This creates uncomfortable questions for me. If AI teaches the lecture, why attend the lecture? If AI writes the essay, what exactly is the essay measuring? If AI passes the exam, what does the diploma actually certify? The college term paper perfectly illustrates this problem. When I was in school, writing a major paper required weeks of research, organization, revision, and critical thinking. The paper itself was never the valuable part. The value came from the thinking required to produce it. Today, large language models can generate that same final product within minutes. The artifact still exists. The learning process does not. Once that happens, the assignment no longer measures what it was designed to measure. Universities Were Really Measuring Human Thinking For generations, universities served as society’s measurement system for cognitive professions. A degree signaled that someone possessed enough knowledge and reasoning ability to perform complex white collar work. But AI changes that equation. Many of the cognitive tasks that universities prepare students to perform are rapidly becoming automated. If those jobs disappear, then much of the traditional university model loses its economic foundation. Higher Education Will Fragment I do not believe universities will disappear. I believe they will break apart into specialized institutions. Research institutes may become independent organizations funded by governments, private companies, or nonprofit organizations. Technical credentialing may shift toward affordable online providers that continuously update practical skills rather than requiring four year degrees. Communities focused on networking and social development may evolve entirely outside traditional campuses. Most importantly, I believe a new category of institution will emerge. Schools whose primary mission is teaching people how to think. Teaching Humans To Think This may sound strange at first. Isn’t that what universities already do? Increasingly, I do not think so. When I talk about thinking, I mean reasoning. Judgment. Agency. Taste. Ethics. Persuasion. Understanding human motivations. Making decisions under uncertainty. These are the capabilities that remain extraordinarily valuable in an economy increasingly dominated by artificial intelligence. Future education should not ban AI. It should teach students how to collaborate with AI while maintaining independent judgment. Students should learn how to verify evidence. Challenge AI generated conclusions. Recognize hallucinations. Understand the limits of machine intelligence. AI should become a thinking partner. Never a thinking replacement. Assessment would also need to change. Instead of take home essays generated by language models, students may demonstrate their reasoning through live discussions, debates, collaborative problem solving, and real time decision making. Perhaps professors themselves evolve into mentors rather than lecturers. People whose greatest contribution is not transferring information, but sharpening judgment. Ironically, liberal arts subjects that many universities have spent decades marginalizing, including philosophy, history, mathematics, political theory, and physics, may become some of the most economically valuable disciplines because they teach people how to think instead of simply training them for a specific job. The University After AI I am not convinced that artificial intelligence will replace every form of human work. As long as AI remains a powerful tool rather than true artificial general intelligence, society will still require a relatively small class of professionals capable of solving novel problems, exercising judgment, and making difficult decisions. Those people will create new companies. Invent new products. Lead institutions. Navigate uncertainty. The education system that produces those people will look very different from the universities we know today. It will place wisdom above memorization. Judgment above credentials. Thinking above information. As a father, I hope those institutions exist by the time my son reaches adulthood. Because I suspect those are the schools that will matter most. The future belongs not to the people who know the most. It belongs to the people who can think the best. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

