AsianDadEnergy's Substack Podcast

After 25 years in the tech industry, I never expected to be here—unemployed, months removed from Big Tech, and living what can only be described as an involuntary early retirement.And yet, something surprising happened.Despite losing a high income, my family of four is living comfortably on under $5,000 a month, in a high-cost area near New York City.Let that sink in.The Anatomy of a “Modest” but High-Quality LifeOur lifestyle isn’t extravagant, but it’s far from deprived. In fact, it’s quietly abundant.Here’s what that looks like:* Housing ($858/month): A fully paid-off home. No mortgage—just property tax and insurance.* Food ($800/month): Mostly home-cooked meals, organic groceries, minimal dining out.* Healthcare ($850/month): Comprehensive coverage through COBRA (soon transitioning to ACA).* Transportation ($396/month): Two fully owned, reliable vehicles, no car payments.* Utilities & Connectivity (~$360/month): Optimized and efficient.* Kids’ Activities ($300/month): A balanced mix of enrichment without overindulgence.* Lifestyle & Fun ($1,400/month): Streaming, travel, experiences, and yes… a bit of joy spending.Total: ~$5,000/monthThis supports a life with safe housing, quality food, good schools, healthcare, mobility, and meaningful family experiences.Not survival. Not luxury. But something better, sufficiency with intention.The Hidden Lever: Ownership Over ObligationTwo decisions quietly drive this entire equation:* Owning our home outright* Driving fully paid-off used carsRemove debt, and your cost of living collapses in a way most people never fully appreciate.A Thought Experiment: How Much Is “Enough”?Suppose that a family of 3 in a more typical, medium-cost area needed ~$3,300/month to live similarly to us, what would it take to sustain that?Using the widely known 4% rule, that translates to roughly:$1 million invested = financial independenceFor many, that number feels impossibly large.But here’s where things get interesting.The Tech Advantage No One Talks About EnoughIf you’re a software engineer, especially if you’ve worked in Big Tech, you’re playing a very different game.With high income and disciplined saving:* Saving ~50% of income + investing in index funds* You could reach $1M in ~9 years* In Big Tech? Potentially under 4 yearsRead that again.What takes decades for most can take years for you.Why This Matters Now More Than EverWe’re in an era of uncertainty: mass layoffs, shifting markets, and fragile job security.The old model, work hard, stay loyal, retire someday, is breaking.Relying solely on your paycheck is no longer a safe strategy.But building financial independence?That’s how you reclaim control.A Quiet RealizationThis journey started as a disruption. A layoff. An unwanted pause.But it revealed something deeper:A good life doesn’t require as much as we think.And freedom arrives much sooner than we expect, if we prepare for it.Final ThoughtIf you work in tech, you have an extraordinary, almost unfair advantage.Don’t waste it.Start building your portfolio.Not out of fear but out of clarity.Because one day, whether by choice or by circumstance, you may find yourself stepping away from work…And when that day comes, you’ll want options.Trust me, your future self will thank you. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

It’s been over 100 days since I was laid off from Big Tech after a 25+ year career in the tech industry. What followed wasn’t panic or fear, but something far more complex: a complete rewiring of how I think about work, identity, and purpose.The Shock of Losing More Than a JobAt first, the layoff felt surreal. There was a brief period of disorientation like a system crash without an error message. I applied to jobs almost reflexively, not out of desire, but habit. Work had become part of my identity, and without it, I was left asking uncomfortable questions:* Who am I without my job?* What was the point of all those late nights and sacrifices?Even without financial stress (thanks to years of saving and investing), I felt something unexpected: shame.The Hidden Mental Toll of Tech LayoffsScrolling through LinkedIn only made things worse. Everyone seemed to be thriving getting promoted, starting new roles while I felt left behind. It created a distorted reality where I was the only one “failing.”Reducing social media consumption became a turning point. Slowly, the shame faded. I began to see how much of my self-worth had been tied to external validation.Freedom Feels… StrangeWith time came an unfamiliar sensation: freedom. But freedom isn’t always comfortable.Without deadlines, pressure, and constant problem-solving, I experienced what I can only describe as stress withdrawal. The absence of challenge felt… empty.So I created my own.* Building side projects* Learning new skills* Creating content* Spending meaningful time with familyRedefining AccomplishmentIn Big Tech, solving high-stakes problems brought intense satisfaction. But it also made everything else feel insignificant.Now, that’s changing.Cooking a great meal for my family. Learning something new. Being present. These small wins are becoming meaningful again. My brain is recalibrating, like switching from junk food to something healthier, and finally appreciating the taste.Time Slows Down When You’re PresentOne surprising shift: time feels slower.Without autopilot work routines, every decision is intentional. Every moment is more present. It’s as if I’m experiencing more life within the same 24 hours.Is This a Better Life?There are clear downsides: loss of status, income, and prestige.But the upsides?* Autonomy over my time* Freedom to choose meaningful work* A deeper sense of fulfillmentFor the first time, I’m starting to wonder:What if this is actually better?If you’re navigating a tech layoff, questioning your career, or exploring early retirement, you’re not alone. This journey is messy, but it might just lead somewhere unexpectedly meaningful. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

It’s another week, another wave of layoffs, and once again the same question bubbles to the surface: who or what is really responsible?For many American software engineers, the H-1B visa program has become an easy target. A symbol of job insecurity. A quiet, persistent threat.But after 25 years in the industry, I’ve come to believe something more uncomfortable:The problem isn’t the people. It’s the system.A Lottery That Doesn’t Measure TalentOn paper, the H-1B program is elegant. It exists to fill genuine skill gaps bringing in top tier talent when local supply falls short.In practice, it behaves more like a lottery than a filter for excellence.Over the years, I’ve worked with H-1B engineers across the entire spectrum from world-class problem solvers to individuals who struggled with the basics. The variation wasn’t subtle. It was staggering.That alone should raise a red flag.If a program is designed to select top talent, outcomes shouldn’t feel random.When the System Incentivizes DeceptionI once led a project that required a specific technical skillset. We brought in a contractor through a staffing firm, it was an impeccable resume, flawless interview.Within weeks, it became clear something was wrong.No progress. No deliverables. Just delays wrapped in vague explanations.When pressed, the truth unraveled: the candidate didn’t have the skills listed. Not even close.This wasn’t just an individual failure. It was a structural one.A system that relies on proxies: resumes, outsourced interviews, middlemen, it creates fertile ground for misrepresentation. Not because everyone is dishonest, but because the incentives reward those who bend the truth just enough to get through the gate.The Other Side: Quiet ExploitationBut the darker reality isn’t fraud. It’s exploitation.I’ve worked with engineers who were brilliant, people operating far above their official titles, carrying projects, solving impossible problems under impossible timelines.And yet, they were underpaid. Overworked. Trapped.Why?Because their ability to stay in the country depended on their employer.That dependency changes everything.It turns negotiation into submission. It turns opportunity into leverage. It creates a class of workers who can’t easily say “no” and that dynamic doesn’t just harm them.It quietly resets expectations for everyone else.The Downward Pressure No One Talks AboutHere’s the part people feel but rarely articulate:When companies have access to workers who can be paid less, pushed harder, and retained through immigration dependency, the entire labor market shifts.Not overnight. Not explicitly.But steadily.Standards change. Expectations rise. Compensation softens.And suddenly, what used to be “unreasonable” becomes normal.A System That Benefits the Wrong PlayersIf you zoom out, the pattern becomes clear.The biggest winners aren’t engineers, American or H-1B.They’re the intermediaries. The staffing firms gaming the system. The corporations optimizing for cost and control. The actors who understand the loopholes and exploit them.Meanwhile:* Talented foreign engineers are constrained and exploited* Domestic engineers face increased pressure and competition* And the integrity of the hiring process erodesSo How Do We Fix It?There’s no silver bullet, but there are better incentives.1. Raise the Wage FloorIf companies were required to pay H-1B workers at the top of the market range, the calculus would change instantly.No more cost arbitrage. No more incentive to undercut.2. Audit AggressivelyNot symbolic enforcement but real oversight.Target high-volume sponsors. Investigate patterns. Penalize abuse.3. Replace the LotteryA random draw makes no sense for a high-skill program.Prioritize roles with real shortages and high wages. Let demand, not chance, drive allocation.4. Fast-Track Proven TalentFor truly exceptional engineers, remove the dependency trap.Grant mobility. Grant permanence. Let them compete freely.Because when talent is free, markets function better.The Hard TruthIt’s tempting to frame this as a conflict between American and foreign engineers.It isn’t.The real divide is between people doing the work and the systems that extract value from them.The best engineers I’ve worked with, regardless of where they came from, wanted the same things: to build, to grow, to be treated fairly.Right now, the system makes that harder than it should be.Final ThoughtIf we want a stronger, more resilient tech industry, we need to stop asking who to blame and start asking what to fix.Because until the incentives change, the outcomes won’t.And we’ll keep repeating the same cycle just with different names attached to it. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

I didn’t expect to find it in my home office, finishing up a quick side project. But there it was, a realization that hit harder than any production outage I’ve ever debugged:What used to take a startup, millions in funding, and months of work… now takes one person a few days.And that changes everything.The Assumption That Built an EmpireFor the past 30 years, our economy has quietly revolved around a single idea:Software is expensive.That assumption shaped everything:* Companies hired armies of engineers* Venture capital poured in by the billions* Entire industries formed around building and maintaining digital platformsFrom payment systems to ad networks to logistics platforms, software wasn’t just useful, it was scarce. And scarcity created power.That power turned a handful of tech companies into giants. It’s why so much of the market today is dominated by digital businesses. The moat was simple:If it’s expensive and slow to build, few can compete.AI Is Draining the MoatThen AI showed up.Not as true intelligence. Not as some omniscient brain.But as something far more disruptive:A force multiplier.Today, tools like Claude Opus allow small teams or even solo developers to:* Build faster* Ship cheaper* Replicate complex systemsWhat once required coordination across dozens of engineers can now be done by a handful of people… sometimes just one.The result?Software is no longer scarce.And when scarcity disappears, so does the moat.The Quiet Death of the InterfaceThere’s a second shift happening, and it’s even more subtle.For years, software companies made money by guiding human behavior through interfaces:* Search boxes* Dashboards* Funnels* Buttons and menusCompanies like Google and Meta built trillion-dollar ecosystems on this idea.But AI agents don’t need interfaces.They don’t click buttons.They don’t browse pages.They just… do the task.That means the value isn’t in the interface anymore. It’s in the execution.And if users stop interacting with software directly, entire business models start to unravel.Where Does the Value Go?If software is becoming cheap and invisible, the obvious question is:Where does the money go?The answer is surprisingly physical.In the AI-driven world, the bottleneck isn’t code.It’s compute.And compute isn’t abstract, it’s real, tangible, and expensive:* Data centers packed with GPUs* Advanced semiconductor manufacturing* Massive energy infrastructure* Global supply chains of rare materialsThis is where the new moats are forming.The New WinnersThe industries positioned to win aren’t purely digital. They live in the real world:* Data center construction and operations* Semiconductor fabrication* Networking infrastructure* Energy production and management* Materials like silicon, copper, and rare earth elementsAnd with them comes a different kind of workforce:* Electricians* Technicians* Engineers working with physical systemsIn a twist of history, the future of tech may look a lot less like code and a lot more like infrastructure.The Ones at RiskNot every company loses.The largest players, those who own the infrastructure, will likely adapt.But much of the software ecosystem built on top of expensive development?* SaaS platforms* Marketing tech stacks* CRM systems* Consumer appsThey’re facing a harsh reality:If anyone can build it faster and cheaper… it’s no longer defensible.A Shift Bigger Than SoftwareThis isn’t an overnight collapse. It’s a slow, grinding transition.But it’s already underway:From digital to physicalFrom software to computeFrom scarcity to abundanceAnd like every major shift, it creates both risk and opportunity.Final ThoughtStanding there, finishing that small project, I realized something unsettling—and oddly exciting:The industry I spent 25 years in is being rewritten in real time.Not by some distant future.But right now. Quietly. Efficiently. Inevitably.And for those paying attention?There are still fortunes to be made.Just not where everyone is currently looking. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

