23: India

22: AI

Bleeding edge San Francisco AI startup: @MonidHQ Makes an automatic AI router to get your AI agents access to better models for what you are asking it to do. @shengkunye tells me why his is the best at his office at @fdotinc. One of San Francisco’s best startup factories. https://t.co/CHySOiUi4l

— Robert Scoble (@Scobleizer) October 22, 2026

14: India

Congrats! CEOs & execs posting to the public directly on 𝕏 is the best way to get your message out and drive product sales. Vastly more powerful and effective than a press release.

— Elon Musk (@elonmusk) October 13, 2026

I've heard thousands of pre-seed pitches. Bad pitches: • Open with the market size • Spend 10 minutes on features • Show a hockey stick with no assumptions behind it Good pitches: • Open with the thing you know that nobody else believes • Explain why now, not just why • Show what you've already built with almost nothing What's the one thing you know that nobody else believes?

— Martin Tobias (Pre-Seed VC) (@MartinGTobias) October 14, 2026

@paulg Not true. The YC Columbus model is a huge misfit for the next 10 years.

— Paramendra Kumar Bhagat (@paramendra) October 14, 2026

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!

— GREG ISENBERG (@gregisenberg) October 14, 2026

Congrats! CEOs & execs posting to the public directly on 𝕏 is the best way to get your message out and drive product sales. Vastly more powerful and effective than a press release.

— Elon Musk (@elonmusk) October 13, 2026

AOC 2028: The First AI Election (Book)

AOC 2028: The First AI Election https://t.co/JBagJuayaa 👇@RepAOC @SenSanders @aoc @Ilhan @AyannaPressley @RashidaTlaib @RepJayapal @GregCasar @ZohranKMamdani @NYCMayor

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

In 2008, Barack Obama’s presidential campaign demonstrated how the internet and social media could transform political communication, organizing, fundraising, and participation. 👇👆 @RepSummerLee @MaxwellFrost @RepRoKhanna @RepMarkPocan @RepBarbaraLee @ewarren

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

AOC 2028: The First AI Election https://t.co/JBagJuayaa 👇👆@RepJudyChu @RepMaxineWaters @RepHankJohnson @RepTedLieu @RepJoeNeguse @RepSaraJacobs

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

AI could turn a temporary election campaign into a continuous civic network. Personal AI assistants could explain legislation, answer policy questions, and help citizens understand competing proposals. 👇👆@RepDeliaRamirez @RepChuyGarcia @RepHuffman @LloydDoggett @RepDeLauro

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

A prepared administration could use the same infrastructure to translate campaign commitments into legislation, implementation plans, and measurable outcomes. 👇👆@RepDinaTitus @RepEarlBlumenauer @RepNikema @RepDarrenSoto @RepWilson @RepCherfilus

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

Universal healthcare, lifelong education, and housing abundance become possibilities to investigate as technology increases productivity and potentially reduces the cost of delivering essential services. 👇👆@RepKamlager @RepLuzRivas @RepSchakowsky @RepCasten @RepLofgren

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

AOC 2028: The First AI Election https://t.co/JBagJuayaa 👇👆@RepGolden @RepAdams @RepGarcia @JasmineForUS @AnaMariaArchila @ZohranKMamdani

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

This creates the possibility of a state that is smaller in administrative headcount but larger in capability. 👇👆@AnnaForFlorida @AlexandriaRojas @JessicaCisneros @AbdulElSayed @SaikatChakra @CoriBush

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

It examines a proposed 70 percent top marginal income-tax rate as a policy hypothesis within a broader debate about taxation, productivity, and public investment. 👆👇@AOCpressley @DemSocialists @JusticeDemocrats

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

Greater economic interdependence and stronger institutions could create opportunities to reduce avoidable conflict and redirect resources toward human development. 👆👇@SunriseMvmt @WorkingFamilies @MoveOn @OurRevolution @PeoplesBudget @DataProgress

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

The book concludes with the Governing OS: an integrated democratic operating system connecting citizen participation, policy design, legislation, administration, and accountability. 👆👇@FightInequality @RealBankReform @ACLU @ACLUpeople @IndivisibleTeam @BoldProgressive

