There was a time when I thought credit cards were simply tools for paying now and settling later. Later, as I began viewing everything through the lens of an engineer—if I had to spend money, why not optimize the cash flow?—I started exploring cashback rewards. And so, from one initial card, I gradually built a dedicated “stack” for each category of spending. 😅 Not to show off how many cards I have. But like building a tech stack: each tool should only do what it does best. My current setup looks roughly like this: - Laptop / Online: VP Step Up – 15% - Transportation / Dining Out / GrabMart: Sacombank Bạch Kim – 16.8% - Supermarkets: Sacombank Uniq – 20% - Food & Beverage: Momo mDigi – 20% - Travel: Sacombank Amex – 20% - Electronics: Cake Premium – 20% - Entertainment: Selected MB/VIB cards – 8–12% I keep a few other cards as backups or for when my primary cards hit their cashback limits. In Web2, I learned how to optimize performance. Through AI, I learned how to optimize workflows. Through Web3, I’ve started paying closer attention to ownership and how cash flows operate. And in real life? I’ve started optimizing my card swipes too. 😂 In the end, cashback rates of 10%, 15%, or even 20% won’t make me rich. But they’ve cultivated a fascinating mindset: Money you don’t optimize is money you leave on the table. #CreditCard #Cashback #PersonalFinance #Optimization #AIEngineer