Alan Vazquez, CFA

Definirse es limitarse.

Anthropic AI engineer just showed how to give AI agents real memory in 4 steps - and it changes everything in 28 minutes he shows exactly how agents can remember across sessions, completely free worth more than any $500 AI engineering course here's what he covers: • why agents forget everything between sessions • memory stores - agents read, write across sessions • dreaming - agents that improve their own memory • 95% cache hit rate, so it stays cheap most people are still copy-pasting context into every new chat - while the people who figured this out are building agents that get smarter every single night watch full video then read article below

Jane Street, Goldman Sachs, JP Morgan, BlackRock, Hudson River Trading, Two Sigma, D.E. Shaw. The most expensive engineering teams in the world released their financial tools on GitHub. Here are 7 repos, one from each. 1. Jane Street, janestreet/magic-trace github.com/janestreet/mag… 5.3k stars. Process tracer powered by Intel PT. When your profiler is blind, magic-trace sees every CPU instruction. 2. Goldman Sachs, goldmansachs/gs-quant github.com/goldmansachs/g… Derivative pricing the GS traders use at their desks. MIT licensed. 3. JP Morgan, finos/perspective github.com/finos/perspect… What JPM traders use to watch markets in real time. A $24k/year terminal, for free. 4. BlackRock, blackrock/lcso github.com/blackrock/lcso Rust optimizer for portfolio problems. Where scipy gives up, this works. 5. Hudson River Trading, hudson-trading/corral github.com/hudson-trading… Structured concurrency for C++20. The foundation of HFT infrastructure at one of the largest U.S. trading firms. 6. Two Sigma, twosigma/flint github.com/twosigma/flint Time-series joins on Apache Spark with temporal tolerance. Built for billions of ticks. 7. D.E. Shaw, deshaw/pyflyby github.com/deshaw/pyflyby Auto-import for IPython and Jupyter. D.E. Shaw also funded the development of IPython itself. Bookmarked it

@CepnikMaciej Not peso strenght but dollar weakness. MXN is thetering at the brisk of abysm if current administration fails (likely) to take actions against its narco goverment.

Okay, if this keeps going, some expats might actually have to move out of La Condesa… To be serious, I don’t get it, the Mexican economy is not doing so great, it’s GDP contracted by 0.8% in the first quarter of 2026

🚨 Guarda esta MASTERCLASS El profesor de Stanford Graham Weaver dio una conferencia sobre cómo DESTRUIR EL MIEDO y vivir una vida ambiciosa. En el vídeo (32 minutos que he subtitulado al español) explica las claves para superar el miedo, dejar de jugar a la defensiva y diseñar un destino ambicioso. 4 LECCIONES sobre cómo construir una vida asimétrica: 1. Haz cosas difíciles (Do hard things) El miedo suele disfrazarse de lógica para mantenernos en nuestra zona de confort. Todo cambio positivo pasa por una etapa inicial donde las cosas empeoran antes de mejorar (worse first). Para alcanzar lo que deseas, debes avanzar directamente hacia aquello que estás posponiendo o que te genera temor 2. Sigue tu propio camino (Do your thing) Intentar cumplir los sueños de otra persona es una garantía de fracaso. El sufrimiento es inevitable en cualquier trayecto de la vida; la clave radica en elegir un proyecto o causa por la que realmente valga la pena luchar. El potencial de una persona se multiplica de forma drástica cuando opera bajo el motor del entusiasmo y la auténtica motivación. 3. Mantén el enfoque durante décadas (Do it for decades) Los logros extraordinarios requieren tiempo y constancia a largo plazo. El factor más determinante para el éxito es la constancia; casi ningún obstáculo puede resistir a una persona decidida que mantiene su energía enfocada durante 10 años o más. 4. Escribe tu propia historia (Write your story) No permitas que la inercia o las expectativas externas dicten tu futuro. Diseña de forma explícita el rumbo que deseas para tu vida, atrévete a pedir lo que quieres y toma acción inmediata para construir esa realidad

INSTEAD OF WATCHING AN HOUR OF NETFLIX TONIGHT. This 1 hour Stanford lecture by Joel Peterson will teach you more about negotiation and getting what you want than most people learn in years. Bookmark it and give it an hour, no matter what.

This 26 minute breakdown from a Google Cloud AI engineer shows how they go from idea → deployed app using Claude. One person + Claude + Google Cloud = a full engineering org running on a laptop. Worth more than any $500 vibe coding course.

Where will AI be in 1, 2 or 3 years?