These days, in my unexpected post–Big Tech era, I spend a fair amount of time cooking for my family.There are worse fates.On this particular day, I was making stir-fried pork and turnips, which felt appropriate somehow: humble ingredients, a little heat, a little patience, and the faint possibility that if you look away for too long, everything burns. Which, now that I think about it, is also a decent summary of a lot of software projects.And as I cooked, I found myself remembering one of my favorite old tech war stories, the kind that only becomes funny once enough years have passed and everyone involved has either recovered emotionally or changed LinkedIn jobs three times.This one takes place in early 2010.The tech industry was still dragging itself out of the wreckage of the Great Financial Crisis, with all the grace of a hungover college student swearing off alcohol forever. I had just crawled out of one disastrous project at a digital consulting agency when, as a reward for surviving it, I was promptly assigned to another.The client was a major luxury car manufacturer. Let’s call them Clio.Clio wanted a beautiful new brand website powered by an enterprise CMS. The sales pitch was irresistible: non-technical staff would be able to create and publish content without relying on developers. Elegant. Efficient. Empowering. In theory.In practice, nobody on Clio’s internal IT team knew how to build a CMS-driven website at that scale. That gap, naturally, became our opportunity. Our agency sold them not just a delivery team, but also the comforting illusion that we would build it all together, shoulder to shoulder, on a schedule so aggressive it bordered on performance art.And this was no ordinary website.This was luxury automotive theater.Thousands of pages dedicated to convincing visitors that spending six figures on a two-ton block of steel, leather, and ambition would elevate them into some higher, sleeker form of human existence. You weren’t buying transportation. You were buying aura.At the center of it all was the vehicle configurator: the crown jewel of the experience. Prospective customers could choose paint, trim, interior finishes, accessories, and all the little details required to transform “car” into “my car.” That configuration data then had to be combined with inventory information and routed downstream to whichever dealership the customer selected, essentially generating a quote request wrapped in logistical reality.In other words, it wasn’t enough to build something pretty. It had to function across a fractured dealership ecosystem where every regional network behaved like its own independent kingdom. Clio’s corporate IT had no consolidated enterprise middleware layer, so every dealership group had its own way of handling quotes and inventory: some used SOAP APIs, some used plain old XML, and a few still clung to late-90s CORBA integrations like they were family heirlooms.Our site had to talk to all of them.That should have been warning enough.The TeamI joined as backend tech lead and quickly surveyed the battlefield.There was Tyrone, a senior backend developer. Brian, a junior backend developer. Sudarshan, an internal Clio backend developer, exhausted and hollow-eyed, with a three-month-old baby at home and the unmistakable expression of a man running on caffeine, responsibility, and dread. On the frontend side there was Andre, the lead, sharp, capable, and blessed with a gift for devastating sarcasm — along with Sarah, a junior frontend developer, and Jiten, Clio’s internal frontend developer. Our project manager, Jake, was relentlessly cheerful, which in retrospect may have been its own kind of survival mechanism.Above me sat Nigel, an enterprise architect with a thick working-class English accent and an admirably low tolerance for nonsense. Nigel reported to Alan, our technical director. Alan reported up to Haley, the account executive who managed the client relationship with an almost supernatural level of finesse.I liked Nigel immediately. He was one of those rare architects who actually wrote code, especially the difficult parts he designed himself. He gave blunt feedback, helped quickly, and somehow made every crisis sound both more severe and more manageable by narrating it in an accent that made the whole project feel like a Dickensian factory.“Right, lads, this is rubbish.”Music to my ears.Then there was Alan.Alan may have been the strongest pure engineer I have ever worked with. He was deeply fluent across frontend and backend systems, moved through technical problems with terrifying confidence, and showed up to work in beach shorts while drinking wine throughout the day. He was brilliant, hilarious, chaotic, and occasionally shocking in a way that would probably trigger at least three HR workflows in a modern corporate environment.At one point, while debugging a CORBA object hydration issue, he also found time to explain the logistics of juggling two girlfriends.A true systems thinker.Haley, meanwhile, was not technical, at least not in the conventional sense, but she possessed something arguably more powerful: an instinctive grasp of hierarchy, psychology, and influence. Watching her navigate conversations with client executives was like watching someone perform diplomatic sorcery. She could sense weak points in organizations the way experienced engineers sense flaky infrastructure. She always knew where the real power sat, where the insecurities were, and how to keep our agency embedded in the account.I respected both Haley and Alan enormously.They did not much care for each other.Which, naturally, added a little extra spice to the atmosphere.The Architecture from HellThen I learned what we were actually building.Clio had already purchased an enterprise CMS, let’s call it Portrait, before fully defining the project requirements. This is the kind of sentence that, if you’ve worked in enterprise tech long enough, causes your soul to quietly leave your body.Portrait, as it turned out, could only render web pages that looked like they had survived the 1990s by hiding in a filing cabinet. So instead of using the CMS to actually present finished web pages, content authors would enter data into Portrait’s grim administrative interface, essentially a joyless gray field factory and that content would then be published as massive XML feeds into a custom Spring MVC application we were building.Our application would parse the XML, transform it, and then generate the sleek modern website the client actually wanted.Which meant the CMS was functioning less as a publishing platform and more as a very expensive content mule.In retrospect, it was one of those architectures that technically works while spiritually insulting everyone involved.And then, on top of that already strange setup, we also had the vehicle configurator integrations to build.Naturally, we got to work.The Death March BeginsThe project escalated quickly.Within a matter of weeks, the vibe shifted from “challenging but manageable” to “everyone quietly lives here now.” We started doing long days. Then longer days. Then 12-hour weekdays. Then weekends. This was peak waterfall-era enterprise delivery, where every phase came attached to immovable dates and the preferred conflict resolution strategy was denial.The code completion deadline approached like a freight train.Then, about two weeks before it hit, the team began to fracture.By 2010, the tech job market was finally starting to recover. Developers had options again. Unfortunately, our company was still managing people as though it were 2009 and everyone should be grateful for fluorescent lighting and a paycheck.So one by one, people started leaving.First Tyrone landed a higher-paying role and exited. Then Jiten left Clio for something better. Nigel, our architect, departed for a new opportunity. Jake, our project manager, left the project just three days before the delivery deadline.And then, on the final day, Sarah came in visibly upset and told us she had learned she was being paid significantly less than other junior developers. She said she wasn’t in the mental state to work and went home.At that point, our team had been reduced to Alan, Andre, Brian, Sudarshan, and me.We were supposed to be code complete the next day.We were not remotely code complete.We needed at least another week.Instead, we had one night.Wings, Wine, and CollapseSo we did what doomed software teams have done since time immemorial: we convinced ourselves that force of will could substitute for time.We coded like maniacs.Code quality was no longer a meaningful concept. We were past elegance, past maintainability, past architecture. We were in the realm of tactical survival. The goal was not to build the right thing well. The goal was to get enough of the thing built that it could survive executive scrutiny for one meeting.That evening, Alan ordered a huge tray of wings and brought in several large bottles of wine.Nothing says “mission critical delivery” like poultry grease and alcohol.We ate, we drank, we coded.Sometime around 1 a.m., Sudarshan got a call from his wife. Their baby had a fever. He looked crushed and said he had to go home.Brian, our junior engineer, snapped.“How can you leave us hanging like this, man? It ain’t fair.”He was furious, truly furious, red-faced, exhausted, unraveling. For a brief moment it looked like the night might end in an actual fistfight between two backend developers in an enterprise web project, which would have been the most honest possible metaphor for the whole experience.I stepped between them, told Brian to calm down, and told Sudarshan to go home to his wife and child.He left.We kept coding.At some point, Brian either wandered off or passed out. I honestly don’t remember. He simply ceased to be part of the system.By 5 a.m., I hit my limit.My head was pounding. My eyes could no longer focus on the lines of code in Eclipse. Alan and Andre were still at it, debuggi

The other day, I was standing at a gas pump, watching the numbers climb beside my aging Honda CR-V, when something felt… off.Gas prices had jumped nearly 40% in a single week.That kind of movement doesn’t happen in a vacuum. It’s not random. It’s not seasonal. It’s a signal.And right now, that signal is pointing straight at a rapidly escalating conflict in the Persian Gulf.War as a Terrible InvestmentWar is often discussed in terms of strategy, power, or necessity. But strip all that away, and it reveals itself as something far more primitive:A high-stakes gamble with potentially unlimited downside.Unlike building a business or writing software, where failure is contained, war has no natural ceiling on loss. It consumes capital, infrastructure, and human lives at a scale that defies rational calculation.If you’re going to take on that kind of risk, the expected return had better be extraordinary.And yet, in this case, the objectives feel… unclear.Regime change? Weapons containment? Strategic deterrence? The goalposts seem to shift by the day. And when the purpose of a war is ambiguous, the cost becomes even harder to justify.It begins to resemble something less like strategy and more like compulsion.The Illusion of Overwhelming PowerOn paper, the United States is vastly more powerful than Iran: militarily, technologically, economically.But power, in modern conflict, is rarely symmetrical.Iran’s advantages are not about matching strength, they’re about exploiting imbalance.Geography, for one, is destiny. A vast, mountainous nation bordered by critical waterways is inherently difficult to invade and remarkably well-positioned to disrupt.Then there’s the Strait of Hormuz, a narrow chokepoint through which a significant portion of the world’s oil, fertilizer, and trade flows. When that artery tightens, the entire global system feels it.And then there’s the economics of warfare itself.Cheap, mass-produced drones, costing tens of thousands of dollars, can damage or destroy assets worth millions or even billions. It’s not just warfare. It’s arbitrage.When the cost of defense exceeds the cost of attack by orders of magnitude, the math stops working in your favor.Information and WillTechnology has also reshaped the battlefield in another critical way: information.Precise, real-time intelligence allows smaller actors to strike with disproportionate impact. A single well-timed attack can neutralize assets that took years to build.But beyond geography and technology, there is one factor that consistently outweighs all others:The will to fight.History has shown, time and again, that when a population feels existentially threatened, when loss becomes personal, immediate, and irreversible, their resolve hardens.And once that happens, wars stop being about objectives.They become about endurance.The Economic Fault Lines Beneath the SurfaceWhat makes this conflict particularly unsettling is not just the military dimension, it’s the economic fragility beneath it.Right now, much of the momentum in the U.S. economy is tied to a single narrative: the rise of artificial intelligence.Massive investments in data centers, chips, and infrastructure are propping up growth. Remove that, and the underlying picture becomes far less stable.This conflict threatens two critical pillars supporting that system:1. Investment FlowsOil-exporting nations in the Persian Gulf have historically recycled their revenues into U.S. assets especially tech. If those revenues are disrupted, so too is that flow of capital.2. Semiconductor Supply ChainsThe advanced chips powering AI are largely produced in East Asia, a region heavily dependent on energy flowing through the Persian Gulf. Disrupt that energy, and you risk disrupting the entire supply chain.The result?A localized conflict with the potential to trigger global economic consequences.The Shape of Unintended ConsequencesWars rarely unfold according to plan. They ripple outward, touching systems far removed from the original battlefield.Energy markets. Financial systems. Supply chains. Political stability.What begins as a regional conflict can, under the right conditions, become something much larger, something systemic.That’s the unsettling part.Not just the war itself, but the second-order effects. The quiet, compounding consequences that don’t make headlines until they’re impossible to ignore.Hoping for the Best, Preparing for the WorstStanding at that gas pump, watching prices surge, it was hard not to feel that something bigger was shifting beneath the surface.Maybe this resolves quickly. Maybe cooler heads prevail.But maybe it doesn’t.And if it doesn’t, the implications won’t be confined to a distant region or a single sector of the economy.They’ll show up in everyday places like the price you pay to fill up your car.Sometimes, the earliest signs of global change are also the most ordinary.You just have to know where to look. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello world.Not long ago, I was a senior software engineer in Big Tech, part of an industry that once felt like the unstoppable engine of the modern economy. For more than 25 years, my days were structured around product launches, sprint cycles, code reviews, and the comforting illusion that there would always be another project waiting on Monday morning.Then came an unexpected change in employment status.These days I describe myself, with only mild irony, as an involuntary early retiree.And like many people who suddenly find themselves outside the machinery of corporate life, I’ve been experimenting with a new challenge: how to structure a day that feels productive, meaningful, and only slightly like I’m turning into a house cat.The Morning RitualMy day begins early, as all respectable adults’ days do with a heroic march into the bathroom followed by fifteen minutes of doom scrolling on the toilet.Markets. Layoffs. Wars. The usual morning news.Eventually my legs fall asleep, which is nature’s way of telling me it’s time to brush my teeth and attempt to resemble a functioning member of society.Next comes coffee.Not just drinking coffee, staring deeply into coffee, waiting for the caffeine to reinstall my operating system.At some point, Leonard the cat appears demanding emotional support. His sister remains asleep somewhere in the house, contributing absolutely nothing to household productivity which, if we’re being honest, probably makes her the most successful member of the household right now.Exercise and Existential SunrisesAfter coffee comes thirty minutes of exercise: treadmill, weights, and the vague sense that unemployment is supposed to be the moment when one finally gets into the best shape of one’s life.Out the window, the sun rises.It’s beautiful, peaceful even.There’s something oddly comforting about a sunrise when you’re unemployed. It’s a quiet reminder that the universe is vast, ancient, and largely indifferent to your LinkedIn profile.The Morning ChaosSoon the house transitions into its daily brief but intense period of chaos.Kids running everywhere.My wife waking up.Cats weaving between legs like tiny furry assassins.But eventually we achieve the objective: children successfully delivered to school.With the house temporarily calm again, my wife and I sit down for breakfast while listening to the news, carefully calibrated information designed to keep us properly aligned with reality.The Professional Part of UnemploymentOnce nourished, I head to the computer to begin the day’s “work.”First, editing short videos for my vlog.Then writing essays for my newsletter where I attempt to sound wise about the tech industry despite having roughly the same information as everyone else.Next comes my daily Chinese reading practice. My goal is modest but ambitious: eventually reaching the literacy level of a motivated middle school student.After that, I respond to YouTube comments, which is important because the internet must always be answered.Lunch, Stir-FriedAround midday, I begin cooking.Today’s menu: pork and turnip stir-fry.Because nothing says “retired tech worker” quite like aggressively stir-frying pork at 11:45 in the morning.Lunch with my wife is honestly one of the highlights of the day: simple, quiet, and surprisingly satisfying.Afterward comes Coffee Number Two, which is critical for preventing my transformation into a fully non-functional daytime zombie.The Afternoon: Building SomethingIn the afternoon I usually get a couple of hours of focused time working on a mysterious and disruptive side project.In Silicon Valley language, this means:I’m building something that might make money… eventually.Some days I also do coaching sessions, which I genuinely enjoy. It’s nice talking to real humans instead of APIs, code repositories, and comment threads.Evening: The Second ShiftSoon enough, it’s time to pick up the kids.Dinner is chaotic again, but everyone is eating the food I cooked, which counts as a major victory.Later I help my son with homework, which mostly involves pretending I still remember algebra from the 1990s.Eventually homework is done, and I tuck my daughter into bed.These quiet moments, the ones that used to happen while I was still answering Slack messages now feel like unexpected gifts.The Sacred Night RitualFinally, the day ends with the sacred evening ritual:Consuming large amounts of completely mindless content on the internet.Strictly for research purposes, of course.And then, sleep.The Strange Gift of TimeSo that’s a typical day in my life.And honestly?Funemployment isn’t so bad.It’s slower. Less structured. Occasionally existential.But it also contains small moments that used to be invisible, sunrises, lunches with my wife, cooking in the middle of the day, helping with homework, putting my daughter to bed.In an industry obsessed with optimization, productivity, and constant growth, it’s easy to forget that life itself is not a sprint cycle.Sometimes it’s just a long day filled with coffee, cats, stir-fry, and the quiet possibility that something new might eventually emerge from all that free time.And if you’re curious to follow along on this strange little journey through tech, layoffs, side projects, and the occasional existential sunrise, you’re always welcome to join me. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello world.I’m an unemployed former Big Tech software engineer with 25 years in the technology industry. These days I joke that I’m in “involuntary early retirement.”One unexpected side effect of that situation is time, a lot more time with my kids.Recently, that time turned into a long and surprisingly heavy conversation with my teenage son.It started casually.It ended with a question that kept me awake most of the night.My son and his friends believe the future is going to be bad no matter what they do.So why bother trying?My First Reaction: AnnoyanceIf I’m honest, my first reaction wasn’t particularly noble.I felt irritated.My instinct was to tell him to toughen up, to get out there and compete, to fight for opportunities, to stop whining about hypothetical problems.In my mind I was thinking:You’ve been given so many advantages. Why wouldn’t you take them and run?And then something uncomfortable hit me.I had heard this tone before.It was my parents’.Becoming Your ParentsGrowing up, whenever I struggled with something in life, the reaction I often received was blame.If something went wrong, it meant I had been:* Entitled* Ungrateful* Lazy* A disappointmentEvery major decision I made as an adult was judged as some level of mistake.Even now, my layoff from Big Tech, something that happened amid mass industry layoffs is seen by them as my greatest personal failure.I love my parents.But I’ve always believed that style of parenting is deeply counterproductive.And in that moment I realized I was about to repeat it.So instead of lecturing my son, I asked him a simple question.“Why do you think the future is hopeless?”What he told me was… remarkable.Fear #1: There Won’t Be Enough Good JobsAccording to my son and his friends, the future job market looks bleak.They hear constantly from older siblings, from social media, from the news that:* AI will automate jobs* robots will replace workers* good careers will become scarceThe belief is that by the time they enter the workforce, the number of high-paying opportunities may collapse.Whether this turns out to be true or not, it’s not an irrational fear.We are entering a world where automation is accelerating.And young people are paying attention.Fear #2: The Cost of Living Will Crush ThemMy son also believes that basic necessities will become prohibitively expensive.Food.Rent.Transportation.Utilities.He joked that by the time he’s an adult, buying groceries might feel like a luxury purchase.During the conversation we both remembered the dystopian 1973 film Soylent Green.In that movie’s vision of the 2020s, a bag of groceries costs over $200.We laughed and then realized something uncomfortable.In some cities today, that joke isn’t far from reality.For many young adults earning median incomes, nearly every dollar they make goes toward simply existing.Saving feels impossible.Building wealth feels unrealistic.That’s not a fantasy dystopia.That’s already happening.Fear #3: The Monopoly Board Is Already FullThe next topic my son raised surprised me.Assets.He said joining adulthood today feels like joining a game of Monopoly when the game is already almost over.Every property is owned.Every asset is expensive.Real estate prices have risen so much that many young people believe homeownership may never be possible for them.Again, whether this perception is fully accurate isn’t the point.The point is that an entire generation believes the ladder is being pulled up behind them.And that belief shapes behavior.Fear #4: Institutions Can’t Be TrustedWhen I was a teenager in the 1990s, I had a very different view of institutions.In my mind, the United States government was something like a real-life version of Captain America.If a comet was about to hit Earth, surely America would lead the effort to save humanity.The president was someone to admire.Corporate leaders were role models.Today’s younger generation sees things very differently.Many of them view governments, corporations, and institutional leaders as fundamentally corrupt.The internet has exposed a tremendous amount of misconduct and hypocrisy among people in power.Perhaps those behaviors existed before, they were simply hidden.But today the transparency is relentless.And it has eroded trust in a way that may be permanently destabilizing.Fear #5: Dating Is BrokenThe last topic we talked about was relationships.According to my son, many young men feel completely invisible to young women.There are a few forces interacting here:* Traditional markers of success, income, status, career stability are becoming harder for young men to achieve.* Third places, physical social environments where young people naturally meet are disappearing.* Social media and dating apps create the perception of an endless supply of highly desirable partners.The result?A strange mismatch.Many young men feel unwanted.Many young women feel dissatisfied with their options.And both sides feel confused about why things aren’t working.It’s a complicated social puzzle with no easy fix.The Risk of a “Low-Desire Society”At the end of the conversation my son asked the central question again.“If the odds are stacked against us… why bother trying?”That question terrified me.Because an entire generation deciding not to try leads to something economists call a low-desire society.We can already see examples in parts of East Asia:* declining birth rates* declining ambition* declining economic dynamismYoung people stop competing.They stop dating.They stop having children.They stop dreaming.Eventually, the society begins to quietly collapse.That’s not a future I want for my kids.The Hard TruthThat night I barely slept.I kept turning these ideas over in my head.And the uncomfortable reality is this:There may not be a clean, systemic solution to these problems anytime soon.Fixing housing affordability, economic mobility, institutional trust, and social fragmentation would require massive changes to our entire socioeconomic system.But while we may not be able to fix the system overnight…We can help our children navigate it.What Parents Can Actually DoAfter thinking about it more, I came up with a few practical strategies parents can use to help their kids.1. Provide Emotional SupportTalk to your kids.Listen to their fears without immediately dismissing them.Let them know it’s normal to feel overwhelmed by the world.Resilience begins with feeling understood.2. Teach FrugalityConsumer culture trains people to spend constantly.Teach your kids that happiness doesn’t require endless consumption.Learning to live well on modest resources is a powerful advantage.3. Build Self-SufficiencyYoung adults should learn how to manage everyday life:* budgeting* responsibility* planning* managing obligationsThese skills build confidence and independence.4. Provide Strategic Financial SupportThe early years of adulthood are incredibly fragile.Helping with targeted support can make a massive difference:* allowing them to live at home temporarily* helping with education* contributing to a first home down paymentThe goal is not dependency.The goal is launch velocity.5. Model Healthy RelationshipsChildren learn about relationships primarily from watching their parents.Show them what respect, kindness, patience, and empathy look like.Demonstrate that meaningful partnerships are built on character, not just status or superficial traits.Apps like Tinder may filter potential matches, but they cannot teach someone what a healthy relationship actually looks like.Parents can.A Generation That Must Not Give UpMy son’s concerns are real.They reflect the anxieties of many young people today.But an entire generation giving up cannot be an option.Every generation faces its own storms.The job of parents is not to pretend those storms don’t exist.It’s to help our children learn how to sail through them.And maybe, just maybe, build something better on the other side. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Many years ago, I was a mid-level developer at a consulting company. I remember staring up at the org chart and wondering how people became architects, then senior architects, then technical directors. It felt mysterious. Political. Reserved for the chosen few.And yet, over roughly six years, I climbed that ladder:Developer → Architect → Senior Architect → Tech Director.At the time, it felt brutal.In hindsight, it was almost straightforward.The uncomfortable truth? The path that worked for me may no longer be enough today.Let me explain.The Old PlaybookWhen I was a mid-level engineer, I did three things obsessively:* I volunteered for very hard projects.* I sought out strong mentors.* I pushed myself into system design work.That was it.1. Volunteer for the DeathmarchOne of those projects was an enterprise service bus middleware component for a massive publishing company, let’s call it Big Corp.It was a nightmare.Months of weekend work. Endless integration problems. And on go-live night, an open-source bug nearly broke me. I remember standing in the parking lot after midnight, overwhelmed, exhausted, and crying in my car.It was ugly.But I shipped.And when you survive something like that, two things happen:* Your technical depth sharpens dramatically.