Entrepreneurship

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. ...

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. ...

In a world dominated by expert opinions and algorithm-driven content, there’s something fundamentally human about wanting to know what others think. Whether we admit it or not, we’re drawn to understand the collective mindset. There’s wisdom in crowds. While large groups may not always converge on absolute truths (in fact, many truthful views begin as contrarian positions), they provide something equally valuable: comfort and context. Being part of a group, understanding its thoughts and values, creates a sense of safety and belonging that’s deeply wired into our social nature. Even when we disagree with mainstream opinions, understanding them helps us navigate social landscapes and provides reference points for our own thinking. This isn’t mere conformity—it’s about contextualizing our experiences within the broader human narrative. ...

Tobi Lutke’s Shopify internal memo Smaller and More Efficient Teams When should we hire a person versus delegating to AI? Recently I’ve been more reluctant towards hiring people as an attempt to build mid sized projects. Yes, the codebases would get pretty big, and there’s also tasks involved that I wouldn’t say are my forte exactly. Yet, when I think about the meetings I have to sit through communicating what I want to build and just time spent doing filler work, I get more and more inclined towards just doing it myself. It’s not to say that teamwork isn’t good work, some of the most creative product ideas I’ve worked on stemmed from chats, during lunch breaks, exploring tangents, with engineers, journalists. The value of connecting the dots during these conversations is something that is difficult to replace. However, is the assumption that delegating work means higher productivity still valid? After all, the cost of execution is continually decreasing (as long as we have a clear idea of what to build). ...

Here’s a list of articles that I founding interesting. I’ve attached the original article / transcript for easy refernece as well. Gary Tan on Manus: The New General-Purpose AI Agent Video URL: https://www.youtube.com/watch?v=JOYSDqJdiro Usable AI agents are finally here from deep research platforms out of OpenAI and Google to similar tools from XAI and DeepSeek. Joining the competition now is Manus, a brand new agentic AI platform that has taken the world by storm. ...

When you want to look for user pain points, go to a bar in the middle of the week, look for the most desparate looking person and buy them a beer. They’d probably have something substantial to talk about. While I don’t usually go to bars during weekdays, I’ve found some similar ways of identifying user needs, mostly through conversations or online forums. This is a running document of the user needs or pain points that I’ve found to be interesting. Perhaps some of them will turn out to be viable business oppportunities. ...

This week, I wanted to organize my thoughts about AI-generated content (AIGC) and creativity-related products from the past few months. Rather than focusing solely on my own projects, I’d like to explore the foundational aspects of AI product design, interspersing examples from my recent work. First, I want to emphasize that technology is merely a tool intended to better serve business needs. If it doesn’t significantly improve efficiency, traditional methods may be more appropriate. Second, despite the many imaginative possibilities of current technology, applications should ultimately be guided by user needs. Finally, AI technologies and markets evolve rapidly, making predictions difficult to validate, but exploring content understanding and generation remains an intriguing challenge. ...

Multi-agent system for cross boarder e-commerce sales automation. Co-founder and head of product. https://cognogpt.com Cogno+ is dedicated to revolutionizing global e-commerce by empowering brands with AI-driven assistance that offers seamless, personalized customer experiences. Our mission is to serve as the digital bridge between brands and customers, enhancing interactions and transactions across international markets, and allowing the brand to increase conversion and upsell while reducing time and money spent on manual customer service. ...

Developing capable multi-agent systems for complex reasoning and human-AI collaboration Single-agent AI systems have limitations in handling complex tasks that require diverse perspectives and specialized knowledge. Multi-agent architectures can enable more sophisticated reasoning, problem-solving, and collaboration capabilities.

Inspiring insights, amplifying voices. (crowdlistening.com) From Content Aggregation to Original Research Crowdlistening transforms large-scale social conversations into actionable insight by integrating llm reasoning with extensive model context protocol(MCP) capabilities. While being able to quantatively analyze large volumes of data is already an interesting task, our focus is not just on content analysis at scale, but rather conducting original research directly from raw social data, generating insights that haven’t yet appeared in established reporting. ...