Estelle Metayer @Competia

Perspective...

Paul Graham @paulg

2 months ago

There's never been an investment like the investment in railroads. (This graph has a log scale!)

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Trends, and Weak Signals: Tokenmaxxing, AI dividends, and Beta mums, by @Competia open.substack.com/pub/competia/p…

A painting of the end of meritocracy: A meeting of the two largest economies and not one woman at the table.

We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs andonlabs.com/blog/andon-mar…

Au revoir Nathalie Baye... On se souvient tous de son introduction parlée de ce tube de Johnny Hallyday en 1985, "Quelque chose de Tennessee", écrit par Michel Berger. Elle y lit avec une voix douce et posée un extrait de la pièce "La Chatte sur un toit brûlant" de Tennessee Williams. Quelle élégance...

Dinergoths, robustness, and punk health, by @Competia open.substack.com/pub/competia/p…

World Monitor, a website that turns any browser into a makeshift situation room worldmonitor.app

Trends and Weak Signals: Ghosposting, agrihoods, and aura farming, by @Competia open.substack.com/pub/competia/p…

Trends: ON ALGORITHMIC WAGE DISCRIMINATION columbialawreview.org/content/on-alg…

Trends and Weak Signals: DIYctionary, viral queues, and culture buddies, by @Competia open.substack.com/pub/competia/p…

@Matt_Pinner 37

AI requires a rethink of the apprenticeship model for knowledge professionals  fortune.com/2025/11/13/ai-…

Why Amazon's Anticipatory Shipping Is Pure Genius via @Forbes forbes.com/sites/onmarket…

The future: The US-China AI Companion Race, by @jordanschneider chinatalk.media/p/the-us-china…

ChatGPT Pulse (launched on mobile yesterday) is one of the most impactful features OpenAI has released. It's an agent that continuously researches on your behalf, building on topics from your recent conversations. I'm really having a hard time wrapping my head around this paradigm, because it's truly unlike anything we've seen before. It's like having a knowledge partner that follows you around, deepening your understanding of whatever you're curious about. Imagine learning a new cooking technique only to have your AI expand on that the next morning with related techniques, science, and cultural context. It's part AI tutor, part personalized journalism. The content feels like a thoughtful third party article, except it's written specifically for you. We're essentially getting our own custom publications now. What if Wired or the WSJ had a dedicated team writing exclusively for your interests and curiosity gaps? That's what this feels like. Wild times ahead.

Welcome Rocki, and congratulations to the mum for her choice of a beautiful watch 😉 #royaloak #audemarspiguet

Rihanna @rihanna

9 months ago

Rocki Irish Mayers Sept 13 2025 🎀

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Someone figured out a surprisingly simple way to make AI agents better at their jobs: just give them a personality. I just read a paper on "Psychologically Enhanced AI Agents," and it's a fascinating look at how we can steer AI behavior without any complex or expensive retraining. Here's the context: Normally, if you want an AI to be good at a specific task (like creative writing vs. strategic analysis), you have to do costly and time-consuming "fine-tuning." The problem is that a generic, one-size-fits-all AI often isn't the best fit. A model optimized for factual recall might not be great at generating an empathetic, emotional story. The key finding is a framework called MBTI-in-Thoughts. By simply telling an LLM to adopt a specific Myers-Briggs (MBTI) personality type in its prompt, its behavior changes in predictable and useful ways. For example, in a strategic game: "Thinking" (T) type agents chose to defect nearly 90% of the time. "Feeling" (F) type agents were more cooperative, defecting only about 50% of the time. This was achieved with just a prompt, no fine-tuning needed. What makes this so interesting is its unexpected simplicity. The ability was there all along, latent within the model. The prompt just acted as a key to unlock it. To make sure it wasn't just a fluke, the researchers had the primed AI take the official 16 Personalities test. The AI's answers consistently matched the personality it was assigned. It truly "became" that type for the task. This completely changes how I think about prompt engineering. It’s no longer just about what you ask the AI, but who you ask the AI to be. The practical applications are immediate: Need an AI for empathetic customer support? Prime it as an ISFJ ("The Defender"). Need one for ruthless market analysis? Try an ENTJ ("The Commander"). You can match the agent's "aptitude" to the task at hand. The broader implication is a future where we move away from monolithic AI models. Instead, we could build diverse teams of AI agents, each with a personality tailored to its specific role. Imagine a creative "ENFP" agent brainstorming with a logistical "ISTJ" agent to plan a complex project. It raises a new question: what's the optimal personality mix for solving a given problem? Ultimately, this research points toward a future of more versatile, capable, and aligned AI. We're learning that we can shape not just an AI's output, but its entire cognitive and affective style for a task. A simple prompt can unlock a whole new dimension of behavior.

OpenAI JUST released how people are using chatgpt each bar in this chart is a billion-dollar wedge if you build the right verticalized, trust-rich AI startup: 1/ tutoring + teaching (10.2%) - people want on-demand teachers more than almost anything else. a personal ai tutor that explains things your way, remembers your progress, and nudges you daily. 2/ how-to advice (8.5%) - this is consumer SaaS for micro-niches: “how to fix my resume,” “how to meal prep,” “how to set up my Shopify store.” every “how-to” is a wedge into a vertical AI agent. 3/ personal writing + editing (18% combined) - 8% of traffic is people asking AI to write emails, 10.6% is editing or critiquing text. this is demand for AI copilots inside every workflow tool: sales, legal, HR, PR. 4/ health, fitness, beauty, self-care (5.7%) - validated consumer wedge. people already trust AI with their bodies. AI trainers, AI nutritionists, AI skin coaches — with a human layer for accountability. note: btw if you like seeing ideas/trends like this, you'll like @ideabrowser (free/paid plans) 5/ purchasable products (2.1%)- tiny % but huge monetization. people literally asking AI what to buy. the Amazon affiliate model gets reborn here. whoever builds the “AI-powered shopping layer” owns the new SEO. 6/ translation (4.5%)still unsolved. what people want isn’t raw translation, it’s contextual translation: tone, culture, slang. AI that doesn’t just translate but localizes your intent. 7/ computer programming (4.2%) - we know this, but it’s worth underlining: devs want copilots. the non-obvious play is vertical code copilots... Shopify dev copilot, Unreal Engine copilot, etc. TLDR; every bar is a behavior that people are already paying for elsewhere. translate those behaviors into vertical ai agents and startups. the data doesn't lie.

Mboko d. Naomi Osaka 2-6 6-4 6-1 in Montreal VICTORIA IS A WTA 1000 CHAMPION. She beat FOUR Grand Slam Champions en route to the trophy. Came back from a set down in her last 2 matches. Saved match point against Rybakina. Won her first-ever title in front of her home crowd. All at 18 years old. As much as this sounds like a fairytale, it isn’t. It’s pure god-given talent & an enormous amount of hard work. The best story in sports right now. 🇨🇦❤️