I was about to hire a marketing lead, an additional researcher and a developer. I set up 15 Grok Bots instead, for $100 a month Here's how I use it every day, and how I keep the spending low 👇 1. Organisation I run a team of specialised Grok @bot agents that keep working overnight. They share one computer, and each has its own memory, routines and connectors (@X, @NotionHQ, @github). How the week runs • Overnight ops kicks in: sync Notion database, check for security patches. The Chief Security Officer will also be on standby • In the morning, ops skim the bots' chats for any drift (drift = where a bot slowly stops doing what I asked) + sends me a morning brief of what got done overnight • Every Monday start of the week we will have a stats review too for @ahboyash and @mementoresearch's content 2. Laying the foundation: Using Notion as the shared brain for the bots' memory A bot's computer can get reset and its chat history can disappear. To solve this, connect GrokBot to Notion via MCP so every bot writes to its own "Second Brain": • Create one main page in Notion Then under the main page, make one page per section. Work areas that connect to its respective section (i.e. one page per bot and has its own repository) • Shared databases underneath: Projects (Status + Next step + Last updated), Decisions • For marketing, content queue for draft posts • Bots check Projects + Decisions before acting 3. X research + content Had almost 1mil impressions over the past month and GrokBot helped me to generate content that was in line with what has been happening lately • Our Scout reads accounts I follow, plus a private account list (study their content and note what went viral) • The CMO turns that + my takes into drafts in my voice and style (how I usually type and structure posts) • Analyst will verify the data • Editor will do a QC on drafts and any iteration if necessary • Posting and edits is still done by me • At the end of the week, will have a weekly report ready for me Example: the security post + Mac audit • Posted a 30-point crypto security checklist (accounts, Telegram, wallets, devices). Landed ~114k views, 1.3k likes, 2.7k bookmarks • Another article on "How to audit your Macbook in 15 minutes (no tech skills needed)". Walked through System Settings + a few read-only Terminal commands my bot fed me. ~16k views, 414 bookmarks • Both of the posts above were drafted with the bots 4. General ops • Using dr eggbot by @poteto to design and optimise other bots. Used it when I had overlapping bots and needed to merge them (fewer good bots beat a big messy team - give every bot one clear job) • Chief Operating Officer does our bot optimisation while the Chief Security Officer ensures account hygiene and runs through the bots (on Telegram) + Mac audits 5. What's new in Grok Bot • Pages: live in-app reports the bot keeps updating (nice updates from @mattyp) • Vault: logins, cards and contacts, so the bot can fill sign-ins • Custom modes and Team Bot sharing • Apple app integrations, video generation, better mobile polish 6. How I'm cutting the spend (@elonmusk pls sir) • Removed (or merge) some obsolete scheduled routines + deleted unused bots • In any group chat, only @mention the bot needed. Long work goes to that bot's 1:1 or Notion • Turn repeat work into scripts the bot just runs, instead of re-thinking the task every time • Keep routines no more frequent than hourly. One lead bot per project 7. If you're just starting to use GrokBot • Add one bot + dr eggbot. Don't build 15 on day one • Hook Notion up first to ensure the data is saved in a repository • Give every bot one job and a "do not do" list • Put long work in 1:1s / Notion, not group chats It's been a fun journey so far. Let me know if you have any tips to optimise Bot below!

Jake Retzlaff discussing whether he had another year of eligibility on @espnthefan: Q: I love that insight because fans never get to hear those stories. If you had another year of eligibility, would you have followed Coach Sumrall to Florida? Retzlaff: That's a tough question. There's no doubt it would've been really tempting. If I were entering the portal again, Florida would've been an incredible opportunity. Playing in the SEC under Coach Sumrall would've been exciting. He's an unbelievable coach. I've said before that Coach Sumrall reminds me a lot of Kalani Sitake. They're similar in a lot of ways. Sumrall is probably a little more Southern and rough around the edges, but they're both authentic leaders who build great cultures. One difference was definitely the language. At BYU, because of what the university represents, the environment naturally keeps things pretty clean. Down South, it was a little different. I think we literally had pass routes named after curse words. That was a culture shock for me. I definitely had to work to keep my own language the way it had been in Utah. Q: Speaking of toughness, let's go back to your time at BYU. Against Oklahoma State, you threw an interception late in the first half, hustled back to make the tackle, and then looked like you were in a lot of pain. Everyone watching thought your shoulder might be seriously injured. Then BYU came out in the second half, ran the ball 10 straight plays, and the first pass afterward was a touchdown to Keelan Marion. Take us through that moment because you showed a lot of toughness throughout your career. Retzlaff: I appreciate that. One thing fans don't always realize is that the only time a football team is truly healthy is before Week 1. After that, everybody is dealing with something. Hopefully, during those early nonconference games, you can stay relatively healthy, but once the season gets going, everybody's managing injuries. Even in my first game against Southern Illinois, I rolled my ankle because the turf gave way while I was running near the goal line. From that point on, you're constantly trying to get as close to 100 percent as possible, knowing you'll never actually get there. That hit against Oklahoma State hurt. I remember running into the locker room trying not to show how much pain I was in. Our trainers and team doctors did a tremendous job getting me ready. The biggest thing I learned is that being healthy is just as much mental as it is physical. If you don't believe your shoulder is healthy, it doesn't matter what the doctors tell you—you won't play freely. Coming out in the second half, after we'd established the run, my first throw was that touchdown to Keelan Marion. Mentally, I had to trust that I was okay and just let it rip. Credit to our medical staff. They got me ready to go, and once I convinced myself I was good, I was able to play my game. Link to interview: 📸: @TulaneAthletics