  5. Jul 4

    I Got Laid Off... Now I Make $11,000 a Month Doing Whatever I Want

    When I got laid off from my Big Tech job late last year, I thought I knew what came next. Shock. Anger. Shame. Sadness. If you’ve ever been laid off, you probably know the feeling. It is as if someone has ripped away not just your paycheck, but your identity. After spending twenty five years in the technology industry, I suddenly found myself unemployed. Meanwhile, every week seemed to bring another announcement of mass layoffs across the tech industry. Friends were losing jobs. LinkedIn became an endless stream of people posting that they were “excited to announce” they were looking for work. It was depressing. But something unexpected happened. Over the following months, I slowly came through the other side. Instead of waking up every morning dreading another day of meetings, deadlines, and corporate politics, I started waking up excited. Some days felt almost euphoric. There were so many things I wanted to learn, build, and explore that I genuinely did not want the day to end. My layoff had accidentally pushed me into something I never would have chosen for myself. Early retirement. I Know I’m One of the Lucky Ones Before going any further, I want to acknowledge something important. This is only possible because I spent many years earning a high salary in tech while aggressively saving and investing. For well over a decade, my wife and I consistently lived below our means. We invested. We avoided lifestyle inflation. We paid off debt. Over time, those boring financial decisions compounded into something extraordinary. Financial independence. Without that foundation, this story would have been very different. I understand that. I do not take that privilege lightly. The People I’m Really Writing This For Ironically, this article is not for people who have already reached financial independence. It is for the software engineers who are still trapped. Maybe you are still employed. Every round of layoffs leaves your team smaller while your workload somehow becomes larger. You spend your days juggling impossible deadlines while carrying survivor guilt because your friends lost their jobs instead of you. Maybe you have already been laid off. Now your life revolves around LinkedIn, recruiter calls, algorithm interviews, and endless rejection. Maybe after decades of experience you are being offered salaries that would have seemed insulting just a few years ago. I genuinely feel for you. That is why I wanted to share something practical. What actually pays my bills today? Where My Income Comes From People often assume that early retirement means sitting on a beach collecting investment income. My reality looks very different. Today my family earns just under eleven thousand dollars per month from a collection of different income streams. Our two rental properties generate about thirty nine hundred dollars per month. Stock dividends from our taxable investment accounts contribute roughly fifteen hundred dollars. Interest from our high yield savings account adds another three hundred dollars. Those are the traditional sources. The interesting part comes next. I Accidentally Started Getting Paid for My Hobbies One thing nobody tells you about early retirement is that you suddenly have an enormous amount of free time. At first, that feels strange. Then it becomes exciting. I started learning new things. I planted an herb garden. I began learning to read Chinese. I worked toward my drone pilot license. I learned how to swim. Then I discovered something fascinating. In today’s economy, it takes surprisingly little extra effort to monetize hobbies you would have pursued anyway. That realization completely changed how I think about work. YouTube Started as Therapy I never planned to become a YouTuber. After my layoff, I fell into a depressive spiral. My therapist suggested journaling. Writing never really worked for me. Talking did. So I started recording videos. That simple habit became surprisingly therapeutic. Then something else happened. People started watching. Even more importantly, they started responding. After years of talking with coworkers every day, unemployment can become surprisingly lonely. These conversations became my new social outlet. Comments turned into discussions. Discussions became livestreams. Livestreams became friendships. Eventually YouTube started paying me around twenty eight hundred dollars per month. Other creator platforms contribute another couple hundred dollars. The money is nice. The sense of community is even better. Coaching Doesn’t Feel Like Work Another unexpected hobby became coaching. I schedule one on one conversations with people using Calendly. Sometimes we talk about software engineering. Sometimes financial independence. Sometimes career transitions. Sometimes life. The conversations are genuinely enjoyable. After decades of solving problems with people, I realized communication is like a muscle. If you stop using it, it weakens. Coaching lets me keep exercising that muscle while earning around twelve hundred dollars per month. I Fell Back in Love With Programming Ironically, I enjoy programming far more now than when I was employed as a software engineer. Without deadlines. Without sprint planning. Without endless meetings. Without office politics. Coding became fun again. I build software that scratches my own itch. Sometimes those projects make money. Sometimes they do not. Either outcome is perfectly fine. One project was an AI powered workflow that generated wall art for online marketplaces. I ran it for only two days before deciding it created very little real value. I shut it down. The listings still earn around seven hundred dollars every month. Another project called Funemployment Day began as a personal tool for tracking my time after leaving corporate life. Today it has hundreds of users and some paying subscribers. Combined, my software projects generate around one thousand dollars each month. Agentic AI Changed Everything One thing that genuinely surprised me is how dramatically AI has lowered the barrier to entrepreneurship. Not because it writes perfect code. It absolutely does not. But because it removes so much of the boring work surrounding a project. Once I publish a YouTube video, AI helps automate titles, descriptions, transcripts, articles, short form videos, and publishing across multiple platforms. Instead of spending hours on repetitive tasks, I spend my time thinking, building, and creating. That feels like a much better use of both humans and machines. Is This a Preview of the Future? Altogether, these income streams generate just under eleven thousand dollars every month. For some readers, that sounds like a fortune. For others, it is much less than their current salary. The number itself is not really the point. The point is that none of this income comes from a traditional full time job. Instead, it comes from assets, hobbies, creativity, relationships, and small software products. Sometimes I wonder if this is a tiny glimpse of what a post labor economy might eventually look like. Not necessarily a utopia. Perhaps something much stranger. As artificial intelligence continues to automate more forms of work, I suspect many more people will eventually find themselves earning income from portfolios of projects rather than a single employer. Maybe this is the future. Maybe it is not. I honestly do not know. What I do know is that my layoff forced me onto a path I never would have chosen voluntarily. Looking back now, I am grateful it happened. If you are currently burned out, unemployed, or wondering whether there is life beyond the corporate ladder, I hope my story gives you at least one idea worth exploring. Sometimes the worst day of your career becomes the beginning of an entirely different life. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

