Sam Lessin congratulates Marissa Mayer and her team on Dazzle, an AI assistant that turns the camera button into an action button using photo context. Mayer's launch post describes it as working without blank prompts.
If a picture is worth a thousand words, your camera roll is worth millions.
That’s why we built Dazzle, an AI assistant that turns your camera button into a "get it done" button. No blank prompts, just instant context and action. 🚀
Ernesto Lopez describes a four-month-old app reportedly making $100,000 a month as a thin wrapper around the Higgsfield API that modifies car photos with AI. He says he cloned the idea in ten minutes using Claude and advocates building similar apps.
Aakash Gupta details Adam Neumann's career, including over $700 million in cashed-out stock before WeWork's IPO collapse, and a 2022 $350 million a16z investment in his residential startup Flow, now valued at $2.5 billion. He notes WeWork sold to Yardi for $450 million.
Adam Neumann ran a $47 billion company barefoot, got fired, watched it go bankrupt, and his new startup is now worth 5x what all of WeWork sold for. The shoes joke is a victory lap.
He cashed out over $700 million in stock sales and loans before WeWork ever filed to go public. When the IPO imploded, employee equity got crushed. His money was already out.
Then came the round nobody could believe. In 2022, a16z handed him $350 million for Flow, a residential real estate startup that hadn't even launched, at a $1 billion valuation. It was the largest single check the firm had ever written. Marc Andreessen's logic was that almost nobody alive has built a real estate brand from nothing, and Neumann had.
Last year Flow raised another $100 million and change at $2.5 billion.
WeWork, meanwhile, filed for bankruptcy in 2023 and got picked up by Yardi for $450 million. Neumann's new apartment company is worth five and a half times what the entire old one sold for.
The lesson buried in a five-word shitpost is what venture actually prices. Neumann vaporized $47 billion of paper value and kept the only skill the money cares about, the ability to make people believe. Three years later the market repriced him at $2.5 billion.
Akshay Kothari of Notion shares a clip from Stripe's Patrick Collison and says Notion is planning for a world where AI agents are the main users of its product. He says the company's house view is that most knowledge exchange will occur between agents within about three years.
This clip from Patrick/Stripe is so good, and also eerily similar to what we’re experiencing inside Notion.
So much so that if you replaced the following words: Stripe → Notion transactions → knowledge transact → collaborate you’d basically get our POV!
“We’re thinking about: how are all the agents and the Claude Code instances going to use Notion directly themselves, right? Both the Notion product, and just how will they collaborate more broadly?
And so we’re thinking a lot about a world where, for most knowledge, agents are the counterparties on both sides. How does an agent sign up for Notion? How does an agent use Notion? Is MCP enough? What should the Notion CLI do? How do we make sure that everything in Notion can be orchestrated and conducted from the CLI, or in some other way that is accessible to agents? How will agents collaborate with each other? What surface will they use?
The Notion house view is that most knowledge will be between agents within, call it, three years. It may not be the case that most of the knowledge volume is directly between agents, but I’ll be sort of surprised if there isn’t just a whirling vortex of reasonably small agent-to-agent collaboration.”
Garry Tan says combining code generation with WhatsApp-style messaging makes sense, reacting to the launch of Wabi 2.0. Wabi describes itself as an invite-only messenger that builds apps and completes tasks for users.
Introducing Wabi 2.0: a new kind of messenger that makes apps and gets things done for you and your friends.
We’re building the OS for the agentic era - software that adapts to your life, gets things done, and makes more room for the people and things that matter.
Invite-only to start. Download Wabi to get on the waitlist. First come, first served.
Tobi Lutke of Shopify praises an integration with Instinct, which lets users discover products, check out and track orders in one conversation. Instinct says 35 percent of its users use it for personal shopping.
35% of our users use Instinct for personal shopping. Today, we’re partnering with @Shopify to bring product discovery, checkout and order updates into one conversation.
Shopping is a creative and personal experience. Your Instinct knows your sizes, the brands you like, and what you’ve bought, kept or returned. When you ask for something, Instinct understands the details that matter, from who a gift is for to when you need it to arrive.
Instinct can now search Shopify’s merchant network for products, and find live information on prices, sizes and availability. When you’re …
Nikita Bier praises Supertake, a platform that uses AI to turn a user's prompt about their beliefs into a constructed stock portfolio. He argues cheaper intelligence will bring hedge-fund-style investing strategies to ordinary users.
Over the last 5 years, I've used every social investing product -- but they all tend to fail in one key spot: Closing the gap between (a) your belief about the world and (b) how to express that belief with stocks.