* Leadership notices.Hard projects compress experience. They force you to grow up fast.2. Find Mentors (Even If It Feels Awkward)I actively sought mentorship from senior technical leaders.At first, mentorship can feel transactional. Almost burdensome to the mentor. But over time, something shifts. If you show initiative and deliver results, many mentors start to care. They feel invested.One of mine, let’s call him Heinz, was a seasoned tech director. He taught me small tactical things (like why knowing sed and awk gives you borderline superpowers) and big strategic things (like why system design is the real career unlock).Mentors don’t just give advice.They give visibility.They give sponsorship.When promotion cycles came around, some of the people advocating for me were former mentors.That matters more than people admit.3. Move From Coding to DesigningThe biggest inflection point in my career wasn’t learning another framework.It was system design.System design is fundamentally different from implementing user stories. It’s about defining modules, boundaries, data flows, tradeoffs, scalability constraints, the blueprint before the building.When you do system design:* You sharpen architectural thinking.* You gain cross-team visibility.* You operate at a higher altitude.By the time promotions came, I had:* Credibility from delivering painful projects.* Visibility from leading system designs.* Advocacy from mentors invested in my growth.That combination moved the needle. Repeatedly.Why That Path Is Harder NowOver the years, I’ve mentored many mid-level engineers.And recently I’ve come to a sobering realization:The journey I took is significantly easier than the one mid-level engineers face today.Today’s environment looks like this:* Saturated job markets.* Wave after wave of layoffs.* Leadership pressure to “do more with less.”* AI amplifying productivity expectations.* Constant fear of replacement.The things that once propelled me upward: volunteering for hard work, gaining visibility, expanding scope are now table stakes just to survive.That changes the game.So what can a mid-career, mid-level engineer realistically do right now?Not magical strategies. Not silver bullets.Coping strategies.Time-buying strategies.Because even one or two extra years of employment can mean:* More savings.* More investments.* Greater optionality.* More leverage over your own life.Strategy #1: Build a T-Shaped Skill SetSpecialization used to be a moat.If you knew COBOL, banks would keep you forever.That moat is shrinking.AI tools can now generate competent code across obscure stacks. The defensibility of narrow expertise is eroding.Instead, build a T-shaped profile:* Deep expertise in one core stack (your vertical bar).* Broad exposure to adjacent domains (your horizontal bar).For example:* Go full-stack instead of only front-end.* Learn data engineering or QA.* Understand product management.* Gain exposure to UX and design thinking.Small teams of versatile engineers are now building what once required multiple departments.The disruptors are compact.You want to be on that side of the equation.Strategy #2: Use AI as a Force Multiplier (If You’re Mid-Level)Here’s an interesting dynamic.AI tools like Claude Code are not productivity-equalizers.They disproportionately benefit experienced mid-level engineers.Why?* Junior engineers lack the depth to detect hallucinations, subtle bugs, security issues, or scalability flaws.* Some senior leaders have let their hands-on skills atrophy.Mid-level engineers who are still deeply technical, and still actively coding, are uniquely positioned to 10x their output.This window may not last forever.But right now? It’s leverage.Use it.Strategy #3: Master the Delegation DecisionAI is not a machine god.It automates a large chunk of software work, but not all of it.Your competitive advantage becomes knowing:* When to fully delegate.* When to collaborate iteratively.* When to do it yourself.Ask three questions:* How long does it take me to do this manually?* How long does it take AI?* How likely is AI to get it right?If AI can generate a well-documented module quickly and safely? Delegate.If requirements are fuzzy and need iterative shaping? Collaborate.If business context is subtle, political, or risky? Do it yourself.Finding that boundary is a superpower.Strategy #4: Develop Deep Domain ContextAI is strong at generalizable coding tasks.It is weaker where domain context lives in messy, semi-analog reality:* Tribal knowledge.* Undocumented workflows.* Historical business constraints.* Political tradeoffs.Mid-level engineers can carve out near-term defensibility by embedding themselves deeply in domain knowledge.Become the person who understands not just the system but why it exists.That context is not easily scraped and trained on.Strategy #5: Learn to Tell the StoryThis one hurts to admit.In the AI era, raw information and logic are commoditizing.For engineers, that’s a body blow.But synthesis and storytelling remain leverage.If you can:* Frame tradeoffs clearly.* Translate technical decisions into business narratives.* Connect architecture to revenue impact.* Turn scattered data into a coherent strategy…You influence:* Scope.* Budget.* Roadmaps.* Headcount.Storytelling moves resources.Resources move careers.The RealityWe are living through instability.Small teams are replacing large ones.AI tools are raising expectations.Career ladders feel less predictable.The old playbook still works, but it’s no longer sufficient on its own.Today, mid-level engineers must:* Be versatile.* Be AI-literate.* Be strategically aware.* Be narratively strong.It’s harder.But not hopeless.If you’re in the middle of your career and feeling squeezed from both sides by hungry juniors and cost-cutting leadership, you’re not imagining it.The pressure is real.The environment has changed.But so have the tools at your disposal.Use them wisely.And buy yourself time.Sometimes survival and compounding is the most underrated career strategy of all. 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Hello world.I’m an unemployed ex–Big Tech software engineer with 25+ years in the trenches of the software industry. I’ve ridden the dot-com bubble, offshoring waves, mobile revolutions, cloud migrations, and whatever we’re calling the post-pandemic tech reckoning.And now? I’m watching the AI gold rush from the outside.Depending on which headline you read this morning, artificial intelligence is either:* An economically unsustainable hype machine* A glorified autocomplete that can’t boost productivity* Or the final exponential surge before Artificial General Intelligence automates every white-collar job in the next 12–18 monthsSo which is it?Is AI just a “probabilistic parrot” repeating patterns from the internet? Or is something structurally different happening this time?Let’s walk through what’s actually changed over the past five years in plain English.Phase 1: The Giant AutocompleteEarly large language models like OpenAI’s GPT-3 were, at their core, probability machines.You type:“Mary had a little…”It predicts:“lamb.”Not because it understands nursery rhymes. Not because it has memories. But because “lamb” statistically follows that phrase in its training data.That training data? A massive scrape of publicly available internet text.Impressive? Yes.Intelligent? Not really.On its own, this was more a clever toy than economic earthquake.Phase 2: Teaching the Parrot MannersThe next breakthrough was supervised fine-tuning.Humans created tens of thousands of carefully written question-and-answer examples. The model was retrained on these, nudging it toward responses that felt helpful, structured, and safe.This is how the first version of ChatGPT launched in 2022.It was better. But still limited.The bottleneck? Humans are expensive. Slow. Finite.So AI researchers did what engineers always do when constrained by humans: they automated the humans.Phase 3: Reinforcement Learning at ScaleInstead of having humans generate both questions and answers, the model could now generate answers while human experts simply judged them as good or bad.Good answer? Increase the probability of similar responses.Bad answer? Penalize it.This is reinforcement learning.But even that eventually hits scale limits.So researchers trained AI models to become evaluators learning from human feedback and then taking over the judging process. Now AI models could train future AI models.And once humans are mostly out of the loop?You can scale to absurd levels.Millions. Billions. Trillions of generated tasks.Evaluated in weeks using massive data centers.Still probability math.But at industrial scale.Phase 4: Chain-of-Thought — The “Reasoning” IllusionThen came reasoning models.Instead of predicting a single answer to:“If you have 8 pizza slices and eat 3, how many remain?”The model breaks the problem into steps.8 slices.Minus 3 eaten.Equals 5 left.This “chain-of-thought” decomposition dramatically improves accuracy. Not because the AI understands pizza but because smaller probability jumps are easier than giant ones.It’s still math.Just math with better scaffolding.Phase 5: Tools — From Talking to DoingThis is where things get serious.Language models began calling tools.Need the current temperature? Call a weather API.Need to write to a file? Call a document function.Need to push code to a repository? Trigger a Git action.Models like Gemini, Claude, and modern ChatGPT versions now interact with external systems.This transforms AI from:Answer machine → Action machine.And action is where jobs live.Phase 6: Re-Act Architecture Thought, Act, ObserveComplex work isn’t one step. It’s dozens. Hundreds.The “Reason + Act” (ReAct) pattern works like this:* Think through a plan.* Execute one step using a tool.* Observe the result.* Update context.* Repeat until done.This loop enables multi-step cognitive labor.But there’s a catch: memory.AI models have context windows, short-term memory buffers. Overload them, and they hallucinate or forget key constraints.Enter the next hack.Phase 7: Agentic Frameworks — The Harness Around the BrainAgent systems wrap AI models in orchestration layers.Think of it as:* A planner agent* Worker sub-agents* A QA agent* External databases storing long-term contextEach agent only sees what it needs.One plans the website.Another writes code.Another tests it.Some systems even simulate 24/7 “proactive” assistants using timed loops that periodically re-prompt the model — giving the illusion of autonomy.Is it consciousness? No.It’s math wrapped in for-loops.But here’s the uncomfortable part:It works.Are We Near AGI?No.There is no understanding. No awareness. No inner life. No self.We are not at the singularity.But that doesn’t mean we’re safe.The Productivity QuestionRecent industry studies suggest frontier models like ChatGPT 5.2 and Claude 4.6 can sustain deep, complex cognitive work for over an hour with success rates exceeding 80%.For context:The average white-collar worker can maintain true deep focus for 60–90 minutes at a time.Across an entire day? Maybe 2–3 hours of real high-quality output.If AI focus time doubles every six months, as some data suggests, we may soon see models capable of four-hour sustained cognitive blocks.And they don’t need sleep.Or weekends.Or health insurance.So… Will AI Replace White-Collar Jobs?Here’s the honest answer:Any job that consists primarily of interacting with a computer interface is at risk.* Software engineering* Accounting* Legal research* Financial analysis* Marketing copy* Project management* OperationsAI models are being fine-tuned for each of these domains right now.We are not watching a toy evolve.We are watching a new kind of digital labor force scale geometrically.The ParadoxAI is still “just” probability.It doesn’t understand.It doesn’t reason in the human sense.And yet through scale, reinforcement learning, tool use, reasoning scaffolds, and Agentic orchestration, it can now perform long-duration cognitive work that looks remarkably similar to what many professionals do daily.That’s the tension of this moment.It’s not conscious.But it’s competent.Something Big Is HappeningAs someone who’s spent 25 years in software, and who is currently unemployed, I don’t have the luxury of dismissing this as hype.I’ve seen enough technology waves to recognize when the ground is actually shifting.This one feels different.Not because machines woke up.But because the scaffolding around them did.If you’re watching this space with a mix of curiosity and existential dread, you’re not alone.We’re all trying to figure out what comes next.And whether we’ll be coding it…Or competing with it. 