AsianDadEnergy's Substack Podcast

AsianDadEnergy

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

Episodes

  1. 2D AGO

    AI Isn’t Creating the Future… It’s Rebuilding the Middle Ages

    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 Past To 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 Themselves When 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 Order Now 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 Labor Artificial 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 Forward This 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    13 min
  2. Tech Is Collapsing. My Investments Paid My Bills Anyway.

    FEB 11

    Tech Is Collapsing. My Investments Paid My Bills Anyway.

    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 Backbone In 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 loans I 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 Wealth My 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 Sold In 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 Insurance A 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 Risk Joining 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 Paid In 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 Asset As 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 Understand In 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 Picture We 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 time In 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    27 min

  3. FEB 6

    The Truth About Offshoring: Why Tech Jobs Are Disappearing for Good

    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 Waves Offshoring 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 Zones Teams 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. Language Even 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. Culture In 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 Again By 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 Terms Abby 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 Incentive Offshoring 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    20 min

  4. FEB 2

    Mass Layoffs in Tech: I Survived Them for 25 Years—Until I Didn’t

    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, 2008 In 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 Layoffs Over 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 Years I 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 Thoughts We’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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    11 min

  5. JAN 30

    Surviving the 2009 Tech Layoffs: All-Nighters, Broken Open Source & Impostor Syndrome

    Lamb Saag, Layoffs, and the Bug That Broke Me Hello, 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 Games The 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 Madman The 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 Beast We 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 Making It 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 Mistake At 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 Exist As 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 Night Orders 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 Fix Davey 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 Nightmares That 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. Epilogue Now, 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    14 min

  6. JAN 30

    Laid Off After 25 Years in Tech: How a 50% Savings Rate Made It Stress-Free

    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 Math Housing 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 Personality Cars 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 Wealth We 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 Family Minimalism 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 Freedom With 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    17 min

  7. JAN 30

    When the AI Bubble Pops: Layoffs, AI Winter, and What Comes Next

    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 Industry That 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 Optics The 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 Bursts If 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    15 min
  8. Big Tech Paychecks, Broke Engineers, and the Money Black Holes

    JAN 30

    Big Tech Paychecks, Broke Engineers, and the Money Black Holes

    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 Wells Tech 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 Salary Housing 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 Spending Tech 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 Race Many 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 Burnout Tech 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 Investments RSUs 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 Happens Illness. 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 Effect Each 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 Outcome My 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 Thoughts This 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    12 min

  9. JAN 30

    25 Years in Tech, Now Laid Off: Honest Advice for Junior Engineers in a Brutal Job Market

    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 Enough When 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 Cowboy That 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 Better Being 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 Now The 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 humans The 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 Home My 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 Yourself If 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 Portfolio Personal 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 Ruthlessly Internships 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 Skill Get 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 Water If 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 Thought I 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    13 min
  10. Laid Off After 25 Years in Tech: The Anxiety, Sacrifice, and Reality No One Talks About

    JAN 30

    Laid Off After 25 Years in Tech: The Anxiety, Sacrifice, and Reality No One Talks About

    Hello, world. Two weeks ago, I was laid off from Big Tech. After twenty-five years in the technology industry, it was my first layoff and it landed with a strange mix of confusion, disorientation, and, unexpectedly, a flicker of excitement. When you’ve spent most of your adult life on a clearly marked path, being pushed off it feels less like failure and more like suddenly waking up in unfamiliar terrain. Learning the Craft My relationship with technology began early. In high school, I was already writing code, building computers, and tinkering with anything that had wires or logic behind it. By college, I was juggling internships and small contracts: writing scripts, building Visual Basic apps, learning by doing. After graduation, I joined digital consulting agencies, and those years felt electric. Every project brought a new language, framework, or platform. The world of software engineering felt infinite. I worked obsessively at the craft. I devoured technical books, lived in IDEs, and chased mastery with the kind of hunger only youth allows. For a time, it worked. I became strong and confident enough that my company sent me to hackathons, where my teams consistently placed near the top. Software felt like magic, and I felt fluent in it’s language. The Shock That Changed Everything Then came 2008. During the financial crisis, I watched brilliant, experienced colleagues lose their jobs. One mentor—someone I deeply respected—broke down in tears, terrified she wouldn’t be able to provide for her family. That moment cracked something open in me. It was also when I discovered the idea of financial independence. A book, Your Money or Your Life, reframed how I thought about work, not as a ladder, but as an exchange of life energy for money. From that point on, my family changed how we lived. We became deliberate. Frugal. Intent on saving not just money, but time and choice. It wasn’t about deprivation; it was about buying freedom. Climbing the Ladder My career continued to grow. I moved from developer to tech lead, from architect to senior technical leadership. Over twenty-five years, I changed companies, designed platforms, led teams, and eventually landed in Big Tech, where compensation reached levels that still feel absurd when I think about them. The perks were real. I traveled across North America, Europe, and India. I worked on cutting-edge systems, earned patents, and collaborated with people who were brilliant, disciplined, and generous with their knowledge. For all its flaws, tech gave me access to extraordinary minds and experiences. The Cost of the Grind But the costs were real too. Tech is relentless. Long hours became longer once teams went global. Early mornings blended into late nights. Learning never stopped, and in my forties, learning started to feel heavier, slower. Still possible, but harder. Worse than the fatigue was the creeping sense of futility. The problems we solved felt recycled. The products rarely made the world meaningfully better. I poured years of effort into systems that would be replaced, forgotten, or quietly deprecated. That time came from somewhere, mostly my family. There were years when I had only an hour each night with my kids. An hour to read, talk, tuck them in. My son is a teenager now, and I can feel how little time remains before he’s grown. That realization weighs heavily: how much of what I missed can never be recovered. Mortality and Memory A few years ago, a colleague, brilliant, hardworking, devoted, he fell ill during a brutal push at work before Christmas. He never came back. The company honored him respectfully, but within a month, it was as if he’d never existed. That realization lingered. Then, earlier this year, my wife suffered a serious health crisis that left her partially disabled. It shattered the illusion that time is guaranteed. Tomorrow isn’t promised. And once you truly understand that, trading your life for work that doesn’t matter feels indefensible. Choosing the Layoff Meanwhile, the industry itself was changing. Interest rates rose. Offshoring accelerated. AI tools reduced the need for human labor. Layoffs came in waves. When my turn arrived, I learned I could protect several junior colleagues by putting myself first on the list. So I did. My former employer treated me fairly, with warning, severance, and respect. For that, I’m grateful. But the chapter still ended. Writing the Next One Now I stand somewhere unfamiliar. The path I followed for decades is gone, replaced by countless trails, none yet chosen. It feels like wilderness, uncertain, but alive with possibility. This is an inflection point. I need to design a life that is mentally healthy, physically sustainable, and genuinely meaningful. That’s why I’m writing. Why I’m recording. Why I’m documenting this moment. The future is an undiscovered country. And for the first time in a long while, I get to decide how the story is written. —Thanks for reading. Talk soon. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    17 min

