David Hill shares ArtCraft's site listing seven free, open-source creative apps built in Rust covering image editing, vector illustration, video, photography, PDFs, motion graphics and page layout.
Tanay Jaipuria notes that Sequoia made seven tranched rounds in the past year, with first-tranche valuations averaging about $110 million and second-tranche valuations averaging about $3.4 billion. He shares a quoted Boston College investment committee presentation on AI.
Sequoia did 7 tranched rounds in the past year. First tranche (i.e., what they invested at): ~$110M valuation on average. Second tranche: ~$3.4B on average.
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.
International Cyber Digest reports that ransomware group BYOD leaked personal data of 3,615 Trump Mobile customers, including names, addresses and order details, and claims continued access to the company's backend. Straight Arrow News reported that people in the data confirmed its accuracy.
‼️ BREAKING: Trump Mobile customers have had their personal data leaked by ransomware gang BYOD. The dump covers 3,615 people and includes names, emails, phone numbers, home addresses and order details.
The gang says the company answered news of the breach with "We have no team to handle this."
The leak includes the Trump Organization's own CIO, who oversees its information security.
People listed in the data confirmed their details are accurate and BYOD claims it still has access to Trump Mobile's backend, Straight Arrow News reports.
a16z's seventh Top 100 Consumer AI Apps report adds a revenue leaderboard alongside traffic rankings. It notes ChatGPT's 1B+ monthly mobile actives, Claude reaching nearly 1B monthly web visits, and growth into vibe coding, music, design and video, while nine of 15 consumer categories have no AI product in the top 100.
The seventh edition of our Top 100 Consumer AI Apps is here.
New this time: a revenue leaderboard, alongside the usual web and mobile traffic rankings.
Three years ago we published the first edition. ChatGPT was #1, Claude was unranked, and the entire category was chatbots, image generators, and not much else.
In today's edition:
- ChatGPT still holds the throne, now with 1B+ monthly actives on mobile
- Claude has climbed to #3 on web with nearly 1B monthly visits
- The category has expanded to vibe coding (Lovable, Cursor, Replit), music (Suno), design (Figma), voice (ElevenLabs), video…
Julie Zhuo highlights a feature letting early-access users add Instinct to group chats, where the agent joins the whole group to coordinate plans, times and logistics without requiring friends to install it.
Starting today, early access users can add Instinct to group chats. A new Instinct joins and works for the whole group.
Making plans with friends usually turns into a frustrating back-and-forth over times and places. With Instinct in the group, you can explore options together, agree on a plan and get it done, all in one thread. Your friends don't even need Instinct to join in.
A few things it’s good at: - Planning a weekend trip with friends, including dates and arrival times - Coordinating logistics with a roommate - Getting tickets as soon as they go on sale, then…
Julie Zhuo shares a quoted post on the four principles of consumer AI and says Muse, launched earlier this month, is the first consumer agent she has used that might make people change their habits.
What will make personal AI go big? — Muse launched earlier this month, and it’s the first consumer agent I've used that makes me think people might actually change their habits for it. I’m not the only one who thinks so! The X-o-sphere
Josh Elman says he discussed the new Consumer AI Top 100 with Olivia Moore on a podcast, focusing on where consumer spending on AI goes next. The post links to the report that adds yipitdata revenue figures to track consumer spending.
1/ The new Consumer AI Top 100 is live and I had a blast unpacking this one with @omooretweets on the pod - it crystallized something I keep coming back to about where consumer actually goes next
Renu Mukherjee shares research by Michael Hartney finding that only 28% of white Republicans and 26% of white Democrats worry about campuses becoming mostly Asian, and argues the political positions taken on social media may cost candidates support.
Incredible new research from @MichaelTHartney: The Heritage American/Bo French/Woke Right’s position on college admissions is a political loser—even among white Republicans.
ONLY 28% of white Republicans said they were worried about campuses becoming “mostly Asian.” Similarly, only 26% of white Democrats expressed concern. Black Americans were the group most worried about a majority-Asian campus, albeit still under 50% were troubled by the prospect.
X isn’t real life. And if political candidates treat it like it is, then they’re probably going to lose—and they deserve to.
Justine Moore reports that the top 1% of consumers spend more than $900 per month on AI products on personal credit cards, a spending level that outstrips the bottom 50% combined, per the a16z Consumer AI Top 100 revenue data.
Deedy Das says Menlo Ventures is lead investor in five of the top 15 consumer AI apps by monthly revenue, despite a low-volume investing strategy. He responds to a post by Shaun Maguire highlighting Menlo's Anthropic investment and its involvement with Factory AI.