  6. Jun 30

    Why Everyone SEEMS to Have More Money Than Me?

    Every once in a while, I experience a feeling that I’m not particularly proud of. It’s the feeling that everybody else is rich. They all seem to have more money than I do. Bigger houses. Newer cars. Better vacations. Better lives. And somehow, despite everything I’ve accomplished, I feel like I’m falling behind. These days it doesn’t happen very often, but every now and then it sneaks up on me. Maybe I’m watching YouTube and someone is giving a tour of their enormous house. Maybe I’m watching Netflix, where every “ordinary” family somehow lives in a multimillion dollar home. Or maybe I’m driving my used Honda CR-V when another successful-looking middle-aged Asian guy cruises by in a brand new Tesla. For a brief moment, my brain whispers: “What happened? Did everyone else figure something out that I didn’t?” Then almost immediately I feel embarrassed for thinking that way. Because I know something that my emotions conveniently forget. Most people are not rich. The Data Doesn’t Match the Feeling If you look at the numbers, only a tiny percentage of American households qualify as liquid millionaires, meaning they have at least one million dollars in investable assets. Even among that group, a million dollars isn’t exactly “private jet” money. Where I live, in a high cost of living area, a million dollars doesn’t even buy many single-family homes. Objectively speaking, the overwhelming majority of Americans are not wealthy. So why does it constantly feel like they are? I’ve spent quite a bit of time thinking about this question, and I think I’ve come up with a few reasons. We Are Wired to Follow the Herd Human beings are social animals. Like apes, elephants, dolphins, and countless other social species, we instinctively look to the group for cues about what success looks like. The problem is that many people don’t have clearly defined personal goals. Without an internal compass, it’s incredibly easy to borrow someone else’s definition of success. Instead of asking ourselves what actually matters, we begin copying the outward appearance of people society celebrates. The expensive house. The luxury car. The designer clothes. The exotic vacations. The visible symbols become the goal, even if they have very little to do with happiness. Social Media Is a Distortion Machine Social media takes this very human tendency and cranks it up to eleven. People naturally want to share good news. Nobody posts pictures of arguing with their spouse over credit card bills. Nobody uploads videos of lying awake at 2 AM wondering how they’re going to make next month’s mortgage payment. Nobody posts photos of the panic attack they had after realizing they financed a lifestyle they can’t actually afford. Instead, everyone uploads their highlight reel. You see promotions. New homes. Perfect vacations. Luxury purchases. Beautiful weddings. Smiling families. You almost never see the anxiety that paid for those pictures. Social media also magnifies survivorship bias. Think about lottery winners. Think about meme stock millionaires. Think about people who got lucky with speculative cryptocurrencies. Millions of people lost money chasing exactly the same opportunities. But you only see the handful of winners. After enough exposure, your brain quietly concludes that extraordinary success is normal. It isn’t. Consumerism Needs You to Feel Inadequate America is fundamentally a consumer economy. Consumption isn’t simply encouraged. It’s necessary. If everyone suddenly stopped buying things they didn’t need, the economy would grind to a halt. Advertising understands something about human psychology. People don’t buy products. They buy identities. Watch almost any commercial. Notice the homes. The neighborhoods. The kitchens. The cars. The vacations. The wardrobes. The lifestyles being presented often resemble families in the top income brackets, yet they’re marketed as completely normal. It’s subtle. But over time, it recalibrates what “normal” looks like. The result is that millions of people begin chasing a lifestyle that statistically very few can actually afford. Debt Makes Everyone Look Rich Here’s the uncomfortable reality. Most Americans don’t