  11. JAN 30

    Big Tech, AI Everywhere, and Fewer Engineers: A Laid-Off Engineer’s Reality Check

    Hello, world. After 25 years in the tech industry, I recently found myself laid off from Big Tech, an experience that has become increasingly common over the last couple of years. With some unexpected time on my hands, I’ve been doing what engineers do best: thinking deeply about systems, incentives, and failure modes. This time, the system in question is AI and more specifically, what the current AI boom means for software engineers. The AI Gold Rush Nobody Asked For If you’ve worked in Big Tech recently, you’ve seen it firsthand. Every department, every product, every roadmap meeting eventually funnels toward the same conclusion: “Can we add AI to this?” Hackathon after hackathon, teams are pulled together to “ideate” around AI, often regardless of whether the problem actually calls for it, or whether the people involved have any background or interest in AI at all. But beyond the buzzwords and demo days lies a far more uncomfortable question: What does all of this mean for software engineering jobs? What Generative AI Is and What It Isn’t Generative AI, particularly large language models, are fundamentally probabilistic systems. When you type a prompt into a model like ChatGPT, each word in its response is simply the most statistically likely word to follow the previous one, based on massive amounts of training data. The result looks like reasoning. It sounds coherent.But there’s no actual understanding happening. Despite the popular narrative, we don’t even fully understand how human reasoning works, so the idea that scaling LLMs linearly leads to Artificial General Intelligence feels, at best, optimistic and, at worst, fantastical. What we have today isn’t a machine god.It’s more like an idiot savant, exceptionally good at mimicking logic without possessing it. And yet… that’s still enough to disrupt an industry. Why Software Is Especially Vulnerable History gives us a useful analogy. In the 19th century, agriculture didn’t require humanoid robots to be automated. Tractors and harvesters, much simpler machines, were enough to replace massive amounts of human labor. Software engineering may be facing a similar moment. Most software written today is repetitive, predictable, and digital by nature—making it ideal training data for AI. Unlike other forms of engineering, software exists almost entirely as text, freely available in repositories across the internet. That makes it one of the easiest professions for AI to encroach upon. The Cracks Beneath the Hype That said, the current generation of AI tools has real limitations: * Training data quality is inconsistent.Open-source code varies wildly in quality, age, and correctness. * AI increasingly trains on AI-generated code.This creates a feedback loop, a snake eating its own tail, where quality can degrade over time. * Context windows are limited.Large codebases don’t fit cleanly into an AI’s short-term memory, leading to hallucinations and subtle but dangerous bugs. * Critical work remains semi-analog.Requirements gathering, stakeholder negotiation, system design, and architectural judgment are not fully digitized, and therefore not easily learned by machines. The result? AI excels at greenfield code but struggles with large, messy, real-world systems. Fewer Engineers, Different Roles Even with these limitations, it’s hard to deny the trajectory. AI already produces code that is good enough most of the time and it will continue to improve. The likely outcome isn’t the total elimination of engineers, but rather: * Fewer roles overall * Greater emphasis on human judgment * More value placed on reasoning, intuition, and systems thinking This isn’t unprecedented. Aerospace and electrical engineering went through similar transitions long ago. Four Ways to Survive the AI Tiger Right now, it feels like AI is a tiger chasing the tech industry. I see four possible coping strategies: 1. Ride the Tiger Work on frontier AI itself. * Pros: High pay, world-changing potential * Cons: Brutal competition, high barriers to entry, and the risk of an AI winter 2. Outrun the Tiger Constantly chase the newest languages and frameworks. * Pros: Short-term job security and high compensation * Cons: Career roulette, cognitive fatigue, and diminishing returns with age 3. Tame the Tiger Become a generalist who orchestrates AI tools. * Pros: Massive leverage, small teams, long-term relevance * Cons: Everyone is trying this, and true generalists are rare 4. Hide from the Tiger Work in regulated or hard-to-digitize industries. * Pros: Stability for now * Cons: Digitization eventually comes for everyone No Perfect Ending, Only Tradeoffs I don’t see a future where everyone in tech wins. But I do see paths where some engineers adapt, specialize, and survive. This isn’t optimism. It’s systems thinking. And yes, I know this sounds a little bleak but it’s my honest assessment after spending a long time thinking about the problem. That said, I’m just a laid-off ex–Big Tech flunky.You should take everything I say with a generous grain of salt. If you’re curious to follow along as I navigate life after Big Tech, thinking, building, and occasionally ranting, then feel free to subscribe and join the journey. Thanks for reading.Talk soon. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