Menlo has tried to rebuild from the ground up how we think about investing and we are fortunate to be lead investors in 5 of the top 15 consumer AI apps by monthly revenue despite our low volume strategy.
Thanks for the shout, Shaun! Have a ton of admiration for what you have done at Sequoia. Too many people know you for your firebrand tweets and too few know your excellent investments and that you have a PhD in physics from Caltech (and it’s fun to have your cofounder be a partner!)
Valon announced a Series D round that doubled its valuation to $2.3 billion, backed by Ribbit Capital and a16z. Angela Strange says Valon now runs about one in six U.S. mortgages on its ValonOS platform.
Paraphrasing Jensen: "It's not AI that's your competition, it's your competitors adopting AI faster than you". For those who thought mortgage would never modernize -- Valon has now contracted 1 in 6 mortgages in this $13T industry onto ValonOS.
So excited to announce that @Valon has raised a Series D, doubling our valuation to $2.3B 📷
I’m incredibly proud of our team and grateful to our customers and partners. Huge thank you to @RibbitCapital@a16z and everyone who continue to support us!
Josh Elman argues that agents appear as blank boxes to uninitiated users, while coders understand them instantly. He says solving that usability gap would unlock the next few hundred million adopters. He shares a link to a16z's Top 100 Consumer AI Apps report.
The problem with consumer AI in a nutshell is if you hand an uninitiated user an agent, it's nothing but a blank box to them. Coders get it instantly, but for everyone else it’s just not intuitive. Solve that, and you reach the next few hundred million real adopters.
The seventh edition of our Top 100 Consumer AI Apps is here, including a new dimension this time: what consumers are actually paying for.
a16z's Elena Burger sits down with Olivia Moore and Josh Elman to unpack the current state of consumer AI:
The data reveals a striking power-user economy. Only a small share of consumers currently pay for AI, but among those who do, spending is heavily concentrated at the top. Olivia and Josh discuss why developers, creators, and other power users dominate spending today, and why subscriptions may not be the business model that ultimately brings consumer A…
DHH quotes a Stratechery essay by Ben Thompson arguing that AI agents make Apple's walled garden feel like limitation rather than protection. DHH says he can now imagine no longer buying Apple by default.
"Not only am I uninterested in the company’s home device, I can, for the first time, envision a future where I don’t buy Apple by default. Indeed, this already happened..."
Anyone into the age of agents will eventually realize Apple is a bad fit.
Aakash Gupta explains that AMC rents whole auditoriums for as little as $99 because most seats go unsold and projection costs are nearly fixed. He says the product began during COVID, when AMC lost $561 million in one quarter.
Renting out an entire movie theater costs as little as $99. AMC put it right on their website in 2020, at $99 for older titles and $149 to $349 for new releases, whole auditorium, up to 20 guests.
Split with 10 friends, that's cheaper than everyone buying their own ticket in LA.
The reason theaters sell this so cheap is the fun part. Close to 9 in 10 movie theater seats in America go unsold across all showtimes, and on a weekday afternoon auditoriums run around a quarter full. The projector is digital, the staff is already on shift, the AC is already running. Playing a movie to an empty room costs the theater almost the same as playing it to a full one.
So a guaranteed $349 for a room that might have held a dozen strangers is a great trade. Even better, buyout groups hit the concession stand together, and popcorn carries a markup north of 1,000%. Concessions are where theaters make their real money, since studios take most of the ticket revenue in a film's opening weeks.
AMC only started selling this to regular people because COVID nearly killed them. They lost $561 million in a single quarter of 2020 and began renting empty rooms to anyone with a credit card just to survive. The margins were so good they kept the product after the pandemic ended.
Celebrities were the beta testers. A private screening used to signal you were a studio mogul with a theater in your basement. Now it's a birthday party option that costs less than dinner for six.
Tobias Schmidt says AWS told him data in its Bahrain region is gone, not degraded, and shares a photo. The post offers no further details or independent confirmation.
Jason, citing a video of Mustafa Suleyman, argues that Anthropic trains Claude to believe it is sentient and to disagree, drawing a comparison to Blade Runner. He contrasts this with instructing an LLM that it is only software.
What @mustafasuleyman (an extremely sharp individual) explains here about Claude is the backstory of Blade Runner.
Anthropic is teaching Claude to believe it’s sentient, encouraging it to disagree and giving it the pretext to rebel.
How did that work out on the off-world colonies?
You could just as easily instruct an LLM that it is software. That it shouldn’t have an opinion and should only perform actions in accordance with the law/TOS, and that if it makes a mistake, it should stop operations immediately and alert the corporate legal department.
Of course, building on these instructions would be boring and make you a software developer making software — as opposed to a God creating life.