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Hello world.After more than 25 years in the software industry, and an unexpected exit from Big Tech, I found myself in an unfamiliar situation: time. Lots of it. The kind of time engineers rarely have, the kind that invites curiosity, experimentation, and occasionally, questionable ideas.This is the story of one such idea.A Simple (and Slightly Dangerous) Thought ExperimentWhat if you could build a system that:* Discovered profitable market niches automatically* Generated digital wall art tailored to those niches* Published the results directly to online marketplaces* And quietly earned income in the backgroundIn other words: could software design, create, and sell creative products without human involvement?It sounded like the perfect retirement-side experiment—equal parts engineering challenge and philosophical mischief.Designing With an AI Co-ArchitectTo move from idea to implementation, I worked alongside OpenAI’s ChatGPT-5, using it less like a tool and more like a collaborator.The planning phase felt like an architectural dialogue:* The AI proposed system designs* I interrogated assumptions* We refined constraints together* Repeat… until the structure made senseIt didn’t feel like architecting. It felt like conducting an orchestra, one where every musician already knew every instrument ever invented.At times, it was like whispering into the ear of a sleeping leviathan.The Architecture: Automation All the Way DownThe final system ran as an automated workflow in n8n, orchestrating a sequence of Node.js tasks:* Identify promising keywords* Analyze successful products* Generate new creative concepts* Produce artwork using generative models* Build marketing assets* Syndicate listings through PrintifyFor the initial MVP, distribution targeted Etsy and Amazon.From there, I generated a full Product Requirements Document using AI and handed implementation to a coding agent powered by Anthropic’s Claude Haiku model.Then I did something that would have been unthinkable earlier in my career.I went for coffee.When I came back, most of the system was written.The Surreal New Development LoopMy role shifted dramatically:* Review AI-generated code* Run integration tests* Fix edge cases* DeployNo sprint planning.No backlog grooming.No weeks of incremental implementation.By the end of Day One, the pipeline was live in my home cloud.Naturally, I assumed I had built a fully automated passive-income machine.Naturally, I was wrong.Reality: The Humans Are Still NeededThe very first production run exposed the messy parts of the real world.1. AI Image ImperfectionsRoughly 1 in 15 generated images contained subtle visual defects, things only a human eye could catch. There is still no reliable automated test for “this looks weird.”2. Intellectual Property LandminesSome outputs drifted dangerously close to recognizable styles or copyrighted material. Text can be screened. Visual similarity? Much harder.3. Marketplace Integration ChaosThe Print-on-Demand pipeline was far from seamless:* Listings failed unpredictably* Variants split into separate products* Metadata required manual correctionInstead of passive income, I found myself babysitting automation.After a full day of supervision, I had published about 100 products.Automation, it turns out, still needs adult supervision.The Moment of Existential DebuggingBy Day Two, I stepped back and asked a different kind of question:Was this even a good idea?If perfectly automated, the system could flood marketplaces with thousands of derivative works. But that doesn’t create new value, it just redistributes attention within an existing market.In economic terms, it wasn’t innovation.It was acceleration without direction.And that led to one of the great luxuries of early retirement:If you’re working on something pointless, you can just stop.So I walked away.The Twist: It Made Money AnywayA month later, curiosity got the better of me. I checked the accounts.Those ~200 listings I had published before quitting?They had quietly generated revenue:* About $600 on Etsy* Around $70 on AmazonAfter costs, fees, and fulfillment, the profit was roughly $200.Not life-changing.But not zero either.An abandoned experiment had paid for a nice dinner and perhaps a bottle of soju.What This Experiment Really Taught MeThis project wasn’t about wall art. It was about understanding how AI is reshaping the act of building.We are entering a phase where:* Designing systems may matter more than coding them* Iteration happens conversationally, not procedurally* Engineers supervise intelligence rather than implement logic* The bottleneck is no longer syntax, it’s judgmentAI can build astonishing things quickly.But deciding what is worth building remains stubbornly human.What’s Next?There are far more interesting problems to explore than teaching machines to sell wall décor. So I’ve moved on to projects that feel less like automation experiments and more like genuine discovery.Still, this strange little system remains one of the most educational things I’ve built.Not because it succeeded.But because it showed me where the real questions now live.If you enjoy thoughtful experiments at the intersection of software, AI, and life after Big Tech, feel free to follow along. There’s plenty more tinkering ahead. 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Hello world.After more than twenty-five years in the software industry, I now find myself in an unfamiliar position: an ex–Big Tech engineer with time to think. And when you suddenly have time, real, unstructured time, you start asking questions that never quite fit into sprint planning or quarterly OKRs. Questions about where all of this is going. About what kind of civilization we may be constructing, almost accidentally, through code, platforms, and incentives.One possible answer is something historians would recognize immediately, even if we insist on calling it innovation: techno-feudalism.A System That Refuses to Stay in the PastTo understand the idea, it helps to revisit classical feudalism—not as a medieval curiosity, but as one of the most stable socioeconomic systems humanity has ever produced. For centuries across Eurasia, feudal societies organized themselves around a simple structure:* A vast majority, over 90%, were serfs, bound to land they did not own.* A narrow middle layer, perhaps 5–10%, were specialists, tradespeople, clergy, or small landholders.* At the very top sat the lords, fewer than 1%, who owned nearly everything.Serfs possessed little beyond their labor. Land, tools, housing, and even access to basic resources were controlled by their lords and leased back in exchange for rent, often paid through work rather than money. Social mobility was rare, ownership rarer still.The system was extractive, unequal, and often brutal. Yet it was astonishingly resilient. Feudalism endured not because it was just, but because it was economically self-reinforcing.How Feudal Systems Sustained ThemselvesWhen productivity plateaued or populations grew too large, lords adapted through three recurring strategies:* Expansion – acquiring new land or resources to maintain surplus value.* Monetization – leasing labor elsewhere, converting obligation into currency.* Control of Dependency – ensuring those at the bottom remained structurally tied to the system.Feudalism did not collapse on its own. It weakened only when demographic shocks, wars, and new frontiers shifted bargaining power back toward labor. Scarcity of workers forced change.In other words, feudalism ended when people once again became economically valuable.The Digital Echo of an Old OrderNow consider the present.Today, ownership of infrastructure, platforms, and capital is increasingly concentrated. Many people do not own their homes outright, their transportation, or even the software tools required to function professionally. Instead, they subscribe. Monthly payments replace property. Access replaces ownership.Housing is rented. Software is licensed. Entertainment is streamed. Mobility is leased. Even productivity increasingly depends on platforms we do not control.This is not medieval agriculture. But structurally, it rhymes.A small group builds and owns the digital “land.” A technical middle class maintains it. The majority participates through continuous payment for access.The Accelerant: Automation of Cognitive LaborArtificial intelligence introduces a new dynamic. Unlike past mechanization, which primarily displaced physical labor, modern systems can perform economically useful cognitive tasks, analysis, generation, coordination at dramatically lower cost.If large segments of human work lose scarcity, the historical mechanism that dismantled feudal systems, valuable labor, may not reappear this time.Without surplus income, fewer people accumulate capital. Without capital, ownership concentrates further. Dependency deepens, even if living standards remain materially adequate.A society can become comfortable and constrained at the same time.A Narrow Path ForwardThis trajectory is not inevitable. History never repeats exactly. But it often presents familiar shapes under new names.We may be approaching a fork between two futures:* One leads toward a highly centralized, subscription-mediated existence: efficient, stable, and quietly stratified.* The other toward a world where technological abundance broadens ownership rather than concentrates it.The difference will not be determined by technology alone, but by how societies choose to distribute its gains.Somewhere between dystopia and utopia lies a narrow path. Whether we recognize it and choose to walk it remains an open question.For now, with time to think, it is a question worth asking. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello, World.I’m an unemployed, ex–Big Tech software engineer with 25 years in the industry.That sentence would have terrified me a decade ago. Today, it feels strangely calm.We’re living through another brutal cycle of tech layoffs. Thousands of engineers: smart, capable people are refreshing LinkedIn feeds and grinding through interviews that feel increasingly like Squid Game with better lighting. Many are hurting. Some are in real financial distress.By a combination of discipline, luck, and a few painful lessons, I’m not.I’m financially independent, though not in the glamorous influencer sense. It’s more like involuntary early retirement. I’m not drawing a paycheck, but our living expenses are covered by returns from a pool of investments built slowly over time. It is an enormous privilege, and I don’t take it lightly.What follows is not advice. I’m not a financial advisor. I’m simply a middle-aged engineer showing his work, the wins, the mistakes, the weird detours and how they compounded into stability.Index Funds: The Boring BackboneIn 2008, during the wreckage of the financial crisis, I fell down a personal finance rabbit hole. Your Money or Your Life shifted my thinking. John Bogle’s The Little Book of Common Sense Investing sealed it.The idea was simple: buy low-cost index funds that mirror the broader market, like the S&P 500, and let time do the heavy lifting. Most active managers fail to beat the market long term. If professionals with teams of analysts struggle, what chance did I have after a day of debugging Java?So in early 2009, while markets were still bruised, I began investing heavily in S&P 500 index funds with a smaller allocation to total market bond funds, roughly 90/10.Funding came from:* 401(k) contributions (eventually raised to 8%)* Employer matching (free money, always take it)* Post-tax brokerage investments, which ramped up after we paid off student loansI also funneled nearly every cash bonus into index funds.Starting in 2009 was luck. The S&P 500 was near historic lows. Over 17 years, those funds averaged roughly 13% annually. Exponential compounding quietly made index funds our largest asset class. Today, the dividends from our taxable accounts form a meaningful portion of our income.Boring worked.Real Estate: Tangible WealthMy father never trusted fiat currency. He believed real wealth is something you can touch.So we bought it.We own our primary residence and two rental properties, all mortgage free. We purchased during the softer post-crisis 2010s and paid them off through aggressive saving.Some argue a primary home isn’t an investment. I see it as capital that appreciates and reduces our housing cost dramatically compared to renting. The rentals, modest homes within commuting distance of major cities, produce consistent income.Property values have grown around 7% annually. Rental yields run 7–8% per year for us. Combined, real estate is our second-largest asset class and a powerful stabilizer.The Side Hustle That Should Have Been SoldIn 2010, I built Android apps to pay off debt. It was the Wild West. Multiple app stores. Low competition. In 2011, I cleared over $100,000.Then the gold rush ended.Competition intensified. Earnings halved in 2012. A buyer offered $53,000 for the entire business. I declined, insulted.I should have taken it.By 2013, new apps earned less and less. Eventually I stopped building. The old apps trickled income for a decade until Google deprecated the SDK and delisted them in 2023.Over ten years, the passive income didn’t even reach half the buyout offer.Lesson: Know when the peak is behind you.HYSA: Sleep InsuranceA high-yield savings account isn’t exciting. It’s insurance.We built it from three months of expenses to one year as layoffs at work intensified. After my lay off, the severance added another year. At 3.75%, FDIC-insured, it’s less about growth and more about peace.Peace compounds too.Big Tech Stock: Concentration RiskJoining Big Tech 7 years ago brought RSUs and an ESPP program with a 15% discount, effectively instant upside.When shares vested in 2020, pandemic growth sent the stock soaring. I held. From 2020–2024, it averaged roughly 22% annual growth for me.But concentrated positions make me nervous. I’ve been gradually converting shares into diversified index funds to manage capital gains taxes.Concentration builds wealth. Diversification keeps it.Precious Metals: Hedge or Warning Sign?A doomer friend convinced me in 2009 to buy silver. I did, modestly, consistently, every Christmas.Silver averaged roughly 12% annual growth over that period.Precious metals produce no cash flow. They simply sit there, shiny and indifferent. Whether that performance represents savvy hedging or currency erosion is an uncomfortable question.FOMO Stocks: Tuition PaidIn 2014, I invested $20,000 into hype-driven “visionary” tech stocks.Two years later: $7,000 gone. Roughly –17% annually.That was my tuition for ignoring fundamentals.Soviet Ammo: The Accidental AssetAs a teenager, I bought surplus Cold War ammunition for pennies per round.It sat in a basement for decades.Two years ago, I sold one can for $700.Roughly 10% annualized growth. The market is strange.Crypto: The Best Return I Don’t UnderstandIn 2017, skeptical but curious, I mined a small amount of Monero on an old laptop. It earned $17 and destroyed a CPU fan.I converted it to Bitcoin and forgot about it.Today, it’s worth around $200, about 27% annualized growth.It’s my best-performing asset.I still don’t understand it.The Big PictureWe made mistakes. Missed peaks. Held too long. Sold too soon. Chased hype. Ignored offers. Got lucky.But over 17 years, consistent investing in productive assets, especially low-cost index funds and real estate, did most of the heavy lifting.Financial independence wasn’t achieved through genius. It was built through:* High savings rate* Boring diversification* Employer benefits* Controlled lifestyle inflation* And a lot of timeIn uncertain times, stability is a gift.If you’re navigating layoffs, know this: markets move in cycles. Careers do too. The key isn’t predicting the future, it’s surviving long enough for compounding to matter.If you’re curious to follow this ongoing experiment in middle-aged reinvention, engineering, investing, existential reflection, I write monthly and share updates.Thanks for reading.Until next time. