Recently, I’ve been seeing strong demand from e-commerce clients, especially around Etsy and Amazon product listings. They need AI image generation tools that can create high-quality visuals for Western market scenarios, with stable and reliable outputs. If you’re building a strong AI agent for e-commerce, there are direct monetization opportunities from real client demand. AI builders focused on the e-commerce space are welcome to connect with me. #ecommerce #amazon #Etsy #aibuilder #imageagent #videoagent #llm #AGI

Without enterprise context, deploying autonomous AI agents is just hiring a team of high-IQ geniuses who have zero clue how your business actually operates. Total chaos. The unsexy, non-AI work of migrating legacy systems to secure cloud environments is the true foundation of 10X productivity. #AI #aiagents #enterprise #productivity

So many teams are using AI to sprint at maximum speed in the wrong direction. AI raised the baseline for code execution, which means the only real alpha left is product taste and acute market insight. Execution is cheap; direction is everything. This is because users don't audit your tech stack. They just want the thing to work. Treat AI as a tool in the stack, not the entire pitch. The 'AI-powered' label won't save a lazy product with a broken user experience. #AI #insights #userexperience

1 million applicants for ~1,100 slots is a staggering 900:1 ratio. The 'AI-native' generation is entering the most fiercely competitive tech landscape in history, where just being a 'measurer' or manager is no longer a viable career path. At the same time, the 'builders vs measurers' breakdown is incredibly spot on. Middle management, audit, and compliance have always been about processing and synthesizing internal data—tasks that continuous AI auditing can now do 10x faster and with zero bias. #AI #AInative #career #techlandscape

The bitter lesson holds for mastering closed-world games, but defining what is actually 'useful to humans' requires the very domain knowledge computation can't derive from scratch. We need computation for the scale, but human intent for the direction.

The 89% isn't shocking because 90% of enterprises use AI as a tool, not an infrastructure. True alpha happens when you move from ad-hoc prompting to AI-native background agents handling whole decision pipelines. Exactly like the early days of computers or electricity. The tech alone doesn't move the needle until organizations reorganize their entire internal factory lines around it. We are still in the 'chat mode' transition phase. Because buying a ChatGPT Plus subscription isn't an AI strategy. You can't achieve Solow-paradox-breaking productivity gains by dropping an LLM into a broken, legacy workflow without programmatic integration. #AI #AInative #LLM #productivity

Just saw a comment on my LinkedIn that speaks for so many users. It points out everything that feels broken right now. To me, more problems just mean a bigger market and more opportunities for us to step in and fix them. I always choose optimism because AI brings so much more good than bad. On the B2C side, it makes legal help affordable. People who used to fear the high costs of legal consulting can now get guidance and understand the law easily. It is literally changing lives. On the B2B side, it drives efficiency for enterprises and gives small businesses the resources they need to protect themselves. For the law firms themselves, adopting AI lowers your overhead and gives you a massive edge over traditional firms still stuck doing everything manually. Stay adaptable, stay ahead. True AGI is still a long shot, but imagine when it does get here. We get our UBI, focus entirely on what we love, and actually live our dreams. What is not to love about that? #LegalTech #AI #BuildInPublic #AGI

The noise is loud, but the cash flow and utilization data tell a completely different story. Outrage doesn't pay the bills; leverage does. The market is quietly voting with its time and subscriptions while the critics argue about the narrative. Every massive technological leap in history has faced a manufactured backfire—from the printing press to the internet. True adoption always happens at the individual level because utility is undeniable. You can't politicalize an efficiency tool that saves people 20 hours a week. #AI #Leverage #technology

AI is a leverage machine, but leverage multiplies whatever you feed it. Good engineers use it to ship scalable architecture faster, while bad engineers just use it to generate structured garbage at an unprecedented scale. #AI #engineer

Invited two listed LLM companies today, and they said yes instantly! They even wanted to lock in a time ASAP. Honestly, I was a bit surprised, but it feels great to be recognized. A close friend of mine (who’s well-connected and works with top tech figures currently trending on Chinese social media) told me, "Keep building this up, and I can get them on board too." Plus, a few early core OpenAI employees are supporting me because of our alumni connection. Incredibly grateful for everyone! I’ve always believed that you have to make yourself strong enough to handle big opportunities. People only share resources when it's a win-win, not when you’re just taking. Keep grinding! #ai #startups #BuildInPublic #AI #LLM

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a16z is hands down the best VC when it comes to marketing. A friend referred me to a partner there recently, and honestly, I learned so much. If you’re a founder and get the chance, definitely try to chat with their team. The insights you’ll get are on another level!