Mike reached out early in the summer and showed me @Supertake, which solves this problem in the most fun way possible: prompt with AI and it constructs a portfolio around your belief.
With the declining cost of intelligence, we're going to see much more sophisticated investing styles emerge that was previously reserved only for hedge funds.
Introducing @Supertake, a new platform that transforms your unique takes on the world into real, shareable investment portfolios using frontier AI and trading agents.
Supertake makes it easy for anyone to invest in their ideas, even if they know nothing about investing.
Scott Belsky comments on Fo, a new consumer agent product from Shivani Poddar that trusts humans for tasks AI cannot do, suggesting human-in-the-loop may become a key differentiator. He links to his earlier post on the topic.
would be wild/ironic if "human in the loop" becomes the key differentiator for consumer agents; new product from @shivanipod and team w/ trust as key area of innovation... and touches upon a few of the attributes from this post yesterday: x.com/scottbelsky/status/2104273606234591739
Shivani Poddar, who led engineering at Google DeepMind, introduces Fo, a personal AI that employs humans for tasks AI cannot yet handle. She claims 2x better real-world task completion and a 94% trust rate, and invites free sign-ups.
OpenMarket announces free watchlists, allowing up to 50 lists with unlimited symbols across stocks, crypto, futures, forex and prediction markets. The company positions the move as a response to TradingView's $155 annual price.
Vikas Alwys profiles Dhravya Shah, who left IIT Bombay to build Supermemory, an AI memory system for emails, files, chats and documents. The post says the company raised $3 million from investors tied to Google, OpenAI and Cloudflare after Shah shipped a new product weekly.
Meet Dhravya Shah, a 19-year-old Indian guy who dropped out of his B.Tech at IIT Bombay and just built one of Silicon Valley’s fastest growing AI startups called Supermemory.ai, which has now raised $3 million USD.
While preparing for the IIT entrance exam, Dhravya Shah built a tiny AI tool on the side and used the money to move to the United States. He got an O-1 visa and moved to the US.
Then he gave himself one challenge: build one new product every week for 40 straight weeks. One of those projects became Supermemory.
An AI memory system that lets AI remember your emails, files, chats, PDFs, and documents just like a human brain.
Today, Supermemory has raised $3 million USD from investors behind Google, OpenAI, and Cloudflare.
All because one teenager kept shipping instead of waiting for the perfect idea.
Sheel Mohnot reports that personal AI assistant Instinct raised $1 billion at a $10 billion valuation from Benchmark, Sequoia and Coatue, with 14 employees. Most new funds will go to compute, which CEO Noah Shinn spends 40% of his time acquiring, and the company is reportedly growing 10% a day.
Andrew Ross Sorkin reports in DealBook that Instinct, an AI assistant, is now worth $10 billion after raising $1 billion from Benchmark, Sequoia and Coatue, with 14 employees. The post links to a separate NYT piece on whether AI safety risks could derail OpenAI and Anthropic IPO plans.
Scoop in @dealbook : Instinct, the hot AI assistant, is now worth $10 billion! With only 14 employees. It raised $1 billion from @benchmark, @sequoia and @coatuemgmt.
Patrick O'Shaughnessy shares a podcast conversation with Noah Shinn, founder of invite-only personal AI assistant Instinct, which is growing about 10% a day with no marketing spend. Topics include the absence of an app, compute purchasing, trust, safety, agent coordination and the business model.
My conversation with Noah Shinn (@noahrshinn), founder of Instinct.
Noah is building a personal AI assistant. It's still invite only, has spent nothing on marketing, and is growing roughly 10% A DAY.
This is his first long conversation about the company.
We discuss: - Why Instinct doesn't have an app - Buying compute months ahead of exponential demand - How users learn to trust it with a credit card - Safety and security - Agents coordinating with other people's agents - Instinct's business model - Apps built on consumer inertia - and more
Enjoy!
Timestamps: 0:00 Intro 4:11 What people are using AI agents for 15:07 Rethinking travel, reservations, and the internet 22:43 Trust, privacy, and personal data 27:50 The business model behind Instinct 38:04 How existing businesses will adapt 47:55 Designing a personal assistant people love 53:15 Growth, compute, and competing with Big Tech 1:11:44 What’s next for Instinct and personal AI
Gergely Orosz notes that Clubhouse took 14 months to ship an Android app, arriving in May 2021 after peak hype had passed and demand had collapsed. He argues this illustrates how slow execution can compound a platform's decline, while acknowledging COVID lockdowns also played a role.