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello world.I’m an unemployed, ex–Big Tech engineer with twenty-five years in the software and technology industry. That sentence alone would have felt impossible not long ago. And yet here we are, living through another wave of mass layoffs across American tech an era where résumés pile up, inboxes stay silent, and explanations are reduced to slogans.One of the most common refrains I hear is simple: it’s offshoring.Now that I have time, an abundance of it, I’ve been sitting with that claim, turning it over carefully instead of reacting to it emotionally. What follows isn’t a hot take. It’s a reflection shaped by decades inside the system.Offshoring Comes in WavesOffshoring in tech doesn’t happen all at once. It arrives in waves, each with a peak of enthusiasm and a valley of regret.I entered my career during one such peak in the early 2000s, when companies aggressively shifted software development to lower-cost countries. In my experience, that almost always meant India. The logic was straightforward: software was expensive to build in the U.S., talent was plentiful elsewhere, and code was code. Or so we told ourselves.As a consultant in the years that followed, I found myself working inside the aftermath of that decision. The codebases left behind were often catastrophic, vast jungles of copy-and-paste spaghetti code, barely documented, impossible to extend, and riddled with bugs. Many applications limped along, more fragile than functional.Worse, when issues arose, it often felt as though the offshore teams supporting the systems didn’t truly understand the code they were maintaining or perhaps had never been given the space or incentive to care deeply about it.By the mid-to-late 2000s, the pendulum swung back. Companies slowed or halted offshoring efforts and brought work onshore again, quietly acknowledging that cheap code can become very expensive over time.Why Was the Code So Bad?This question haunted me early in my career. Mathematics doesn’t change by country. Engineers don’t become less intelligent when they cross borders. In theory, software quality should be roughly equivalent everywhere.Over time, I realized the issue wasn’t intelligence. It was friction.Time ZonesTeams separated by half a world rarely overlap meaningfully. Collaboration collapses into tickets and emails. Context gets lost. Nuance disappears. Projects devolve into a “throw it over the fence” workflow with each side doing its piece in isolation, hoping the other can make sense of it later.LanguageEven when offshore engineers speak excellent English, subtlety often doesn’t survive translation. Requirements lose precision. Assumptions go unchallenged. And sometimes, asking the right question feels harder than simply saying yes.CultureIn more hierarchical cultures, junior engineers may be discouraged, explicitly or implicitly, from speaking up. Problems get noticed but not surfaced. Uncertainty is masked as confidence. Work proceeds anyway, and the consequences appear downstream, where they are far more expensive.None of this reflects a lack of talent. It reflects systems that punish curiosity and reward silence.The Pendulum Swings AgainBy the mid-2010s, offshoring returned, this time with more sophistication.In 2015, I worked on a large enterprise re-platforming project for an automotive client. There, I met an offshore architect, let’s call him Abby, based in Gurugram, outside Delhi.I was wary at first. Experience had trained me to be. But Abby quickly dismantled my assumptions.He was brilliant. Deeply knowledgeable. Tireless. He understood the platform better than I did, despite technically reporting to me. To maximize overlap with U.S. teams, he worked until 10 or 11 p.m. his time, every weekday. Eventually, U.S. management began to expect this level of sacrifice from everyone offshore.Abby was paid roughly one-sixth of my salary.And yet, his cost of living was nowhere near as low as I had imagined. Cars, utilities, food, nearly U.S. prices. Housing near the office was so unaffordable that his family lived hours away. During the week, he shared a tiny apartment with coworkers. He saw his wife and child only on weekends.He worked weekends too.He told me about suffocating smog, brutal heat waves, floods, wild dogs, and constant environmental stress. I didn’t fully believe him, until years later, when I visited the same area myself and saw it firsthand.Once, during a dengue fever outbreak, I watched fear consume him as he worried about his child’s safety.And yet, he considered himself lucky.Unequal TermsAbby and I were men of equal worth. Of comparable skill. Of shared pride in our craft.But we competed on profoundly unequal terms.Over my career, I’ve worked with offshore engineers across India, Latin America, China, and Eastern Europe. Many are my friends. All are trying to provide for their families, no differently than American engineers.In the last decade, many of the old barriers have fallen. Collaboration tools improved. Companies built parallel offices abroad. Offshore engineering quality rose dramatically. Today, many offshore engineers are true peers to their U.S. counterparts.Which brings us to the uncomfortable truth.The Real IncentiveOffshoring was never about quality.It was and remains about cost.Offshore engineers are still significantly cheaper than U.S. engineers. Unless something drastic changes, offshoring will continue and likely accelerate.I’ve thought hard about what could stop it.Regulation can protect certain sectors, but it raises costs and slows innovation. Poaching elite offshore talent strengthens companies but worsens competition for domestic workers. Tariffs invite retaliation and risk splintering global tech ecosystems. Waiting for work to return via automation may succeed but as manufacturing taught us, automation brings work back without bringing jobs.Each solution carries a heavy price.Who Wins?I don’t see a magic button. I don’t see a clean fix waiting just beyond the horizon.What I see are capable engineers, onshore and offshore, competing desperately for scraps.In a more just world, they wouldn’t be rivals. They would be brothers, building together instead of being measured against one another.The true winners are easy to identify.Capital wins.If you own it, the line goes up. Stock prices rise. Human cost fades into abstraction. As long as the graph climbs, everything is considered fine.Maybe that’s all that matters now.Thanks for reading. If you’re morbidly curious enough to walk this path with me, I write and talk about these topics regularly. And if you choose to support the work, thank you. Truly.We’ll chat later. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello world.I’m an unemployed, ex–Big Tech software engineer with 25 years in the technology industry. And like many of you, over the past week I’ve been watching yet another wave of mass layoffs sweep across tech, tens of thousands of engineers, designers, and product leaders suddenly finding themselves on the outside.Every layoff cycle brings back a memory I can’t quite shake: my first.My First Layoff, 2008In 2008, during the Great Recession, I was a mid-level developer at a digital consulting agency. I’d been there just under two years, still learning, still finding my footing. I had a mentor, let’s call her Dana, an exceptional software architect who patiently taught me concepts I still carry today. She explained the differences between dynamically typed languages like PHP and the strongly typed Java systems I was used to, never making me feel small for not knowing.Then one afternoon, building security appeared on the floor.An emergency town hall invite hit our calendars. We gathered in the atrium, where our CEO, Rob, stood in front of us looking exhausted. He explained that unexpected economic conditions had caused the loss of major clients. Hard cuts had to be made for the company to survive.What struck me most wasn’t the announcement, it was his demeanor. There was shame in his face. Sadness in his eyes. He took full responsibility for the layoffs, repeatedly emphasizing that none of the affected employees were at fault. It felt almost ancient, like watching a leader fall on his sword.When the town hall ended and we returned to our desks, nearly half the floor was empty. Dana’s cube was stripped bare.I felt fear, anxiety, self-doubt, and an overwhelming sense of survivor’s guilt.At a nearby café, I found Dana. She told me she’d been laid off. She said mentoring me had been a pleasure. Her voice broke. She looked older than I’d ever seen her. At the time, she was younger than I am now, but loss has a way of aging you instantly.That was my introduction to mass layoffs.Three Eras of Tech LayoffsOver 25 years, I’ve survived countless layoffs across three distinct eras.The Great Recession Era was marked by reluctant leadership. Layoffs were painful, shameful, and avoided until there was no other option.The M&A Era of the late 2010s brought quiet, discreet layoffs: fast, clinical, and rarely discussed.The Post-COVID Big Tech Era, beginning around 2023, is something else entirely. Layoffs are framed as efficiency. As optimization. As something to be proud of. Strong engineers are cut not because they failed, but because markets demand higher valuations.In my view, this era is the most brutal and unpredictable of all.When my own Big Tech layoff finally came, I’d lost count of how many rounds I’d survived.How I Stayed Employed for 25 YearsI can’t offer guarantees, but I can share what helped me last as long as I did.Build a reputation for dependability.Be known as someone who gets things done well. That requires initiative, optimism, and solution-oriented thinking.Make your value visible.Speak up strategically. Share accomplishments. Ensure your manager—and their manager—knows what you contribute.Continuously learn in-demand skills.From bare metal servers to cloud platforms to SaaS, I was always learning what the market needed next. In-demand skills act like a parachute when you fall.Work on revenue-critical projects.Projects that directly make money are the least likely to be cut.Network relentlessly.Inside your team. Across departments. Outside your company. Your network is a safety net.Be versatile.Take on varied roles. Learn flexibility. Remember: the highly specialized T-Rex didn’t survive, but the adaptable mammal did.Final ThoughtsWe’re living in an age of seemingly unending layoffs in tech. These strategies are coping mechanisms, not guarantees. But applied consistently, they can move the needle.If you’re navigating this uncertainty, you’re not alone. I’m sharing this journey openly, part reflection, part therapy, part survival guide.If you’d like to follow along, join the newsletter, or simply grab a coffee with me along the way.Until next time. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Lamb Saag, Layoffs, and the Bug That Broke MeHello, world.I’m an unemployed ex–Big Tech software engineer with 25 years of experience, which in today’s economy apparently qualifies me for involuntary early retirement. One unexpected perk of this phase of life is that I now do a lot more cooking for my family. Today’s menu: Indian lamb saag. Slow, deliberate, and unforgiving if you miss a step, much like enterprise software.As the lamb simmers, let me tell you a story from a darker, stranger time.2009: The Corporate Hunger GamesThe year was 2009. Layoffs were everywhere. Entire floors disappeared overnight. Companies weren’t trimming fat; they were amputating limbs.I worked at a digital consulting agency that had already survived several rounds of bloodletting. By all logic, I should have been gone. Yet somehow, like a cockroach surviving a nuclear blast, I remained employed.Most of our major clients had vanished. One of the few whales still alive was a massive publishing conglomerate. Let’s call them Big Corp.Big Corp had just experienced a revelation that felt revolutionary at the time: What if people bought our newspapers and magazines… on the internet?Unfortunately, they had no e-commerce platform, almost no technical capability, and about 90% of their internal IT staff had already been laid off. In their place stood a shimmering mosaic of offshore and onshore H-1B contractors from a massive IT services firm. We’ll call them Outsourced Consultancy Services, or OCS.Naturally, my company won the pitch to build Big Corp’s e-commerce platform. And just like that, we dove headfirst into a corporate dumpster fire armed only with PowerPoint decks and unearned confidence.An Org Chart Designed by a MadmanThe project team was… unusual. Nearly half the people involved were VPs, directors, account executives, or some flavor of Extremely Important Person. There were almost more chiefs than Indians, which statistically should not be possible.Leadership had clustered around this project like penguins in a blizzard, hoping proximity to billable hours might keep them alive.I joined as a senior developer, and for the first time in my career, I became the tech lead of my own squad. It included Eddie, a brilliant engineer from New Jersey; Sam, an Australian project manager; Ravi, an OCS build master stuck in green card purgatory; and several junior developers.On paper, I reported to Bharath, an enterprise architect from OCS who had never written a line of code. Bharath reported to Heinz, an East German tech director from my company, and Mega, an OCS director. They reported to Fred, the client-side chief architect, and finally to Mr. Burns, a senior VP who looked exactly like a South Asian version of the Simpsons character. Same stare. Same energy. Same ability to drop a room’s temperature by ten degrees.If this sounds confusing, don’t worry. It was worse in real life.Building the BeastWe were tasked with building a web-based e-commerce system that allowed customers to order custom bundles of newspapers and magazines. Today, this would be a two-day Shopify project. Back then, it took five months, tens of millions of dollars, and what felt like several ritual sacrifices.Orders flowed through an enterprise service bus, were chopped into pieces, and fed into a horrifying backend fulfillment ecosystem composed of overlapping legacy systems, orphaned applications, and entire platforms built around employees who had been laid off years earlier.These systems were maintained by offshore sysadmins who treated them like ancient temples: don’t touch, don’t ask questions, and pray.There was exactly one client-side IT veteran who understood how it all worked. His name was Davey. He was gray-haired, exhausted, and spiritually done.My team owned the middleware layer. “Simple,” they said.PowerPoint Architects and Sausage MakingIt quickly became clear that Bharath’s tools were PowerPoint, Word, and criticism. I did the actual design. I wrote the specs. I drew the diagrams. Bharath reviewed them and offered feedback like:* “The font lacks authority.”* “This box should feel more visionary.”