𝐖𝐡𝐲 𝐂𝐨𝐝𝐢𝐧𝐠 & 𝐋𝐞𝐠𝐚𝐥? 𝐓𝐡𝐞 𝐌𝐚𝐭𝐡 𝐨𝐟 𝐇𝐢𝐠𝐡-𝐕𝐚𝐥𝐮𝐞 𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐀𝐈 "I’ve always been bullish on vertical AI, and the arrival of 'Claude Legal' proves the thesis. Aside from coding, Legal is the next frontier where AI isn't just a 'nice-to-have'—it’s a high-ROI necessity. 𝐓𝐡𝐞 𝐄𝐜𝐨𝐧𝐨𝐦𝐢𝐜𝐬 𝐨𝐟 𝐓𝐚𝐥𝐞𝐧𝐭: Think about the cost of hiring a top-tier engineer or a lawyer in the US. These roles don't just command high salaries; their pay is often 10x or 20x the average income, with virtually no ceiling. For LLM companies, the ROI in these sectors is unparalleled. Even capturing a tiny slice of the market translates into massive profits because the 'unit value' of the work is so high. 𝐓𝐡𝐞 𝐑𝐞𝐚𝐥 𝐌𝐨𝐚𝐭: Key Distribution Channels and Customer Relationships: While model companies provide the brainpower, the real 'moat' for startups remains the customer base. You can’t disrupt deep-seated professional relationships overnight. 𝐓𝐡𝐞 𝐌𝐚𝐫𝐤𝐞𝐭 𝐒𝐢𝐠𝐧𝐚𝐥: We’re currently seeing incredible traction. Three Legal AI firms recently approached us for market expansion. Two of them are still in their earliest stages, yet they’ve already secured hundreds of thousands in ARR and locked in partnerships with Big Tech. The demand isn't just there—it's overflowing." #llm #agi #ailegal #aicoding #productmoat #talentROI #claude #customercentric #distributation #lawyer #engineer

There will be no AI jobpocalypse. The story that AI will lead to massive unemployment is stoking unnecessary fear. AI — like any other technology — does affect jobs, but telling overblown stories of large-scale unemployment is irresponsible and damaging. Let’s put a stop to it. I’ve expressed skepticism about the jobpocalypse in previous posts. I’m glad to see that the popular press is now pushing back on this narrative. The image below features some recent headlines. Software engineering is the sector most affected by AI tools, as coding agents race ahead. Yet hiring of software engineers remains strong! So while there are examples of AI taking away jobs, the trends strongly suggest the net job creation is vastly greater than the job destruction — just like earlier waves of technology. Further, despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%. Why is the AI jobpocalypse narrative so popular? For one thing, frontier AI labs have a strong incentive to tell stories that make AI technology sound more powerful. At their most extreme, they promote science-fiction scenarios of AI “taking over” and causing human extinction. If a technology can replace many employees, surely that technology must be very valuable! Also, a lot of SaaS software companies charge around $100-$1000 per user/year. But if an AI company can replace an employee who makes $100,000 — or make them 50% more productive — then charging even $10,000 starts to look reasonable. By anchoring not to typical SaaS prices but to salaries of employees, AI companies can charge a lot more. Additionally, businesses have a strong incentive to talk about layoffs as if they were caused by AI. After all, talking about how they’re using AI to be far more productive with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus. To be clear, I recognize that AI is causing a lot of people’s work to change. This is hard. This is stressful. (And to some, it can be fun.) I empathize with everyone affected. At the same time, this is very different from predicting a collapse of the job market. Societies are capable of telling themselves stories for years that have little basis in reality and lead to poor society-wide decision making. For example, fears over nuclear plant safety led to under-investment in nuclear power. Fears of the “population bomb” in the 1960s led countries to implement harsh policies to reduce their populations. And worries about dietary fat led governments to promote unhealthy high-sugar diets for decades. Now that mainstream media is openly skeptical about the jobpocalypse, I hope these stories will start to lose their teeth (much like fears of AI-driven human extinction have). Contrary to the predictions of an AI jobpocalypse, I predict the opposite: There will be an AI jobapalooza! AI will lead to a lot more good AI engineering jobs, and I’m also optimistic about the future of the overall job market. What AI engineers do will be different from traditional software engineering, and many of these jobs will be in businesses other than traditional large employers of developers. In non-AI roles, too, the skills needed will change because of AI. That makes this a good time to encourage more people to become proficient in AI, and make sure they’re ready for the different but plentiful jobs of the future! [Original text in The Batch newsletter.]