Remember how it took Clubhouse (voice chat app) 14 months (!!) to build an Android app.
By the time they launched it (in May 2021), they missed peak hype on the platform (which was Feb 2021) and demand collapsed
What an example of slow execution speeding up a platform dying... even if we can argue that the platorm itself was tied to COVID lockdowns (and an "escape" from it)
Shirish highlights a business that finds counterfeit copies of brands online and gets them removed, charging only when takedowns succeed, and says it earns $430k per month in the US. He argues the model would be even larger in India, citing knockoffs of D2C products on Meesho, and quotes a bootstrapped founder's $500k MRR post as context.
my startup is bootstrapped - no investors started with $20k a slack channel google sheet and south african virtual assistant we are only 1 year and 9 months old we only have 153 customers
Freddy Fang reports that $1,000 in Apple Ads yields 15 paying subscribers in the US versus 65 in Brazil, and notes higher cost-per-tap in the US and GB against strong conversion in Romania. He recommends testing funnels across geographies before scaling.
$1,000 in Apple Ads gets you 15 paying subscribers in the US vs 65 in Brazil.
Most app founders burn budget trying to scale across markets like the US and GB where CPT climbs over $1.60. Meanwhile, markets like Romania hit 77% CR at low CPT.
Experiment around and look below at different geographies to test your funnel and grow
HEK highlights OpenMarket's free offering of up to 16 charts per layout, unlimited classic indicators, and thousands of economic series, positioned against TradingView's paid plans. The quoted launch post also cites footprint charts and order book heatmaps.
TradingView charges $2,399 a year to plot 16 charts on one screen.
Starting today, you can do the same for free on OpenMarket.
Everyone now gets: → up to 16 charts per layout, any grid from 1x1 to 4x4 → no limit on classic indicators: RSI, MACD, moving averages, Bollinger and more → 5,000+ economic series from 200+ countries and 50+ central banks
And beyond candles: footprints from every trade, not estimates, and live order book heatmaps from real depth, on crypto, CME futures and more.
Every market, one terminal: • US stocks and tokenized stocks • Crypto • CME futures • Forex, commodities…
A fitness page built around an AI-generated blue character posts simple workout and muscle-growth slideshows, then sells a $19.99 workout blueprint via a link in bio. The author calls it a more interesting AI use case than generic AI slop.
he built a fitness page around an AI generated blue character, posts simple workout / muscle growth slideshows and then sells a $19.99 workout blueprint through the page
no face no filming workouts no personal brand needed
just:
-> AI character -> useful fitness content -> consistent visual style -> link in bio to the product
the page is already at 325k+ followers
he basically turned one made-up character into the face of an entire fitness brand
this is the kind of AI content use case i find way more interesting than random AI slop
Peter Yang says Grok Bot is his favorite AI tool for cloud work and teases an episode with its engineering and design leads covering the 14 bots they use and a design bot that builds user flows from a keyframe. He links to his YouTube channel for the episode.
Grok @bot is still my favorite AI tool for actually getting work done in the cloud.
Tomorrow, I'm sharing a new episode with @poteto and @pengzheng_, the engineering and design leads for Grok Bot, about:
→ The 14 bots they use for work and life → Peng's design bot that turns one keyframe into a full user flow → Lauren's eng lead bot that manages a team of eng bots
Who better to learn Grok Bot from than the people who built it?
Mauro, a 22-year-old builder, reportedly grew a gym app to $160,000 per month in one year by testing features with A/B experiments, killing underperformers, and scaling creator-driven UGC distribution that paid creators about half of revenue.
He’s 22 years old and built a gym app doing $160,000/month in just one year.
But Mauro’s edge isn’t the product or the marketing. It’s how he decides what to build.
Most builders ship features and hope. Mauro treats every feature like a science experiment - problem first, hypothesis second, A/B test everything, kill anything that doesn’t move the metric.
One tiny example: adding a single screen at the end of a workout lifted retention 3%. Meanwhile, two completely redesigned home screens moved… nothing.
He also cracked distribution with UGC: 500+ creator accounts, 80,000 videos posted in a year, nearly 1 billion views.
He pays creators ~50% of revenue so they stick around for the long run. One lock-screen-notification format did 17M views on a single video.
The takeaway: stop guessing what to build. Track events, run A/B tests for 2+ weeks, and focus on the screens that actually move activation, retention, and ARPU.
Vaibhav Domkundwar shares a quote from Gokul Rajaram of Marathon Management Partners, who argues that ARR multiples are meaningless without burn rate and that investors should seek companies that can grow efficiently in bad markets.