INSTEAD OF WATCHING AN HOUR OF NETFLIX TONIGHT. This 60-minute Cambridge lecture by Demis Hassabis will teach you more about the future of AI than most people will learn in the next 5 years. Bookmark it and give it an hour, no matter what.

50 pessoas. $2 bilhões de dólares em receita. Zero product managers. A Cursor gera mais receita por funcionário do que Goldman Sachs, Google e Apple combinadas. E o CEO acabou de entregar o playbook inteiro de graça. Cada engenheiro da Cursor ganha entre $808 mil e $1,1 milhão por ano. E os engenheiros não escrevem mais código. Eles gerenciam dezenas de agentes de IA rodando em paralelo, cada um em sua própria VM na nuvem, 24 horas por dia. Enquanto o engenheiro dorme, os agentes continuam entregando. Nesse vídeo o CEO explica em 9 minutos como eles fazem isso. Salve este post antes que todos copiem o manual. Os números: 1. 35% dos PRs mergeados na Cursor são criados por agentes autônomos 2. Em março de 2025, pra cada usuário de agente tinha 2,5 no autocomplete. Hoje inverteu: 2 de agente pra cada 1 de autocomplete 3. Uso de agentes cresceu 15x em 12 meses 4. Os engenheiros mais produtivos têm 100% do código escrito por agentes O ciclo mudou. Humanos definem escopo e revisam. Agentes planejam, codam, testam e abrem o PR. Validação antes do código, não depois. 50 pessoas entregando o que empresas com 5.000 engenheiros não conseguem. O que surgiu ali não é ganho de produtividade. É uma nova classe de trabalhador: o engenheiro que não programa. Toda empresa que ainda avalia engenheiro por linhas de código ou horas na cadeira está rodando com o modelo mental de uma fábrica do século passado. O novo indicador é quantos agentes autônomos você consegue orquestrar ao mesmo tempo. Quem entender isso primeiro vai ter uma vantagem competitiva impossível de superar.

The 36 BIGGEST startup opportunities right now 1. biggest b2c: solving loneliness. third spaces, community apps, IRL 2. biggest b2b: managed AI employees for businesses 3. biggest overlooked: elder tech. 70 million boomers who want products that make them happier & healthier 4. biggest mobile: action apps that do things, not apps you stare at 5. biggest trades: matching platforms for electricians, plumbers, HVAC. supply shrinking 6. biggest consumer social: small social. group chats as products, no feeds, no ai slop 7. biggest ecommerce: agents that recommend products you'll like, shop, buy for you 8. biggest creator: live shows and unscripted content 9. biggest edtech: AI tutors that adapt through conversation 10. biggest SaaS: pay-per-outcome pricing 11. biggest auto: AI service advisor for dealerships. answers the same 15 questions 24/7 12. biggest talent: training non-technical people to operate agents 13. biggest boredom: curated offline experiences delivered to your door. kits, games, challenges. anti-screen products 14. biggest spiritual: the need for belonging is exploding, new formats of spiritual get togethers 15. biggest wellness: longevity biomarkers you actively manage 16. biggest mobile: action apps that do things, not apps you stare at 17. biggest one to solve ai slop: digital verification that you're a real human. every platform will need this within 2 years 18. biggest infrastructure: agent permissions, security, audit trails 19. biggest media: AI native media companies. build distribution, sell products later. 20. biggest parenting: family ops automation. forms, scheduling, logistics 21. biggest accounting: bookkeeping agents that charge per transaction 22. biggest fashion: brand-owned resale. every brand wants to control their secondary market 23.biggest hobbies: adult learning for joy. pottery, woodworking, drawing. 24. biggest skincare: at-home diagnostics. scan, get a protocol, track progress 25. biggest agriculture: precision farming tools for small farms. enterprise version exists, family farm doesn't 26. biggest pest control: subscription pest prevention instead of reactive treatment. the model flip that lawn care already made 27. biggest regulated: on-device AI. healthcare, legal, finance open up when data stays local 28. biggest gaming: AI characters with real memory and relationships 29. biggest dating: agent-mediated matchmaking 30. biggest fitness: adaptive coaching that rewrites your program daily 31. biggest travel: autonomous trip planning and rebooking 32. biggest food: personalized nutrition based on blood work and gut biome 33. biggest pet: health monitoring. $140B industry, almost no tech 34. biggest defense: AI-native security and compliance tools 35. biggest robotics: physical AI. $30 brains on existing hardware 36. biggest nostalgia: products that feel analog. vinyl, paper, handmade. counter-positioning against AI everything