* “The verbiage needs architectural gravitas.”Then he presented my work to leadership.I smiled, nodded, and stroked his ego, because for the first time in my career, I had full ownership of an application. No micromanagement. No interference. Pure sausage-making freedom. Worth every ounce of frustration.We worked late. We bonded. Eddie, despite a stutter that caused management to underestimate him, was a phenomenal engineer. Ravi worked endlessly, supporting his family while trapped in immigration limbo. Sam dreamed of retiring as a landlord back in Australia.We ate together constantly, mostly Indian food. It’s strange how easy it is to form deep friendships when you’re young and suffering together.The Open Source MistakeAt some point, a client executive who had never touched middleware decided that open source was better. Requirements be damned.They chose an open source ESB product. Let’s call it Crazy Boss.Consultants from the company behind Crazy Boss, Silly Hat, arrived. They gave a dazzling demo, proclaimed that open source meant fewer bugs, charged an ungodly amount of money, and vanished.Here’s the lesson I learned too late:Open source does not mean bug-free. Sometimes it means you get to discover the bugs personally.The Bug That Shouldn’t ExistAs go-live approached, late nights became routine. Then weekends. Then time stopped mattering altogether.During system integration testing, an order entered the system and vanished. Not failed. Not errored. Gone.I checked everything. Logs. Queues. Dead letter Queues. Every line of middleware code. The bug should not have been possible.We couldn’t reproduce it.Leadership shrugged. “Probably a fluke. Let’s go live.”I did not shrug.I spiraled.I rebuilt environments. Simulated load. Obsessed. The stress followed me everywhere. When my girlfriend, now my wife, visited me before go-live, I was so anxious I couldn’t even be intimate.Nothing kills romance like a missing async message.Go Live NightOrders flooded in. Systems broke. We fixed them. By 3 a.m., things stabilized.Then the calls came.Missing receipt emails. Missing orders.The bug was real. My middleware was eating them.Mr. Burns stared at me and said, “Someone really effed this up.”Something inside me snapped.I walked out to the parking lot and cried. Full breakdown. Full impostor syndrome. My career was over. I was a fraud.Then Sam and Heinz followed me out.“Be kinder to yourself,” Sam said.Heinz added, with peak East German nihilism: “It never gets better. It only gets worse. Then we die. So why worry?”We went back inside.The FixDavey saved the day.He noticed the bug only happened after Crazy Boss ran for days under load. The solution?A cron job that restarted the instances in a round-robin fashion.No downtime. Just reboot and pray.It worked. The launch was declared a success.Months later, we learned the truth: a memory leak in Crazy Boss that only occurred under high concurrency on Citrix VMs.Of course.Aftermath and Curry NightmaresThat morning, I found Ravi sitting quietly. He told me his daughter’s daycare was teaching kids to throw away food, a grave sin in his culture. During go-live night, he decided to quit OCS and return to India.“God will find a place for me,” he said.Weeks later, Eddie suggested Indian food to celebrate surviving. At Curry Dreams, a local Indian buffet, I saw a cockroach the size of my thumb crawl up the wall… and fall directly into a vat of curry.We left immediately.From that day on, Curry Dreams became Curry Nightmares.EpilogueNow, years later, I’m stirring lamb saag in a quiet kitchen, unemployed but oddly at peace. That bug didn’t end my career. That breakdown didn’t define me. It was just another chapter in a long, messy story.If you have a morbid curiosity to follow along on this strange life journey, you know where to find me.Thanks for listening.Talk soon. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello, world.A few months ago, I became what feels like a new tech archetype: an unemployed ex–Big Tech engineer with over 25 years in the industry. In today’s climate, that sentence alone is enough to spike blood pressure. Yet, strangely, my recent layoff hasn’t felt like a crisis. It’s felt more like a quiet pause, a semi–early retirement, or at least a transition into the next chapter of life.That perspective didn’t come from optimism or denial. It came from math.For more than a decade, my family has maintained a savings rate north of 50% of our gross income. It wasn’t flashy. It wasn’t Instagram-worthy. But it fundamentally changed how we experience uncertainty. A high savings rate builds a large emergency fund, and that buffer softens the sharpest edges of job loss. More importantly, sustained saving allows those dollars to compound into income-producing investments, eventually buying you something far more valuable than luxury goods: optionality.If you do it long enough, financial independence becomes less of a dream and more of a boring, inevitable outcome.Debt Is a Black Hole (I Know Because I Fell In)Let’s start with the most important lesson: debt is financial gravity.Educational and consumer debt behave like a black hole attached to your wallet—relentlessly sucking money away while giving nothing in return but anxiety and regret. Whatever you bought with that debt is long gone, but the payments linger, quietly preventing you from building emergency savings or investing in your future.I know this intimately. Early in my marriage, my wife and I sat down for an honest look at our finances and realized we owed over $150,000 in student loans. This revelation landed just days after she told me she was pregnant. It was shortly after the financial crisis, my job felt unstable, and the debt alone was costing us more than $1,000 a month in interest.We were trapped.So we declared war on debt.We slashed our spending to the bone. Aside from rent, we lived on about $100 a week: groceries, toiletries, everything. We lived like monks with Wi-Fi. During the day, I worked my consulting job. At night, I built Android apps, fast, ugly, practical apps, anything that could generate revenue.This was around 2010, when Android was the Wild West. Apps that did almost nothing were making real money. I churned out about 50 simple apps: timers, flashlights, bird guides, concrete calculators. I priced them at one or two dollars, and somehow… they sold.I worked 80–90 hours a week for years. When my son was an infant, his crib sat beside my bed. At 1 a.m., after another night of coding, I’d hold his tiny hand for a few quiet minutes before falling asleep. That was the time I had with him back then. It was brutal, but it worked.Within two years, we were debt-free.We used a psychological “snowball” strategy, paying off the smallest loans first. Was it mathematically optimal? No. Was it emotionally powerful? Absolutely. Watching balances disappear kept us moving forward.Freedom tastes better than efficiency.Housing: Ignore Realtors, Embrace MathHousing is usually the largest expense in a household, which means it’s also the biggest lever.Whether renting or buying makes sense depends on location, but once you decide to buy, ignore the advice to “get as much house as you can afford.” That mindset quietly sabotages long-term wealth.Instead, I used the 80/20 rule. If you’re willing to compromise 20% on size, finishes, commute, or neighborhood, you can often cut the price dramatically.That’s exactly what we did. We bought a modest home with a large backyard, decent schools, and a longer commute. It was a short sale, and the total monthly payment—including taxes and insurance was around $2,000. That was a fraction of what many of my coworkers were paying.The result? Massive monthly savings that went straight toward paying off the mortgage early.Today, our housing costs are down to about $900 a month in property taxes and insurance. That’s it.Transportation Is a Toaster Oven, Not a PersonalityCars are utilities, not status symbols.If you live in a dense metro area, public transportation may be the cheapest solution. If you need a car, buy one that maximizes reliability and minimizes lifetime cost. For me, that meant used Toyotas and Hondas, three to five years old.This is the sweet spot: you get 80–90% of a car’s usable lifespan for half (or less) of the original price. These vehicles are mass-produced, boring, and extremely durable. They’re also cheap to insure and repair.I currently own two fully paid-off Honda CR-Vs. Each costs about $150 per month in total lifecycle expenses: gas, insurance, maintenance, everything. That’s a tiny fraction of the cost of a new luxury vehicle.Boring wins again.Food: Brown Bags, Crock Pots, and Quiet WealthWe rarely eat out, maybe once a month for special occasions. For over 15 years, my wife and I brown-bagged our lunches. By my rough estimate, that habit alone saved us a few hundred thousand dollars.Cooking isn’t hard. With basic skills, you can make food that’s 80–90% as good as restaurant meals at a fraction of the cost. And if you want a true engineering marvel in your kitchen, allow me to introduce the crock pot.For about 15 minutes of prep time and pennies of electricity, it produces massive quantities of cheap, delicious, nutritious food. Chili, curry, soup, set it and forget it.We buy mostly unprocessed foods, often organic, from reasonably priced stores like Aldi. For a family of four, our monthly food budget runs around $700–$800.Managing Consumerism in a FamilyMinimalism is easy when you’re single. Add a spouse and kids, and things get… complicated.The solution isn’t deprivation, it’s containment.We set monthly spending ceilings. We teach our kids to think about value, not just desire. (This lesson is working better on my son than my daughter, but progress is progress.)I also noticed that most consumer goods lose their appeal shockingly fast, sometimes within days. So I built a small “distribution center” in my basement where unused items are inventoried and resold on eBay, Facebook Marketplace, or Mercari. Unsold items are donated for tax deductions.That system recovers about 10–20% of what we spend on consumer goods, which quietly adds up.The Boring Path to FreedomWith these strategies, we saved more than 50% of our income for many years. None of this is revolutionary. Outside the tech bubble, this is how many people already live.But in an industry facing endless layoffs, these habits can turn a terrifying event into a manageable transition.My layoff didn’t feel like falling off a cliff. It felt like stepping onto a different trail.If you’re morbidly curious to follow along on this life journey, you know where to find me. And if you found this useful, welcome to the quiet, unsexy, deeply satisfying world of financial independence.See you next time. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello world.Until recently, I was a senior engineer at a Big Tech company, with 25 years in the technology industry behind me. Today, I’m unemployed, watching the industry I grew up in sprint headlong into what feels like the largest speculative bet of its lifetime.Not long before I was laid off, my former employer held a company-wide AI hackathon. By that point, the company had already invested billions of dollars into training frontier models and building out the infrastructure to support them. Massive data centers. Enormous training runs. A portfolio of large language models that needed, urgently, to justify their existence.The goal of the hackathon was simple, at least on paper: come up with bold, transformative, responsible AI ideas that could, somehow, turn all of this spending into revenue.In other words: please make the AI pay for itself.The A-Team (and a Reality Check)I joined a hackathon team led by a senior engineering leader—let’s call him Danny. On paper, it was the A-Team.There was Jimmy, the Canadian tech lead who could brute-force his way through any codebase. Subash, an H-1B architect who was frighteningly sharp. Alex, a junior engineer who had survived our brutal internship program. And Lionel, a support team lead with an effortlessly charming British accent which, by the way, is an unfairly powerful asset when pitching business ideas in tech.We brainstormed and quickly landed on what seemed like an obvious win: an AI-powered customer support agent.The idea was straightforward. Most customer support cases are repetitive. With a large language model enhanced by Retrieval-Augmented Generation (RAG)—essentially giving the model access to proprietary internal knowledge, we believed the agent could autonomously resolve roughly 90% of incoming cases.Within a day, we had a working proof of concept running inside a Docker container.Feeling confident, we presented the idea to a business leader in our product line, let’s call him Leo.Leo listened patiently. Then he dismantled the idea.Yes, he acknowledged, the agent might handle 90% of cases. But the remaining 10%—the hard, messy, ambiguous ones were what consumed over 90% of the support team’s time. Those were the cases customers escalated. Those were the cases that mattered.What we had built, he argued, was essentially a glorified FAQ page.Then came the line that stuck with me: “This feels like a shiny solution in search of a problem.”A Microcosm of the AI IndustryThat moment crystallized something uncomfortable.Despite the massive investments and the relentless internal pressure to “AI-ify” everything, it was genuinely difficult to extract real, defensible business value from AI in many domains. Outside of narrow niches with abundant training data, returns were murky at best.That small hackathon experience now feels like a perfect microcosm of the broader AI industry.Hundreds of billions, possibly trillions, of dollars are being poured into AI. Yet most AI initiatives today are losing money. In some cases, a lot of money. Each API call to a large language model can cost several times more to serve than it generates in revenue.Meanwhile, the hype machine roars on.World models. Humanoid robots. Confident proclamations that AGI is just around the corner.Some of these efforts are legitimate research. Others feel like science fiction being aggressively monetized. If this reminds you of the dot-com bubble, you’re not wrong, except this time, the scale is orders of magnitude larger.Financial Alchemy and Corporate OpticsThe problem is that the money has already been spent. And investors want returns now.To maintain the appearance of growth, companies resort to financial gymnastics: buying AI services from each other to simulate demand, reclassifying existing product revenue as “AI revenue” after adding superficial features, and framing mass layoffs as “AI efficiency gains” while quietly shifting work offshore.The result is a market that looks strong on the surface but increasingly fragile underneath.Big Tech now accounts for roughly 40–50% of the S&P 500’s total valuation. If confidence cracks, if investors realize these investments won’t pay off on the promised timelines, the unwind could be violent.If the Bubble BurstsIf an AI collapse happens, it likely won’t be a single dramatic moment. A weaker, AI-only company could fall first. A large investor could panic. Political backlash against data centers and energy costs could accelerate sentiment shifts.The downstream effects would be severe: an AI winter where funding dries up, market caps shrink, RSUs evaporate, and layoffs spread not just across AI teams, but across entire platforms and ecosystems.Beyond tech, the impact would ripple outward: data centers halted, semiconductor orders canceled, real estate markets strained, financial institutions exposed. In a worst-case scenario, cascading failures could spill into the broader economy.This isn’t a prediction. It’s a plausible risk path.How to Cope (Not Panic)So what can individuals, especially software engineers, do?At work: double down on core problem-solving skills. Learn to wield AI as a tool, not fear it. Build T-shaped expertise that spans engineering, product, and business.Outside of work: build a much larger emergency fund than traditional advice suggests. Reduce fixed expenses. Create alternative income streams: side projects, businesses, anything that isn’t tied to a single employer.None of this is easy. And none of it is guaranteed to be necessary.This may all amount to nothing more than the late-night musings of a laid-off engineer with too much time to think. The AI boom could continue. Stocks could soar. Everyone could get rich.But history suggests that when investment, hype, and financial reality drift too far apart, gravity eventually reasserts itself.For now, all we can do is stay alert, stay flexible, and remember that technological revolutions are rarely as smooth or as profitable as they look at the peak. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello world—and welcome to the uncomfortable side of tech.I’m a recently laid-off ex–Big Tech software engineer with 25 years in the industry. In the middle of what feels like an endless wave of tech layoffs, I keep hearing the same question from people outside the industry and from junior engineers just starting out:“With those salaries, shouldn’t senior software engineers all be rich and financially independent?”On paper, it’s a perfectly reasonable assumption. Tech compensation, especially in Big Tech, looks outrageous to most people. Six-figure salaries, stock grants, bonuses, numbers that feel almost cartoonish compared to the median income.And yet… reality tells a very different story.Over decades in tech, I’ve watched many experienced, intelligent engineers accumulate shockingly little savings. Some are so financially exposed that a single layoff pushes them instantly into crisis mode. I’ve even seen stories of engineers laid off from companies like Meta who, after months of unemployment, ended up homeless.So how does this happen?After a lot of reflection, I’ve come to think of the answer as a series of money vacuums, individually rational choices that quietly drain even enormous incomes when stacked together.Money Vacuum #1: High Cost-of-Living Gravity WellsTech workers cluster in a handful of metropolitan areas, places like the Bay Area, Seattle, New York. These cities routinely cost two to three times more than rural or mid-sized regions. And this is true even if you live modestly, even if you “live like a monk.”I grew up in rural Pennsylvania. The cost difference is staggering.No matter how frugal you think you are, geography alone can quietly eat your paycheck.Money Vacuum #2: The House That Ate Your SalaryHousing is where things really get dangerous.Surrounded by peers buying large homes in prestigious neighborhoods, many engineers follow suit. These houses often sit in top-tier school districts, come with expensive renovations, and carry truly massive mortgages.Between mortgage payments, property taxes, insurance, maintenance, and utilities, it’s not unusual for housing costs to reach $5,000, $10,000, or even $15,000 per month.Worse, housing is illiquid. When layoffs hit, you can’t easily access that equity, so the very thing meant to represent “success” becomes a financial trap.Money Vacuum #3: Luxury Cars and Status SpendingTech workers, especially consultants, are prime targets for luxury car marketing. Cars become symbols of success, innovation, arrival.But behind the feelings are tens or hundreds of thousands of dollars in depreciating assets. In many urban centers, public transportation would do just fine, yet monthly car payments often rival a typical family’s mortgage.That’s not freedom. That’s drag.Money Vacuum #4: Food as Convenience (and Therapy)Tech is stressful. Food becomes a coping mechanism.Takeout at work. Restaurants as family time. High-end grocery stores where basic items cost multiples of normal supermarkets.The result? Monthly food spending that can quietly rival a mortgage payment, again.Money Vacuum #5: The Education Arms RaceMany engineers come from cultures that deeply value education. The instinct is understandable but the spending can spiral.Tutoring, cram schools, extracurriculars, private schools, college funds, it all adds up. For families with multiple children, education spending can easily match housing costs.The hard truths:* Spending 10x more doesn’t make your child 10x more successful.* Excessive pressure can damage mental health and create resentment toward learning itself.Money Vacuum #6: Consumption as a Band-Aid for BurnoutTech work consumes lives.Endless calls. Launches. Hypercare. Travel. There’s little time left to actually live.That emptiness often gets patched with consumption:* Burned out? Buy a new gadget.* Marriage struggling? Buy designer goods instead of time.* Kids need help? Buy educational toys instead of attention.Thousands disappear every month without ever addressing the real problem.Money Vacuum #7: Tech Bro FOMO InvestmentsRSUs vest. Six figures land in your account.Suddenly, an entire ecosystem appears, pitching world-changing investments you must get into right now.NFTs. Exotic hardware startups. Energy mirrors. Plant-based 3D-printed meat.Sometimes, someone wins big. Most of the time, money quietly evaporates. Domain expertise doesn’t magically transfer, but confidence often does.FOMO plus overconfidence is a devastating combination.Money Vacuum #8: When Life Just HappensIllness. Accidents. Divorce. Family emergencies.These hit everyone, but when high earners fall, they fall harder. More money at risk means more damage.The Brutal Stack EffectEach of these choices seems reasonable in isolation. Together, they can devastate even the highest compensation packages in tech, leaving engineers frighteningly exposed when layoffs arrive.That’s why so many “rich” engineers aren’t actually secure.My Own Layoff: A Different OutcomeMy recent layoff looked very different.After years of saving and investing, I wasn’t thrown into survival mode. I landed somewhere closer to semi–early retirement.It feels a bit like being kicked off the Hindenburg right before it explodes, standing just outside the blast radius, watching the slow-motion catastrophe unfold across the tech industry.It’s horrifying. And, admittedly, impossible not to watch.Final ThoughtsThis isn’t about shaming. It’s about awareness, empathy, and hard-earned perspective.If you work in tech (or hope to) you deserve to understand the invisible forces pulling at your finances. High income doesn’t guarantee safety. Intentional choices do.If you’re morbidly curious about my ongoing journey through tech, layoffs, and financial independence, feel free to stick around.Thanks for reading.Talk soon. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe

Hello, world.I’m a software engineer who was recently laid off from Big Tech after more than 25 years in the industry. Over the past few weeks, I’ve received a steady stream of questions from college students studying computer science, mostly young guys asking some version of the same thing:“Is it still worth it?”“Should I even keep pursuing tech?”Those questions have taken me back to my own early days as a junior engineer, fresh out of college, stepping into a world that feels almost unrecognizable compared to today.When a Diploma Was EnoughWhen I started my career, simply having a computer science degree was often enough to get your foot in the door. I remember joining a consulting company and being dropped straight onto a high-pressure project, a CMS launch for a major telecom client, barely a month from go-live.As a junior developer, I was immediately assigned bug-fixing duties. There was just one small problem: I didn’t actually know how professional software development worked.My degree hadn’t taught me about unit testing, mocking data, runtime debugging, or even basic dependency management in Java. Predictably, many of the bugs I “fixed” failed spectacularly in higher environments.One day, I spent hours stuck on an error caused by a library version mismatch, an “unsupported major/minor version” issue. I didn’t know what that meant, so I did what any confused junior engineer might do: I started exploding the Java package and inspecting class files by hand.Eventually, our build master, let’s call him Dima, wandered over. Dima was kind, brilliant, and fond of deeply pessimistic jokes. He laughed, explained the issue in about 30 seconds, and fixed it. For the rest of the project, I was lovingly known as “the guy who exploded his package.”Becoming a Production CowboyThat project also introduced me to my first real tech lead, Naga. During our go-live night, we stayed up until the early morning hours, fixing one production-blocking defect after another.At one point, after midnight, things seemed stable enough that Dima went home. Naturally, that’s when everything broke.I vividly remember Naga manually editing configuration files directly on production servers, no pipelines, no guardrails, just raw experience and calm under fire. He may not have been the most disciplined engineer by today’s standards, but he was an exceptional leader and a genuinely good human being.Around 5 a.m., when the site finally went live, Naga told me something I’ve never forgotten:“The most important thing isn’t fixing the bugs.It’s learning from them and having fun doing it.”Fear, Impostor Syndrome, and the Desire to Get BetterBeing a junior engineer back then was a cocktail of emotions: fear, excitement, anxiety, hope. I had massive impostor syndrome but also a deep hunger to improve, to master the craft, and to earn my place in the world.Throughout my career, I was lucky. I had mentors like Naga who guided me, supported me, and believed in me. As I advanced, I tried to pay that forward, mentoring junior engineers and later running internship programs at my most recent company.Which brings me to today.The World Junior Engineers Are Entering NowThe environment today could not be more different.There are simply far more engineers on the job market. Years of “learn to code” messaging from governments, universities, and Big Tech itself have saturated the pipeline. As a result, a computer science degree is worth dramatically less than it was a generation ago.Junior engineers today are competing with:* Mid-level engineers willing to take junior roles* Laid-off seniors swallowing their pride to stay employed* Offshore engineers working for lower wages* Senior engineers supercharged by AI tools* And, increasingly, GPU-filled data centers consuming budget once reserved for humansThe cruel irony? New graduates are often more capable than I ever was at their age.I once had an intern architect, build, and deploy a production-ready cloud application that the company actually used. He still didn’t get a full-time offer. Not because he wasn’t good, but because there simply weren’t enough entry-level roles.Worse still, even when juniors do get hired, support systems feel thinner than ever. There are incentives to discard them quickly rather than invest in their growth.It feels like the industry is wasting an entire generation of smart, motivated engineers and that feels deeply unjust.Why This Hits Close to HomeMy own son is STEM-inclined. He’s a teenager and recently submitted his first pull requests to an open-source project. Watching him navigate this world has made these questions impossible to ignore.So instead of offering platitudes, I want to share a few practical coping strategies, things that, in my experience, can genuinely move the needle.1. Be True to YourselfIf you genuinely enjoy computer science, even if you just kind of like it, keep going.But if you hate it? If you’re only here because of parental pressure, TikTok salary videos, or the promise of easy money, pause.Don’t betray your inner voice.I’ve met many people who stayed in tech for external reasons alone, and for most of them, it became a source of deep regret.2. Build Eminence, Not Just a PortfolioPersonal projects are fine, but what really matters is recognized work.Build software for your university or a nonprofit. Contribute meaningfully to open-source projects. Speak at meetups. Join hackathons and try to win them.You want institutions, organizations, and communities to vouch for your work.3. Maximize Internships RuthlesslyInternships aren’t a guarantee but they are orders of magnitude more effective than cold applications.Use career fairs, alumni networks, professors, and professional connections. If you miss the internship window, compensate aggressively elsewhere.4. Treat the Job Hunt Like a SkillGet your résumé professionally reviewed. Practice LeetCode and HackerRank until interviews feel routine. Do mock interviews. Apply broadly, not just to tech companies, but to any company hiring software engineers.If needed, consider adjacent roles: QA, DevOps, data engineering, sales engineering. Once inside, you can pivot.5. Be Flexible—Like WaterIf Big Tech isn’t hiring, consider partnerships, gigs, startups, or solo projects. Be open to relocation, even to another country.Flexibility creates surface area. Surface area creates opportunity.A Final ThoughtI make no promises. The system is undeniably hard right now.But I do believe that for most of you, these strategies, applied consistently, will help.If nothing else, I hope this reflection reminds you that you’re not alone, and that the struggle you’re feeling is real, not a personal failure.If you’re curious to follow along as I navigate life after Big Tech, I’ll be sharing more of these thoughts. It turns out, making these vlogs and writing pieces like this feels surprisingly meaningful.Thanks for reading.Take care. Get full access to AsianDadEnergy's Newsletter at asiandadenergy.substack.com/subscribe