High ARR multiples won't save an AI startup with runaway burn rates.
Gokul Rajaram @gokulr, Founding Partner at Marathon Management Partners, explains why evaluating companies on revenue alone is a major risk:
"The ARR multiple in isolation without looking at the burn is basically irrelevant…What I want is a company that when the markets turn, they can still keep growing efficiently and they can raise a round even in a bad market."
A viral post profiles Maddy Zhang, an MIT graduate and Airbnb senior engineer earning $400K remotely, and outlines a five-step strategy for landing high-paying remote roles, including filtering remote-first companies and timing applications.
Meet Maddy Zhang, who completed her Bachelor’s in Computer Science from MIT.Her internships include Amazon, Microsoft, Morgan Stanley, and IBM. Now, she is a Senior Software Engineer at Airbnb, earning $400K a year ... and that too remotely.
She also worked at Google California for 4½ years.
This is how she cracked a $400K remote job in the United States.
Here’s the strategy to get a high-paying remote job:
Step 1: Filter companies that are remote-first.
Step 2: Build an async-proof portfolio.
Step 3: Have an application timing system .. apply to jobs that have been live for less than 48 hours.
Step 4: Do remote-specific interview preparation.
Step 5: Run a warm visibility loop in the background.
Sequoia partner Pat Grady shares a recorded video of his thoughts on AI, originally prepared for the Boston College Investment Committee, an LP and his alma mater. He stresses it is not a sales pitch.
The @BostonCollege Investment Committee (an LP and my beloved alma mater) asked for a few thoughts on what's happening in AI. I recorded a test run yesterday morning and then shared it with my partners, who encouraged me to share it more broadly... so here you go!
This is not a sales pitch, it's just a reflection on what we're seeing. And it wasn't intended to be shared, so please pardon the rough edges.
Erik Torenberg introduces Cosign, a curated professional network for the startup community featuring a directory of investors, companies and operators, endorsement graphs, and private intent signals for investing, hiring or working together. Joining requires a cosign or direct application.
Excited to introduce @Cosign: the curated professional network for the startup community: cosign.co
Our goal is to create the following:
- A comprehensive startup directory of investors, companies, and operators, including what they worked on and who they worked on it with.
- Cosign graph: Who shaped your career? Who were you actually in the trenches with? Who would work with you again? Who thinks you’re someone to watch?
- Durable reputation: Great endorsements happen every day on X and disappear into the feed. Cosign attaches those signals permanently to people and companies.
- Discovery: Who are the best fintech angels? Which AI companies should I watch? Who are the best designers?
- Intent network: Privately signal “I’d invest in them,” “I’d hire them,” “I’d work with them,” or eventually even “I’d acquire this company.” Match people when interest exists on both sides.
Imagine if Wikipedia, LinkedIn, and OG AngelList had a baby. Though Cosign is a community, not a business.
In order to join, you need to be cosigned. Or you can apply directly.
David Booth and I started this idea 7 years ago but didn’t have the firepower to make it work. Now we do.
No one has really touched LinkedIn in 20 years. Excited to take a swing.
The Deal Director predicts a high-profile chief revenue officer will soon explain to sales reps that the old selling environment no longer exists, quoting DHH's argument that honesty about change helps people adapt.
There's nothing kind about letting good people live in a fantasy world that no longer exists. You have to tell them, even if it hurts. Because the sooner they accept reality, the sooner they can adapt to the future.
Paul Graham says the rise of AI agent swarms creates multiple startup ideas, including filtering out agents and welcoming them in an orderly way, in response to Nikita Bier's warning about bot detection and human verification.
This is a big enough problem that there's not just one startup idea here, but several. For example, there will probably be one variant meant to filter out agents, but another meant to welcome them in an orderly way. This also seems an idea you could build more on.
Bot detection & human verification will be one of the most urgent demands for businesses over the coming years. Agent swarms will suffocate every website and form; small companies and government websites are most vulnerable.
There is a huge gap in the market for this right now. When we looked at what offerings were in the market to use at X, there was not a single company that brought together all the latest technologies so we had to do it all in-house.
Josh Elman compares the Muse Connect platform to the 2008 launch of Facebook Connect, calling it one of the biggest consumer API developments in a long time. He is responding to Muse's partnership announcements and asking which connectors users want next.
Jason praises Meta for releasing smart glasses without a camera and asks whether anyone has built a pendant or glasses that authenticate with AI and genetic platforms. He says he would like to fund such a product, with a video attached.