Liang Wenfeng’s remarks at the investment meeting: DeepSeek did not start out to make money, go public, or chase the capital markets. It was a group of ordinary people driven by profound goodwill toward the world, wanting to do something useful for humanity. The company is vision-driven, with no formal organizational structure, KPIs, or performance evaluations. The vision is embodied in the way they work and their attitude toward the world; its core is restraint and goodwill. He repeatedly elaborated on “restraint”: the AI market is large enough (potentially 10% of human GDP) that monopoly is impossible—sharing is essential. Open-sourcing is part of both the vision and the business strategy, not something forced upon them. Open-sourcing does not hurt revenue because pricing aims only at a reasonable profit—recovering hardware costs in ten months (roughly a 6x return)—rather than maximizing profit. Demand is inelastic at higher prices; lowering prices made employees cheer because the goal is to make the technology affordable for more people. After open-sourcing, third-party deployment costs remain higher and cannot meaningfully challenge their own business. Last year’s consumer-side users and this year’s enterprise revenue are both by-products on the road to AGI; they have no intention of fighting for traffic or building a super-app. The long-term goal points clearly to AGI. The technical roadmap is clear: after the current Agent stage, the next step is continuous learning (allowing the model to adapt over long periods like a human), then the singularity of self-iteration, and finally embodied intelligence. Continuous learning is the key bottleneck; once solved, AI can accelerate the company’s own R&D, making the path much easier. The company sticks strictly to the main line (language models, CoT, Agents, etc.), declining to pursue video generation, world models, or other off-track directions, while remaining willing to help others. The sole core interest is team stability. Money and resources are not the problem—as long as the people stay, AGI will be achieved. The recent financing has substantially reduced this risk. The main gap with the United States is compute resources (currently about 20,000 H-equivalent cards, with aggressive expansion underway); the talent gap is small. The strategy is to buy as many cards as possible at reasonable prices and prioritize converting cash into GPUs. Domestic chips (Huawei) face a historic opportunity in the ecosystem; technologies such as TileLang can dismantle CUDA’s moat, with validation expected within a year. Organizationally, “official work” occupies no more than half of people’s time; the rest is left for individual exploration. There is little overtime, preserving a relaxed research culture. Commercialization has always been happening, but it is not the goal—focusing on AGI creates a dimensional advantage. Ultimate differences will lie in cost, timing, and user experience; China may carve out a place through lower costs and better experiences. The vision is restraint, sharing, and concentration on the main line, thereby increasing the probability of achieving AGI. Liang Wenfeng carries clear traces of quantitative trading: as a quant expert and the boss of a quant firm, he extracted substantial returns from market volatility and deeply understands that “excess returns are unsustainable” and that “excessive greed will eventually backfire.” This experience has been internalized into a character of “not competing and leaving profits for rivals”—he proactively open-sources top-tier architectures and models, prices only for reasonable cost recovery, explicitly refuses to fight for consumer traffic, avoids head-on competition with big tech, and is even willing to help Alibaba, Moonshot, and other competitors reproduce the technology. This is not feigned humility; it is the use of “restraint” as a strategic weapon: sacrificing short-term sesame seeds to secure the long-term watermelon and team cohesion. He is simultaneously pragmatic and idealistic: on the one hand he candidly admits “we are just a group of ordinary people” with low starting points and scarce resources; on the other he uses vision to unite people and maps a continuous-learning roadmap toward AGI. On the one hand he emphasizes that the company must still survive (enterprise revenue can provide a floor); on the other he treats profit maximization as a dead end that will be defeated by those who take less. His decision-making style is decentralized and consensus-driven, almost obsessive about team stability, yet aggressive in expanding compute—classic quant thinking: control the controllable risks and amplify asymmetric advantages. He can roughly be described as a calm, restrained, long-termist technological idealist: the caution of a market veteran and the pure spirit of a scientist converge in him. He neither fantasizes about monopoly nor shies away from commercial reality, always placing the achievement of AGI above personal and corporate interests. People who truly make money in the stock market eventually become different kinds of good people—donating, sharing, and practicing religion or charity.

똑똑똑 #andTEAM# #K# coming at BND's door 🔗 🔗 🔗 🔗 #BOYNEXTDOOR# #똑똑똑# #똑똑똑_Challenge#