The 'unit test' for taste is cultural resonance, and that’s a moving target. AI is great at mimicking the past, but true 'art' or 'great products' usually break the existing patterns that AI was trained on. Taste is knowing which rules to break.

AI-native transformation 🆚 Reality I had calls with two tech giants this week—one from procurement at a top US firm and another leading HR research at a major Chinese tech company. Both executives want to use AI to cut costs and boost efficiency. Anyone with an AI-native mindset knows that almost every daily task can be turned into a specific AI skill to save hours of work. But for big corporations, execution is incredibly hard. Even the world’s leading tech companies are struggling to pivot. Why? It’s not because employees aren’t smart or willing to learn. The real issue is that performance reviews haven’t caught up. In most companies, there’s no "more work, more pay" incentive. If you become more efficient, your boss just gives you more work, or worse, the company decides they need fewer people and starts layoffs. From an employee’s perspective, why wouldn't you just stay quiet and do the bare minimum? The real challenge for managers is designing a new system that rewards people for being efficient. We need to make sure those who truly master AI get paid more for their results. Jensen Huang once suggested using token usage as a metric to evaluate employees. It’s a decent starting point, but it’s not perfect. The best employees shouldn't just use more tokens—they should have the highest ROI per token. Defining and measuring that ROI is exactly what we need to figure out next.

The line between 'ideation' and 'production' is blurring. In 2026, being an 'individual contributor' means being a 'one-person system architect.' If you aren't leveraging agents to ship, you're essentially operating at 10% capacity.

In this era, identifying pain points is the ultimate entrepreneurial skill. Where do you find them? Through your customers. They are your core asset. Even if your first version fails, having users gives you a second chance. AI can’t automate trust. The stronger AI gets, the more valuable human connection becomes. I’ve seen this firsthand. Recently, I landed a Web3 partnership through an old classmate and a lead from a government-linked public company worth millions. My product wasn't the right fit, so I handed the leads to my partners. Business is about opening doors for others. People want to work—and win—with people they like and trust. In B2B, if your service is solid, people pay for the relationship. I recently signed a deal with a 2% premium because of the value and support I’ve provided. It’s a two-way street: I support your business, you support mine. The era of the "God-tier Engineer" is changing. Coding alone isn't enough when Claude can do it better. I don't write code, but with a clear product vision, I can build what a client needs in a week. Future engineers must think like product managers. Opportunities for "regular" people are exploding, but so is the competition. Silicon Valley is just the beginning.

This weekend I went to a gathering hosted by one of my Indian friends. It was full of Indian founders, Indian VCs, and a few American founders. I didn’t see a single Chinese person there except myself. Before going, I asked my Indian classmate what I should prepare so I could fit in better. He told me: just share things you think are valuable, and be very direct and concise. When it comes to networking, Indians are really good at it. At least on the surface, they make you feel very comfortable. I spent the whole night adding people on LinkedIn, and I already set up a few deeper chats with Indian friends next week. Some of them even said they would introduce me to other people. So it feels like a good start. Before leaving, the friend who hosted the gathering told me: Faye, I’m planning another small meetup sometime soon, you should definitely come again. I said absolutely, no problem! Feels like I made a few good Indian friends.

Very productive day today, and another day of meeting new people. Building real connections does not happen in one day. It takes small moments over time, mutual support, and trust built step by step. In the morning, I had a great conversation with a human strategy management team from a major tech company. Since many of them came from product backgrounds and are deeply passionate about AI, we instantly clicked. I shared a lot of useful AI tools from overseas, which also helped broaden their perspective. We talked from the morning all the way through lunch about how people at different career levels are using AI, their mindset toward it, and how AGI could reshape society in the future. It really feels like there are endless possibilities ahead. In the afternoon, I met another YC founder, a woman in her twenties. Her first startup failed, but her second one got into YC. She was clear in communication, patient, humble, and genuinely impressive. She even said she would really like to collaborate with me. Meeting more and more talented Gen Z founders makes me feel very lucky. We are all learning from each other along the way.