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

The election is the demonstration project. Redesigning democracy for the age of abundance is the larger ambition. 👆👇@DemandJustice @FairEconomy @EconomicPolicy @GreenNewDeal

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

The AOC Moment: Four Megatrends Reshaping America https://t.co/nYX5qGOo96 AOC 2028 https://t.co/mNXpIJyIXX AOC 2028: : The Future of American Progressivism https://t.co/OFT21hpjcu 👆👆

— Paramendra Kumar Bhagat (@paramendra) October 10, 2026

3: Balen Shah

1: Fly Dubai Terror

11: BRICS

10: Water

This is why it's a good thing that American labs are in the lead. If Chinese labs were, their employees wouldn't be able to warn us about threats. But Chinese labs will encounter the same threats within a year, in complete silence. https://t.co/Bg5Vakbl4W

— Paul Graham (@paulg) September 10, 2026

People who do extraordinary work are often anti-charismatic; they don’t talk to strangers, struggle in social settings and usually prefer to be alone.

We interviewed one CEO who hid in a stairwell for an hour at his own launch party because the chit-chat was unbearable, and…

— Adam Shuaib (@adamshuaib) September 10, 2026

Most people dismiss the improbable. We back the founders building it. 150+ companies shaping what comes next in AI, robotics, enterprise, healthcare & medicine, climate, consumer, fintech, manufacturing, infrastructure, space and beyond. pic.twitter.com/8TYBD7L5HE

— Vinod Khosla (@vkhosla) September 10, 2026

Nepali Khana 🍲!
Do you like it ? pic.twitter.com/gq16Bd8SHd

— Ananda Nepali (@anandanepali99) September 9, 2026

The Nepalese flag is the only one in the world that isn't rectangular or square. It is also the only flag whose height is taller than its width.

The flag we see today was adopted in 1962. Prior to that, though, it looked quite different.

As always, there's a great story.

1/n pic.twitter.com/33o5wX99wf

— Iain Cameron (@theiaincameron) September 10, 2026

Of this is remotely true.. https://t.co/rcIeSNORCP

— Manisha Koirala (@mkoirala) September 10, 2026

Local business owners, I have two words: Facebook ads

If you're a local business, a dry cleaner, a a barber, a restaurant, my favorite thing in the world right now is Facebook ads in a 10-mile radius.

— Gary Vaynerchuk (@garyvee) September 9, 2026

Yesterday's AIs ate the Internet and became a patchwork mediocrity.

Today's AI hunts and feasts upon the Mozarts, Einsteins, and Shakespeares of our age.

To birth a gang of ghostly geniuses that write our code, drive our cars, do our work, and run our world.

— Naval (@naval) September 10, 2026

People need to wake up to what’s going on. This is the highest-stakes game in the history of mankind. You didn’t think they would just do nothing to protect their potential God-like power, did you? Don’t be foolish to think they just care about you!

“The incentive is obvious.… https://t.co/Hx9rDELhix

— Derya Unutmaz, MD (@DeryaTR_) September 10, 2026

How a coastal refinery that makes water, power, salt and magnesia from the sea could redraw the water map of India — and why the first decision is the simplest one: to measure it. https://t.co/Pa5y25mHVl

— Ilir Mehmetaj (@IlirMehmetaj) September 10, 2026

HCTGS v36 India — The Tower That Can Pays for India’s Water Before the Water Even Arrives HCTGS v36 India. 2,000 towers. Per year: 730 billion m³ freshwater — India’s entire water use · 17,500–26,300 TWh or 350–525 Mt H₂ · 1,090–1,410 Mt magnesia · annual output $1.6–2.8 trillion. CAPEX $1.3–2.3 trillion over 25 years — $52–92 bn a year in orders. Each running tower funds the next within two years. Ground occupied: 160–400 km². Entry: 30 towers — the Chennai corridor and the Gulf of Khambhat. ......... Punjab draws 156 percent of its annually extractable groundwater. Rajasthan draws 147. Haryana 137. Those are the 2025 figures from the national Dynamic Ground Water Resources assessment, and the difference comes from aquifers that took ten thousand years to fill.

8: BRICS

2: Xi Jinping