Most people talk about Agentic AI. Very few can actually design it. Here’s a simple cheat sheet to design + explain Agentic AI architecture 👇 🎯 Start here ➡️ Define the goal What exactly should the agent achieve? 1️⃣ Orchestration Layer ➡️ The control panel Decides flow, logic, and coordination 2️⃣ Agents Layer ➡️ The workforce Single or multi-agents handling specialized tasks 3️⃣ Tools Layer ➡️ Execution power APIs, web search, databases, external systems 4️⃣ Memory ➡️ The brain Short-term + long-term context storage 5️⃣ Monitoring ➡️ The eyes Track every step, detect issues in real time 6️⃣ Reliability & Failure ➡️ The safety net Retries, fallbacks, human-in-the-loop 7️⃣ Governance & Security ➡️ The guardrails Auth, compliance, audit, data protection 💡 Real insight: Agents alone don’t make systems powerful. Architecture does. If you can explain this simply, you’re already ahead of 90% in AI. ❤️ Like 🔁 Retweet 🔖 Bookmark Follow @MeenakshiYACS for more such posts #AI #ArtificialIntelligence #GenerativeAI #CareerGrowth #Upskilling

Emerging VC Funds Actively Deploying 2026👇 @HaunVentures — $1B across 2 funds @HummingbirdVC — $800M @AforeVC Fund IV — $185M @1752vc — 🚀 @strikervp Fund I — $165M @ZeroShotFund I — $100M target @mantisVC Fund III — $100M @basecasecapital — ~$99M across 3 funds @haystackvc Fund VIII — $85M @2048vc Fund III — $82M @PrecursorVC Fund V — $66M @pax_ventures Fund I — $50M @SevenStars_VC Fund I — $40M @Antifund I — $30M @mtf_vc Fund I — $22M Mischief VC Fund II — $80M A lot of fresh dollars flowing into AI infra, devtools, cyber, defense, vertical AI, and next-gen software.

Jack Dorsey on how every company can now be a mini-AGI:

En 2007, el profesor de Stanford Joel Peterson impartió una clase de 1 hora sobre cómo negociar y obtener lo que quieres. Sus 3 ideas: → Nunca muestres necesidad → La confianza vence a la manipulación → Piensa en términos de relaciones 12 lecciones para negociar mejor:

Here are 10 websites that print money while you sleep. 1. Carrd.co Build a one-page website in 20 minutes. Sell it on Flippa for $500-$2000. People pay this much because they cannot do it themselves. 2. Gumroad.com Upload one PDF. One Notion template. One prompt pack. It sells at 3am while you are dreaming. Zero inventory. Zero shipping. 3. Systeme.io Free funnel builder. Build it once. Run ads to it. Wake up to Stripe notifications. The funnel does not sleep. 4. Payhip.com Sells digital products in 190 countries. Handles VAT automatically. You upload. They handle the tax nightmare. You keep the money. 5. Ko-fi.com 0% platform fee on tips and memberships. Creators are pulling $3-8k/month here while everyone else fights for scraps on Patreon. 6. Sellfy.com Print on demand + digital products in the same dashboard. Design a t-shirt at midnight. It ships itself for the next 5 years. 7. Teachable.com Record one course. Sell it 10,000 times. One creator I follow made $47k from a course she recorded in a weekend two years ago. 8. Beehiiv.com Newsletter platform with a built-in ad network. They place sponsors INTO your newsletter automatically. You write. They sell. You cash out. 9. Lemonsqueezy.com Stripe + Paddle had a baby. Handles global tax compliance so you can sell SaaS to anyone on earth without touching a lawyer. 10. Whop.com Sell access to a Discord, a Telegram, a course, a community. Recurring revenue. The kind that hits your account before your alarm goes off. The difference between people who make money online and people who don't is not talent. It is picking one of these and shipping this week. Save this. Share it with someone who needs it.