possess enormous amounts of wealth. Yet many appear wealthy. How? Debt. Modern finance allows almost anyone to temporarily purchase the appearance of financial success. Luxury cars. Expensive homes. Designer furniture. High-end electronics. Exotic vacations. None of these necessarily indicate wealth. Many simply indicate access to credit. The problem is that debt has a hidden cost. Financial stress. Relationship problems. Mental health struggles. Lost opportunities. Years, sometimes decades, spent servicing yesterday’s consumption. Ironically, these displays of wealth create a psychological burden for everyone else. The illusion makes perfectly successful people feel like failures. I’ve certainly experienced it. Maybe you have too. The Bigger Picture: The K-Shaped Economy I think something even larger is happening beneath the surface. Our economy increasingly resembles a K. One branch rises upward. The other falls behind. The upper branch consists largely of people who own productive capital. Stocks. Businesses. Real estate. Increasingly... Artificial intelligence. Robotics. Automation. These assets can continue creating value twenty-four hours a day. Meanwhile, the lower branch depends primarily on labor. The problem is that labor doesn’t scale the way capital does. As AI improves, capital becomes dramatically more productive. Human labor, on the other hand, doesn’t become exponentially more valuable simply because technology advances. In fact, many forms of labor may become less valuable over time. That doesn’t necessarily mean society is doomed. Perhaps governments adapt. Perhaps entirely new industries emerge. Perhaps we’ll experience major political or economic reforms. Nobody knows. But I do think the gap between owners of capital and sellers of labor is becoming one of the defining stories of our generation. If you’re fortunate enough to work in a high-paying field like technology, I believe one of your biggest priorities should be gradually converting income into ownership. Because ownership compounds. Labor generally does not. Three Ways I Try to Stay Grounded I don’t have all the answers. But these habits genuinely help me. 1. Define your own version of success. Don’t inherit someone else’s goals. Figure out what actually matters to you. Financial security. Freedom. Family. Purpose. Recognition. Adventure. Whatever it is, make sure it’s yours. Once you know where you’re going, other people’s lives become much less distracting. 2. Compare yourself with your past self. Comparison really is the thief of joy. Especially when you’re comparing yourself against someone whose financial situation may be almost entirely fictional. Instead, ask a simpler question. Am I a better version of myself than I was five years ago? If the answer is yes, you’re winning. Celebrate that. 3. Minimize social media. Yes, I realize the irony. You’re probably reading this because the internet recommended it. But I genuinely believe excessive social media consumption is one of the most damaging habits for our mental health. It constantly encourages us to compare our ordinary lives against everyone else’s carefully curated highlights. That’s a game you can never win. Sometimes the healthiest thing you can do is simply close the app. Final Thoughts I’ve come to believe that the feeling that “everyone else is rich” says far more about the world we live in than it does about our actual financial situation. We’re surrounded by advertising. We’re immersed in social media. We’re encouraged to borrow. We’re constantly shown lifestyles that belong to a tiny fraction of the population and told they’re normal. No wonder so many of us feel like we’re falling behind. But the feeling is not reality. Reality is quieter. Reality is slower. Reality is built over decades of consistent decisions rather than viral moments and luxury purchases. So the next time I see another shiny Tesla drive by while I’m sitting in my aging Honda CR-V, I’ll try to remind myself of something simple. I don’t need to win someone else’s race. I only need to keep making progress in my own. And honestly, that’s more than enough. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

  7. Jun 24

    The AI Coding Revolution Has a Huge Problem?

