SWE Investment

TL;DR: Nassim Taleb’s The Black Swan isn't an investing manual; it’s a masterclass in risk management. The biggest takeaway for a long-term investor is that survival takes precedence over maximizing returns. By rethinking diversification, challenging the assumptions behind our predictive statistical models, and building portfolios that can withstand the "highly improbable," we can engineer long-term financial resilience. 📖 Book: The Black Swan: The Impact of the Highly Improbable by Nassim Nicholas Taleb If you'd like to read it yourself, here is my affiliate link: https://amzn.to/4gUYcGD Not every book that influences the way I invest is actually an "investing" book. One of the most influential titles on my bookshelf is The Black Swan by Nassim Nicholas Taleb. At first glance, it doesn't appear to be a book about building wealth or picking stocks. It is a book about uncertainty. The more I internalized its core arguments, the more I realized tha...

When people look at a large investment portfolio, it's easy to assume it was built by investing the exact same amount every single month for decades. That certainly wasn't my experience. My investment journey has gone through several distinct phases, each reflecting what was most important in my life at the time. If you are on the path to financial freedom, understanding these phases can help you navigate your own timeline. Phase 1: Before Investing Came Financial Stability When I first started earning a salary, building wealth through the stock market wasn't my highest priority. Building an emergency fund was. Before putting serious money into the market, I wanted enough cash to cover roughly six months of living expenses. That emergency fund wasn't there to earn a high return; it was there to buy peace of mind. Knowing I could survive an unexpected expense or a period without a paycheck made every other financial decision easier. Only after that safety net was securel...

TL;DR: Like many software engineers, I solved my retirement planning problem the obvious way: I built a custom financial model in a spreadsheet. Instead of tracking daily market noise, this model aggregates long-term trends, separates W-2 and 401(k) investment pipelines, and uses conditional formatting to track the only metric I truly care about—compounding passive dividend income. Here is the architecture behind it. Like many software engineers, when I first confronted the problem of long-term asset allocation and retirement math, I solved it the most obvious way possible. I built a spreadsheet. I’m convinced creating custom tracking models is a fundamental occupational hazard for developers. It wasn't because I enjoy tracking data points for the sake of it; the spreadsheet was spun up to answer one deceptively simple question: Am I on track to retire with a sustainable runway? That question has been at the core of my investing journey from day one. I knew I couldn't predict ...

TL;DR: MJ DeMarco’s The Millionaire Fastlane argues that true wealth requires decoupling your income from your time. While the book heavily champions entrepreneurship, high-earning tech professionals face a unique variable: replacing a six-figure W-2 salary with a side hustle is incredibly difficult. Here is how I refactored the book's core philosophy to turn a software engineering salary into a passive asset-building engine. 📖 Book: The Millionaire Fastlane by MJ DeMarco If you'd like to read it yourself, you can find it here (affiliate link): https://amzn.to/4eGOLcr Like most people in the corporate world, I earn money by working a traditional job. Every two weeks, I receive a paycheck in exchange for the time, code, and system architecture I provide to my employer. There is absolutely nothing wrong with that path. In fact, a career in technology has provided me with financial opportunities and capital allocation options that many people never get. But reading The Milli...

TL;DR: I uploaded my investment holdings into ChatGPT to see if an AI portfolio analyzer could provide genuine financial insights. While the AI successfully identified my dividend-growth strategy and flagged key allocation risks, it completely missed a major blind spot because it lacked external context about my overall career compensation (RSUs). AI is an incredible tool for portfolio reviews—but it can only analyze the data you give it, not your entire financial life. We seem to be living in the absolute peak of the AI cycle. Every single week brings a new model deployment, a new application, or another headline claiming that machine learning is about to disrupt yet another legacy industry. Naturally, I started wondering whether large language models (LLMs) could provide useful, data-driven insights into something I spend a lot of time engineering: my investment portfolio. So, I decided to test it. I uploaded my raw portfolio spreadsheet into a custom ChatGPT environment tailored f...