Who gonna win the AI race? - Anthropic - OpenAI - Gemini - Deepseek - Manus

The season finale of the CODE Challenge is out Every note Carolina, Edvardo, and Ethan have captured, organized, and distilled exists for what happens this week Express is the step where a Second Brain has to produce something the rest of the world can see, use, or buy

.@ElegantSnowWhit "Distribution density compounds" — 100%. We learned this the hard way. Paid a single KOL, got zero registrations. Then shifted to seeding 30 smaller voices who genuinely used the product. Result? 80% of our open source growth came from organic word-of-mouth, not any single big influencer. The old playbook of "find ONE big influencer" is 2022 thinking. In 2026 it's about building a network of genuine advocates.

AI doomerism exists, in part, because solutions to our most important problems still remain unsolved while examples of superficial process automation abound. We’ve lost the script. If AI wants to be celebrated, it should put solutions to some of society’s greatest problems at the front of the line. Case in point…why hasn’t anyone focused on an AI for fixing the growing illiteracy of our children?

The fallacy of this is that more creates more. More hours, more hiring, more something. And it is true in a sense. If you put in more work, more work will happen. But I think for most startups, the leverage is really in how differently you approach the problem, how well you cultivate your team, and the strategy. Any large company can outspend you on hours. They have thousands or tens of thousands more people, spending more hours. If hours worked were the metric, every large company and government organization would always win and do the best work. More hours, better output. This thinking is often representative of younger founders, where the startup becomes their identity and life. They have a hard time doing anything else, and cannot understand that your work is not the person that is you. But activities outside of work can grow you as a person too and make you do better work. I’ve never worked this way. As a designer, I always saw the need to take a step back, to take a break. At times, I might work 12 hours or 16 hours, or whatever amount was needed, but it wasn’t the norm. You just can't grind design, you need inspiration. But taking that step away from the work, would give me more perspective, inspiration and I could approach the problem differently or I could just see the solution. Grinding is never good for any creative problem, and startups or creating new products are often mostly about creative problem solving. Grinding works ok for email jobs, or where you just executing on very clear playbook. With Linear, we’ve never worked this way. We work reasonable hours, 5 days a week. All of us founders have families. Many of our employees have families. I personally stop every evening, spend time with the family, cook dinner for the family, eat dinner together, and focus on things outside of work. Sometimes I work in the late evenings or weekends, but to me the pride is that I don’t need to. Company should be succesful without it. My goal is to build a company that is sustainable in the long term, and doesn’t require heroics or personal sacrifices every single day. There are times when our team is heroic. Launches, incidents, some other work that just needs to be done. They will work late into the night because they know it is the right thing. But we don’t require that every day or every week, and the more this happens, the more I think it is a failure of our company and leadership. The team and the leaders should always keep a reserve to use when something is needed. Our thinking was also that quality, which we value, doesn’t emerge from working more or stressing people more. It emerges when you create the conditions for it to emerge. Often it is the appreciation, space, time, and how the person feels. A person who is rested will do better work. I wouldn’t attribute much of our success to working a lot. The success came from having clear thinking, ideas, and focus to do the right things. I sometimes wish we could move the culture more toward a Zen master. Real mastery is not exerting the most effort. It is achieving the outcome with the least necessary effort.

A rational conversation on where AI is actually going with @benedictevans For 20 years, Benedict has been one of the clearest, most reliable thinkers on where technology is heading, and how it'll impact our lives. He was @a16z's resident "thinker" for 5 years, and has spent the last six as an independent analyst tracking the most important tech trends. As you’d expect, he’s spending all of his time on AI. In his words, "AI is eating the world." We discuss: 🔸 Where value will actually accrue in the AI stack 🔸 Why AI labs are suddenly buying consulting firms 🔸 The rise in anti-AI sentiment, and where it leads 🔸 Why distribution is becoming the ultimate moat 🔸 Why the right question about your job isn’t “What percent can AI do?” but “Is this a task or a job?” 🔸 Why things will probably be okay Listen now 👇 youtu.be/BD3vLtWhT5A

Thought experiment: if every company suddenly had infinite free compute, what new products would emerge? My take: with very few exceptions, not much would change. The bottleneck is figuring out what people want, and it’s not so easy to apply compute to solve that.

IMO deep research has been ~dead since o3 and interactivity was always more impt for active learning and eliciting intention thoughtless prompt -> long ass report nobody reads is inferior to read -> think -> ask -> read -> think -> ask

Noticing an interesting version of gell-man amnesia where people use AI for their job and see all the various things they have to do in the “last mile”, but then look at someone else’s job and think that AI will eliminate it immediately. We all have a much deeper appreciation for the nuances and complexities of the work that we do every day. We run into issues about accessing data, we know how much context is needed to get AI models to work the way we need, we have to review the output of the AI to make sure it’s accurate, and then we have to incorporate that work into some broader business process. We see all those steps deeply for the work that we do. Then, a moment later, we see AI do something in a foreign space and think that it can go automate that entire function. We tend to dramatically underestimate the work that goes into making the AI work just as effectively in those jobs. This is reason to be skeptical about many of the theories of job loss. It’s coming from the lens of being able to automate individual tasks with AI, without understanding all the work that goes into doing the job fully.

🚀 Introducing Canva AI 2.0: our biggest product launch to date, and the most significant shift for design in a decade. For the first time, imagination is the starting point. Read more: bit.ly/4cm5Zuy

Today we’re introducing two big steps for health at OpenAI: - ChatGPT for Clinicians, a free version of ChatGPT designed for clinical work - HealthBench Professional, a new benchmark to evaluate real clinician chat tasks We’re excited about what this can unlock for care. ❤️