    A few weeks ago, I stumbled across a debate that has been making the rounds in software engineering circles. The spark came from Boris Cherny, an engineer at Anthropic and the creator of Claude Code, arguably the most influential AI Agentic Coding harness in the world today. During a podcast appearance, Boris made a statement that immediately grabbed my attention: Coding is largely a solved problem. He went on to explain that he hadn’t written a line of code by hand since November, and that essentially all of his code is now authored by Claude Code. Needless to say, this generated strong reactions. Some people interpreted it as evidence that software engineering is about to be fully automated. Others saw it as confirmation that AI coding tools are delivering unprecedented productivity gains. As someone with twenty-five years of experience in software development, I found myself somewhere in the middle. Because while I absolutely believe AI is transforming software engineering, my own experiences suggest that programming is nowhere close to being a solved problem. In fact, the more I use these tools, the more complicated the situation appears. The Rise of Agentic Software Development Over the past few years, we’ve witnessed a rapid evolution in how software gets built. First, developers used AI to generate snippets of code. Then they began using AI assistants to complete larger programming tasks. Today, we’re entering what many people call Agentic Software Development. Instead of asking an AI for a few lines of code, developers increasingly delegate entire workflows. The AI can analyze requirements. Generate designs. Write code. Create tests. Review its own output. Deploy software. Monitor production systems. In theory, the human becomes less of a programmer and more of an orchestrator. The promise is obvious. If AI agents can perform most of the implementation work, then software engineers can become dramatically more productive. Ten times more productive, according to some advocates. Perhaps even more. At least, that’s the dream. My First Encounter With Enterprise Agentic AI In 2025, I returned to work after a lengthy medical leave. My wife had experienced a serious health crisis, and I had spent months focused almost entirely on family. When I came back, one of the first things I noticed was that my employer had become obsessed with Agentic AI. Leadership had heard about tools like Claude Code and Cursor. They had heard stories about developers becoming ten times more productive. Naturally, they concluded that our company needed its own internal version. Let’s call it Kevin. Kevin was our homegrown agentic harness. Compared to Claude Code, Kevin felt slower, heavier, and burdened with enterprise compliance guardrails. It ran on older-generation models. It often struggled with context. And yet, despite all its flaws, Kevin was still capable of orchestrating significant portions of software development. Using Kevin gave me a front-row seat to what Agentic AI actually looks like inside a large enterprise. What I observed left me both impressed and concerned. The Business Knowledge Problem One of the biggest weaknesses I encountered had nothing to do with coding itself. It had to do with understanding. AI models are remarkably good at generating software. What they are not particularly good at is understanding the business context behind that software. Organizations often operate on thousands of unwritten assumptions. Knowledge exists in hallway conversations. Slack threads. Meeting notes. Institutional memory. The heads of senior employees. Much of this information never appears in formal documentation. Humans navigate these gaps naturally. AI agents do not. If a requirement is not explicitly documented, the AI will often substitute something that appears reasonable based on its training data. The generated code may compile successfully. The unit tests may pass. The architecture may look elegant. And yet the implementation may completely miss the actual business objective. This problem becomes particularly severe in large brownfield systems where decades of accumulated business logic exist beneath the surface. The Context Window Wall Another challenge is context. Every AI model has a limited working memory. For small projects, this isn’t a major issue. For enterprise software systems containing millions of lines of code, it becomes a constant battle. Once an AI agent exceeds its effective context window, strange things begin to happen. The model forgets previous decisions. It hallucinates APIs. It reintroduces deprecated libraries. It generates solutions that were already rejected earlier in the workflow. Developers have created countless mitigation strategies. Context compaction. Summarization. Subagents. Selective context filtering. These techniques help. But they don’t eliminate the underlying limitation. The larger the system becomes, the