Opportunity Costs It’s never easy to discover that a product you’ve poured your heart, sweat, and tears into isn’t working out. Startups operate in constant ambiguity, and sometimes you can’t see light at the end of the tunnel after toiling away for what feels like an eternity. Sometimes there simply is no light.
I’ve heard the phrase “Take more market risk when you are young, and more execution risk when you are older.” As I understand it, this suggests that people early in their careers should bet on markets and opportunities, even contrarian ones. I’m reflecting on this because I’ve been thinking deeply about how to best allocate my time and energy on the most promising projects. This isn’t about diversifying—I recognize my limited attention span, and pursuing everything simultaneously leads to burnout and mediocre results. Hence this post: an attempt to provide clarity.
Every now and then I come across some article or discussion that just feels plain and mundane. All the words seem to make sense, yet at the same time, they feel almost predictable. Despite how well articulated these ideas were - be it in carefully formatted slide decks or confidently delivered proses - they fail to amaze. Ever since November of 2022, the ability to articulate words cohesively (I’m purposefully not using the word coherently) has become table stakes. In a society where frankly most work is evaluated on completion and length, LLMs have led to a rapid advancement of productivity. Yet I think we should make certain clarifications here - productivity gain is in automating repetitive and redundant tasks, this does not apply to all tasks, in fact, using GPT for sophisticated reasoning is almost guarenteed to produce mediocore results.
When you build a product with 10k or 100k users, it’s a matter of skill. But when you are planning to build a product with 1 million or 10 million users, luck is a factor that one cannot neglect. During my short time of working at ByteDance (Gauth, TikTok), I caught glimpses of what the early days of the company looked like. However, as the company grew, the early product culture slowly diluted. What does it feel to have worked at such a company during the early days, and how does one go about finding such a company? This is the question that I’ve been repeatedly thinking about recently, and trying to figure out through writing this post.