We’re building out a new program at @NotionHQ: We call it field storytellers. Where Internet filmmakers & creators meet local businesses. All around the world. They travel there to apprentice a business for a day/two, and come back with stories, documented and published. Field storytelling is a bet that stories are best told and relationships are best built when it’s done out on the field. If you’re great with a camera, love traveling to meet local businesses, and Internet savvy with an audience, reach out 🖤

Most writers who hit an income ceiling think their bottleneck is craft. Most writers who can’t move past an income ceiling believe their bottleneck is writing ability. If you think getting better and better at writing will mean people will pay you more, then I’ve got a rude awakening for you. To make more money as a ghostwriter is not just about improving as a writer. It’s about all the other skills that surround the writing that make your clients feel valued, heard, and comfortable. Positioning, packaging, and free consulting beat polishing another sentence every time.

Is X still the best place to build an audience from zero?

2021: hard to build, easy to get noticed 2026: easy to build, hard to get noticed spend accordingly

This is crazy work from Mark Scheifele.

Be the City of Toronto: > Be the 4th largest city in North America > Mayor who doesn’t speak English > Shut comments off, bc in Canada it is freedom of expression not freedom of speech > 55.7% of the population is a visible minority > 19 billion dollar annual operating budget > Give people on the street free drugs > Then let them kill themselves > Lower all speeding limits > Most congested city in North America (2023) > Tax people 55% > Spend $5M on Recycling Bin Stickers > Give $1.4M in research grants to study gender-affirming surgeries > Provide gender-affirming surgeries to city employees.

We’ll pay you up to $100K for every company you refer that licenses its data to @Mercor. We’ve partnered with > 500 companies so far. If you know a company with 100+ employees and data in code, gaming, manufacturing, healthcare or professional services, refer them at data.mercor.com/refer.

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!

X is my favorite platform on the internet, but growing from 0 here is above and beyond the hardest. All the greatest minds, buyers, and capital allocators are here, plus some of the funniest people on earth. But if you want fast reach from scratch, go after IG. A decent post with a tiny account on IG can bring you followers. Trial reels take almost no effort to tweak slightly and post multiple versions. LinkedIn is much easier too. How to make an IG reel that performs: 1. Find a viral reel you like. 2. Plug it into @bot or @stanleybystan and ask for a word for word breakdown of the script. 3. Have it interview you on your expertise to mad lib your thoughts directly into the script. 4. Record the video in the Edits app. 5. Make a new version on the top left, change the font color or text size on the hook, and post versions as trial reels. I can break down LinkedIn too if helpful, just let me know. In an AI world, everyone needs to be creating content. Founder led, EGC, team. The era of staying quiet is dead. It will be very clear who recognized this and who didn't.

We’re bringing the magic of Waymo to Toronto! 🇨🇦 In the coming days, you’ll begin seeing Waymo’s all-electric vehicles driving through Toronto’s streets as we lay the groundwork for our ride-hailing service. Our goal is to begin serving riders in 2028. Sign up for future updates: waymo.com/waymo-in-canada