My 30+ observations on the greatest opportunities in AI agents right now: And some ideas that are keeping me up at night. 1. The new buyer on the internet is an AI agent. Imagine billions of new customers showing up with money to spend but they only shop via MCP. That's what's happening. No MCP server means you're invisible to the fastest growing buyer on the internet. 2. Every franchise system in America (30,000+) needs an agent layer and none of them have one. One founder per franchise vertical. That's 30,000 businesses waiting. 3. Everyone said "distribution is the only moat" a year ago. Now I'd add that the only moat is distribution plus memory. The company that has your audience AND your agent's accumulated context is impossible to leave. 4. Consumer mobile is more interesting than it's been since 2012. Apps can finally DO things for you instead of showing you things. The next wave of $100M apps are being built right now. 5. The most interesting startup nobody has built is an agent marketplace where you rent access to someone else's trained agent. A recruiter spent 6 months training a sourcing agent on healthcare hiring. That agent is worth renting to every other healthcare recruiter on earth. The agent itself becomes the product. 6. A sorta strange phenomenon that's happening right now is agents are developing preferences. Give the same agent the same task 100 times and it starts developing patterns in how it approaches it. Nobody is studying this yet. But the agents that develop good patterns are worth more than the ones that don't. That's a new kind of asset. 7. Dead internet theory is about to become dead SaaS theory. Half the apps you use will quietly replace their support team, their onboarding team, and their content team with agents. You won't notice for months. Then you'll realize you haven't talked to a human at that company in a year. 8. The most valuable data in the world right now is sitting in the support tickets of small or mid tier SaaS companies. Every ticket is a customer telling you exactly what to build next. Mine this. 9. The most interesting pricing problem nobody has solved is how do you price a product when your costs change every time OpenAI or Anthropic updates their model pricing? Your margins can swing 40% overnight based on a decision made in San Francisco. The company that builds dynamic pricing infrastructure for agent-based businesses solves a problem every AI company has. 10. The best AI products feel like they're reading your mind. The worst ones feel like filling out a form with extra steps. 11. An interesting arbitrage I've noticed lately is hiring a human VA for $20/hour to supervise an AI agent that does $200/hour work. The human just checks the output. 12. The managed AI agent business is becoming the new agency model. $5k/month per client. You build it, run it, maintain it. The client gets a digital employee they never have to think about. This will be a $50 B+ category. 13. The first "shadow agent" scandals are about to drop. Employees running personal agents on company infrastructure without telling anyone. Using company API keys. Agents accessing internal docs. IT departments have little visibility into this right now. Lots of opportunity to build companies here. Definitely a painkiller not a vitamin type of business. 14. Right now there are probably millions of agents running on autopilot that their creators forgot about. Still burning tokens. Still sending emails. Still scraping websites. Still costing money. The "find and kill your zombie agents" tool is a product that writes itself. 15. Companies are starting to hire based on someone's agent portfolio instead of their resume. "Show me 3 agents you built that are running right now." It's REALLY early but it's starting. 16. Your Slack archive is a product. Every company's internal Slack has thousands of messages explaining how they actually do things. The company that lets you point an agent at your Slack history and auto-generate SOPs and agents from it will be enormous. 17. We're watching the cost of intelligence fall faster than the cost of distribution. Which means distribution is now the expensive thing. 18. The most underrated asset a human can have in 2026: the ability to sit in a room with another human, make eye contact, and have a real conversation. As AI handles more of the transactional stuff, the humans who can do the relational stuff become disproportionately valuable. The soft skills people used to dismiss as fluffy are becoming the hard skills. The hard skills people spent decades acquiring are becoming the soft ones. 19. There are MANY huge companies to be built around the fact that most people's agents are running on their personal laptops which they also use to browse the internet, check email, and download random files. The attack surface is enormous. One compromised Chrome extension and your agent's API keys, customer data, and workflows are exposed. 20. There's a new type of burnout forming that doesn't have a name. It's not from working too hard. It's from context switching between human work and agent work 50 times a day. Reviewing agent output, correcting it, approving it, reviewing again. The mental load of supervising agents is different from the mental load of doing the work yourself. Some founders are telling me they were less tired when they did everything manually because at least the cognitive pattern was consistent. 21. The cheapest form of market research: search "[your industry] spreadsheet template" on Google. Whatever people are tracking manually is your product. 22. Half the YC companies pivoted within 8 weeks of demo day. Not because they failed. Because agents let them test 5 ideas in the time it used to take to test one. The concept of "committing to an idea" is dissolving. Serial pivoting is becoming the default because 1) AI lets you move fast 2) the world is moving fast. 23. The loneliest job in tech right now is being the only person at your company who understands what the agents are doing. You can't explain it to your boss. You can't hand it off to a colleague. If you leave, everything breaks. You've become a single point of failure for an entire automated system. That person needs a title, a team, and a backup plan. Most companies haven't figured this out yet. 24. Your browser history is the most valuable training data you own and you're giving it away for free. Every site you visit, every product you research, every competitor you study, every pricing page you screenshot. That behavioral data, structured and fed to an agent, would make it understand your business better than any onboarding call. The company that lets you turn your browser history into agent context builds something nobody can replicate. 25. Everyone is building AI wrappers. Nobody is building AI unwrappers. The tool that takes an AI-generated document and tells you which parts a human wrote and which parts were generated. 26. Stripe just became the most important company in the agent economy and they barely had to do anything. Every agent that sells something needs Stripe. Every agent that buys something needs Stripe. They're the payment rail for the entire agentic internet by default. 27. The most undervalued API in the world right now is the US Postal Service address verification API. It's practically free. Every local business lead gen agent needs it. Every real estate agent needs it. Every direct mail agent needs it. Boring government infrastructure is quietly becoming the backbone of agent-native businesses. 28. The concept of "business hours" is for humans. Your agent closed a deal in Tokyo at 3am, processed the payment, sent the onboarding email, and updated the CRM before your alarm went off. 29. What happens when agents start recommending other agents? Your research agent finds that a competitor's sales agent is better and suggests you switch. Agent referral networks are forming organically. The first agent affiliate program is probably 6 months away. 30. Cal dotcom closed their source code. That's the canary. When open source companies start closing up, it means agents were cloning their product too easily. Every open source company is quietly asking the same question right now. 31. "AI for pet groomers" sounds like a joke and that's exactly why it will work. 150,000 of them in America. Zero tech. All scheduling by phone or IG DMs. The joke ideas always win. 32. The thing that will seem most obvious in hindsight: we spent 2025-2026 arguing about which model is best while the entire value was in the orchestration layer. The model is the CPU. Nobody buys a computer based on the CPU anymore. They buy it based on what they can do with it. Makes so much sense in hindsight. What else will be obvious in hindsight? I'll share more notes soon. I can't sleep with all that's going on. Maybe you too. What an incredible time to be building.