harder it is for the AI to maintain a coherent mental model of the entire application. Ironically, this is often where software engineering is most difficult in the first place. The Hidden Cost of Infinite Code One thing AI agents are exceptionally good at is generating code. Lots of code. An astonishing amount of code. Thousands of lines. Tens of thousands of lines. Entire subsystems can appear almost instantly. The problem is that quantity and quality are not the same thing. Many AI-generated implementations contain unnecessary abstraction layers. Duplicate functionality. Excessive complexity. Architectural choices that seem reasonable locally but become problematic globally. Without strong human oversight, repositories begin accumulating what can only be described as AI sediment. Layer upon layer of generated code. Each piece understandable in isolation. Collectively becoming harder and harder to maintain. Technical debt compounds quietly. And unlike financial debt, software debt often remains invisible until it becomes a crisis. The Vibecoding Trap This brings us to what I believe is the most important problem. Human review capacity. A team of AI agents can generate thousands of lines of code per hour. A human engineer cannot review thousands of lines of code per hour with high confidence. The math simply doesn’t work. As output increases, review quality inevitably declines. Cognitive fatigue sets in. Attention drops. Comprehension weakens. Eventually, the reviewer stops acting as an engineer and starts acting as a rubber stamp. This is the danger behind what many people call vibecoding. The developer repeatedly prompts the AI until something appears to work. The code ships. Nobody fully understands it. Nobody feels ownership over it. And nobody wants to maintain it six months later. At that point, accountability becomes largely fictional. The engineer remains responsible for the software without truly possessing the knowledge necessary to evaluate it. So Is Coding Solved? Despite everything I’ve written, I remain incredibly optimistic about AI. These tools are genuinely transformative. For greenfield projects, prototypes, internal tools, and well-understood problem domains, the productivity gains are astonishing. Recently, I used Agentic AI to build one of my own projects. The agents completed work in hours that might previously have taken days. The productivity boost was real. But here’s the important distinction: The AI performed the implementation. I still spent days reviewing the code, testing the software, validating assumptions, and ensuring everything actually worked. The bottleneck moved. It didn’t disappear. And that’s why I struggle with the claim that coding is solved. Perhaps code generation is becoming solved. Perhaps implementation is becoming increasingly automated. But software engineering has always been about much more than typing characters into an editor. It involves judgment. Tradeoffs. Domain expertise. System design. Risk management. Human communication. Institutional knowledge. And responsibility. None of those problems appear solved to me. The Next Rabbit Hole: Loop Engineering What’s particularly fascinating is that many of the engineers pushing Agentic AI furthest seem to be moving beyond prompting altogether. Boris Cherny has suggested that developers should stop prompting and start building loops. Peter Steinberger has made similar arguments. The idea is that autonomous agents should continuously generate, evaluate, and refine their own work. This concept is often referred to as Loop Engineering. I’ve spent time reading about it. Experimenting with it. Trying to understand it. And if I’m being honest, I still don’t entirely get it. What’s more frustrating is that concrete, end-to-end examples remain surprisingly rare. The discussions often feel abstract. Almost mystical. As if everyone has seen the future except the people trying to build software today. Maybe that’s because we’re still in the earliest stages of this transition. Or maybe we’re collectively mistaking experimentation for certainty. Either way, I’m not convinced we’ve arrived at the destination yet. My Current Conclusion Agentic AI is one of the most important technological developments of my career. It is already changing how software gets built. It will continue changing how software gets built. But from where I sit, coding does not look like a solved problem. It looks like a rapidly evolving one. And that’s actually far more interesting. For now, I’ll keep experimenting. I’ll keep learning. And I’ll keep trying to separate the genuine breakthroughs from the hype. Because if the future of software engineering really is being rewritten by AI agents, I’d like to understand what’s actually happening beneath the marketing slides. And if you’re curious too, you’re welcome to come along for the ride. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