    16 min

  12. JAN 30

    After the Big Tech Layoff: Brutal Interviews, Early Retirement Fears, and What Comes Next

    Hello, world. A little over a week ago, I shared a vlog about being laid off from Big Tech after twenty-five years in the industry. I didn’t expect what happened next. The response was overwhelming, in the best possible way. Messages of encouragement, thoughtful advice, shared stories, and hard-earned wisdom poured in. I want to start by saying thank you. Truly. I also want to acknowledge something important: this is an extraordinarily difficult moment for laid-off engineers everywhere. I know I’m one of the fortunate ones. Years of saving, investing, and a bit of luck have given my family some stability. Many others don’t have that buffer. Life intervenes (illness, obligations, timing…etc) and suddenly survival mode replaces reflection. And for junior engineers just entering the field, my heart really goes out to you. You’re facing forces far beyond your control, and that’s an especially brutal place to be. Because of my circumstances, I have options. Over the past few weeks, I’ve been exploring three broad paths forward, weighing each carefully. Option One: Back to Big Tech The first option is simple, at least in theory: get back into the grind. Apply for another Big Tech role. For me, this path has exactly one upside: staggering compensation. Out of habit and inertia, I started applying. Dozens of applications disappeared into silence. Some were rejected within minutes by automated systems. Eventually, I landed a single real screening and moved forward to a technical interview. While preparing, grinding through Java problems on LeetCode, I paused and remembered someone from my past. In 2010, freshly promoted and full of confidence but short on wisdom, I interviewed a man I’ll call Bob. He was in his fifties, gray-haired, intense. I grilled him relentlessly. Design patterns. Concurrency. An LRU cache from scratch. He handled everything effortlessly. Only later did I learn he had worked on the original Java language and JVM at Sun Microsystems, experience he’d removed from his résumé just to stay employable. In the debrief, everyone agreed Bob was technically excellent. But the verdict was clear: “not a cultural fit.” Looking back, I don’t think Bob was aggressive. I think he was desperate. Now, years later, preparing to interview with someone half my age, I realized something uncomfortable: I had become Bob. That insight ended my Big Tech job search. The cost to dignity, identity, and peace simply isn’t worth the paycheck. Option Two: Early Retirement The second option is early retirement. After nearly seventeen years of living below our means, my family has built enough of a cushion that paid work is optional. Time, real time, has become mine again. Time for family, health, friendships, and simply being present. There’s a lot to love about this option. Compounding works quietly in the background. In theory, wealth continues to grow while life slows down. But two concerns linger. First, the system itself. Capitalism, as we know it, isn’t guaranteed. AI investments, economic shocks, black swan events, any of these could reshape the world in ways that make passive income less reliable. A backup plan feels prudent. Second, meaning. Most men, once their basic needs are met, feel an internal pull to build something to create, contribute, matter. Leisure alone doesn’t satisfy that drive. Option Three: Meaningful Work That leads to the third option: doing work that actually matters. Not hustle-for-hustle’s sake. Not grinding endlessly. But building something meaningful whether with others or on my own. Projects, tools, ideas that make a dent, however small. This path isn’t easy. It requires a shift from executor to creator, from employee to founder. There are no guarantees anyone will care about what I build. Still, this option feels alive in a way the others don’t. The Path Ahead Where does that leave me? Somewhere between option two and option three. Semi-retired, but curious. Financially independent, but still driven. I plan to experiment, to throw ideas at the wall and see what sticks. Build slowly. Learn openly. Stay human. If you’re morbidly curious about how this unfolds, you’re welcome to follow along. I don’t have answers yet but I’m finally asking the right questions. Until next time. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit asiandadenergy.substack.com

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

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