ANTHROPIC JUST EXPOSED HOW FAR BEHIND MOST FOUNDERS ARE IN BUILDING COMPANIES WITH AI AGENTS. Not a chatbot guide. Not a prompt tutorial. A full workshop on how to architect, build, and deploy AI agents that run your business operations autonomously. From the team that built Claude. For free. Here is what most people are missing about why this is different from every other AI workshop. Most workshops teach you how to use AI tools. This teaches you how to REPLACE business functions with them. Not replace individual tasks. Entire functions. Research. Content. Customer communication. Operations. Analytics. All running on agent systems that trigger autonomously, hand off between each other, and compound their output without a human initiating anything. The founders who attended Anthropic's enterprise briefings on this material are already building companies with 3 to 5 person teams that operate at the output level of 50-person organizations. Now the same workshop is public. Free. The gap between companies that understand how to architect multi-agent systems and companies that are still using AI as a chat tool is not closing. It is widening every single month. This workshop is the fastest path from the wrong side of that gap to the right one. Bookmark this and watch it this weekend. Follow @cyrilXBT for every Anthropic release that changes how companies are built.

@Bher_SimonM @ArturoVill7 @Viri_Rios El mismo sesgo con el que se juzgó a García Luna? Debe ser un error!

@ArturoVill7 @Viri_Rios Facho o no entiendes o te haces, lo que expone @Viri_Rios es que el jurado no es imparcial ya que se ha alimentado de series de narcos entonces ya traen un sesgo, no interpretes algo que no dice. Punto

La palera del narcorégimen Viri Ríos (@Viri_Rios) ahora critica que en EE.UU. se juzgue con jurados ciudadanos “que ven series de narcos” y hasta insinúa que mañana querrán juzgar a la presidenta. Oye, Viri… ¿sabes quién sentenció a Genaro García Luna? Un jurado de ciudadanos. De forma unánime. Culpable en 5 cargos. Tú misma lo has llamado narcotraficante. Entonces, ¿ahí sí sirven los jurados ciudadanos, pero cuando toca a alguien del régimen que te paga, ya no? Qué hipocresía. Cada día quedas más exhibida

🚨 A junior at Jane Street reportedly landed a $220K–$600K role because he used AI to analyze trillions of data points faster than most teams ever could. In this 1-hour lecture, he breaks down the exact system behind it: • how he researches massive datasets • how AI finds patterns humans miss • how his machine turns raw data into decisions • how you can apply the same thinking yourself Skip Netflix tonight. Watch this instead. One hour could completely change how you think about research, AI, and opportunity.