  8. Jun 22

    Something Is Seriously Wrong With People?

    A few days ago, my wife received a credit card in the mail from a company we had never used. Apparently, someone had opened an account in her name. Naturally, I assumed identity theft and immediately called the credit card company to shut the account down and find out what information had been used to create it. After spending twenty minutes navigating an infuriating AI phone system, I finally reached a human being. Or at least, I think I did. The conversation felt strange. Every question I asked seemed to trigger a predetermined response. Every attempt to move the conversation in a logical direction was met with another scripted answer. It was as if the representative was following a flowchart that he could not deviate from under any circumstances. At one point I caught myself wondering whether I was talking to another AI. I wasn’t. It was clearly a real person. Yet somehow the interaction felt less human than many conversations I have had with chatbots. That experience stuck with me because it wasn’t an isolated incident. Lately, I have noticed a growing number of interactions that feel strangely mechanical. Not just in customer service. Not just online. Everywhere. People seem more scripted. More performative. More constrained. Almost as if they are operating from a limited set of dialogue options. Like NPCs in a video game. Now before anyone gets offended, I am not saying everyone behaves this way. I meet plenty of thoughtful, authentic people. But I encounter this phenomenon often enough that I can no longer ignore it. And it leaves me wondering: What exactly happened? The Corporate Mask That Never Comes Off I first noticed this trend while working in tech. Anyone who has spent time in a large corporation understands that some degree of performance is expected. We all wear masks at work. That part is normal. What felt different was seeing people become completely consumed by the performance. Simple ideas would be transformed into elaborate slide decks. Meetings would be scheduled to discuss future meetings. Entire conversations would revolve around appearing aligned rather than accomplishing anything meaningful. Everyone knew the ritual. Everyone participated. Nobody seemed willing to acknowledge the absurdity of it. What unsettled me was that for some people, the corporate persona appeared to become permanent. The mask never came off. The language, the mannerisms, the carefully calibrated responses followed them everywhere. Even outside of work. Conversations Feel Different Since being laid off, I have more opportunities to talk with people in everyday settings. Coffee shops. Parks. Neighborhood events. Random encounters. And what I have discovered is that many conversations feel surprisingly shallow. There is often a narrow range of approved topics. Food. Entertainment. Sports. Local events. Anything deeper can create immediate discomfort. Discussions about purpose, meaning, technology, society, mortality, economics, or the future often cause people to retreat. Not because they disagree. Because they seem exhausted. As if they simply do not have the mental bandwidth for the conversation. Perhaps that is the real issue. Not that people have become less intelligent. Not that people have become less caring. But that people have become overwhelmed. Theory One: We Are Overstimulated Think about how radically the environment has changed over the past twenty years. Most people now spend the majority of their waking lives connected to digital platforms. Their attention is continuously pulled in dozens of directions. Every notification competes for cognitive resources. Every algorithm is optimized to generate emotional reactions. Anger. Fear. Excitement. Outrage. Anxiety. The result is a constant state of sensory overload. When people are exhausted, authenticity becomes difficult. Deep conversations require energy. Curiosity requires energy. Human connection requires energy. And many people simply have none left. Theory Two: We Have Been Conditioned By Work Most Americans depend on employment to survive. That reality shapes behavior in powerful ways. Corporate environments reward predictability. They reward compliance. They reward process. They reward metrics. Over time, people learn to suppress parts of themselves that do not contribute directly to performance. Creativity becomes risky. Authenticity becomes risky. Spontaneity becomes risky. Eventually the performance becomes second nature. The script becomes internalized. And after years or decades of repetition, it becomes difficult to distinguish between the role and the person. Theory Three: Social Media Creates Behavioral Clones The early internet felt like exploration. You wandered. You discovered strange websites. You stumbled into unfamiliar ideas. The modern internet feels different. Algorithms decide what you see. Algorithms decide what you think about. Algorithms increasingly determine which personalities rise to prominence. Within every online community there are archetypes. The motivational guru. The productivity expert. The leadership philosopher. The lifestyle influencer. And many people unconsciously imitate these personas because they appear successful. Over time, entire communities begin speaking the same way. Thinking the same way. Reacting the same way. Not because they independently arrived at the same conclusions. But because they are all consuming the same inputs. Theory Four: The Meaning Crisis Perhaps the deepest explanation is that many people no longer know what they are living for. Traditional sources of meaning have weakened. Communities are fragmented. Institutions are less trusted. Consumerism often replaces purpose. Individualism often replaces belonging. The result is a quiet sense of disconnection. A feeling that life is somehow missing a center. When people lose connection to meaning, they often lose connection to themselves. And when that happens, everything starts to feel performative. Or Maybe It’s Just Me My wife has a much simpler explanation. She thinks people have not changed at all. She thinks I am getting older. According to her, I am viewing the past through nostalgia tinted glasses and imagining a level of authenticity that never actually existed. And honestly? She might be right. Memory is unreliable. Perspective changes with age. Perhaps twenty five year old me was simply less observant. Or perhaps middle aged me has become more cynical. I genuinely do not know. What I do know is that something feels different. Whether that difference exists in society or only inside my own perception remains an open question. So I will leave that question with you. Do people seem more authentic today? Less authentic? Have social media, corporate culture, and digital life fundamentally changed the way we interact? Or is this simply what getting older feels like? I would love to hear your thoughts. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

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This is a very public journal of anxiety, existential dread, and way too much tech knowledge. Basically therapy, but with Wi-Fi. asiandadenergy.substack.com

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