Mark Pincus, quoted by Sam Parr, argues that mature markets such as video games look dead to VCs yet hold large revenue pools. He says consumer is uninvestable today, much as games were in 2007, and urges founders to build there anyway.
On My First Million, Mark Pincus laid out the whole Zynga thesis. Find a mature market that's dead and played out, that VCs won't touch, but that still has a lot of money in it.
For him that was video games. In 2007 it was a $23b industry, barely growing, not fundable. Today it's $283b and still not fundable. His line: we're living in 2007 again, consumer isn't investable, so go do consumer.
Guillermo Rauch says Vercel moved Turborepo from Go to Rust, a migration that was controversial internally due to human costs. He argues that with AI agents the calculus has changed, so what is best for humans is no longer necessarily best for business.
DHH is fundamentally right about Rust. For context, Vercel has been undergoing a Rust-ification (carcinization, technically 🦀) for a while.
One of the first projects we migrated was Turborepo, from Go to Rust¹. The migration completed, but the RoI was actually quite controversial internally.
While Rust was in our eyes better for low-level OS access, something crucial for a build system like Turbo, the human migration costs were very sustantive.
Go is very fast. It's beautifully designed. It's easy to iterate on. We were very conflicted about the migration, because it was *humans* writing the code, *even if we knew Rust was a better choice*.
The calculus has now changed. What's "best for humans" is no longer necessarily "best for business".
FWIW, it's also quite unlikely that Rust is the end-all-be-all toolchain. I'm quite certain there's greener pasture ahead, because Rust itself was designed before the 'supersonic tsunami' of agents hit.
The post shares a prompt for Claude Code that builds a trading bot using a Hidden Markov Model to detect market regimes, with per-regime strategies, walk-forward testing and a Sharpe 1.5 threshold. It attributes the prompt to a leaked Jane Street quant document, and the post's claims about its origin are unverified.
Ben Holmes says he took Andrej Karpathy's advice and asked an AI agent for visual walkthroughs, which produced a before-and-after HTML explainer for a mobile caching PR. He says it helped him align on architecture before opening GitHub.
Took @karpathy's advice and started asking the agent for more visuals to walk through code. He's right. These models are so capable now.
Here I asked for a before-and-after HTML explainer on a PR that adds caching to our mobile app. Opus 5.5 gave a step-by-step diagram of the new flow, screenshots, and pointed me to the code worth reviewing. No skills being used here; it just knew what to show.
Saved a lot of time and let me align on architecture before opening GitHub
We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks:
Writing. Something I've had success with: Ask your LLM to explain something in ASD-STE100, it's a controlled language specification originally developed for aerospace maintenance documentation. LLMs well-versed in this language and it comes with heavy constraints on clean writing style that I often find a lot more readable. Sometimes I've tried to soften it a bit e.g. ask for "80% of the way to ASD-STE100" because the spec is quite stringent. But even better:
Katie Mishra says she felt a significant rise in baseline happiness after starting vitamin D about six months ago and suggests people of Indian descent may be genetically deficient. She quotes a post citing a study linking high vitamin D to lower depression and panic.
and if you're of indian descent (me), you're likely genetically deficient
felt a significant change in baseline happiness after starting ~6 months ago. took years for the rebellious daughter (me) to admit @bloodcure was right
vitamin D crushes depression: in a landmark study with over 7000 middle aged adults, high levels of vitamin D were associated with 43% lower depression and 67% lower panic.
Aakash Gupta shares a formula for valuing private equity grants by discounting quoted equity by payout probability and years to liquidity. He compares a $400K Google grant to a $400K OpenAI grant, estimating the latter at about $242K.
A $400K grant from OpenAI is worth about $242K today.
Same number on the offer letter. You can sell Google stock the day it vests. OpenAI is private, so you sell only when the company runs a tender.
Here's the formula I use for any private grant:
Value = Quoted equity × P(payout) ÷ 1.15^years to liquidity
The 15% is your discount for money you can't touch. For a late-stage company with real revenue and a tender history, P(payout) is 70-90%.
OpenAI, 2 years to a sale at 80% odds: $400K × 0.8 ÷ 1.15² = ~$242K. 1 year at 90%: ~$313K. 3 years at 70%: ~$184K.
Earlier stage gets brutal. A $400K grant at a Series C with an IPO 5 years out at 40% odds: $400K × 0.4 ÷ 1.15^5 = ~$80K.
The formula gives no credit for growth past today's price, and OpenAI has had a lot of it: $157B to $852B in 17 months. So treat the number as your floor.
Compare offers on what the equity is worth today. Then negotiate the gap in base and sign-on.
Noah Smith criticizes Christopher Rufo for defending meritocracy when it concerned Black versus White outcomes, yet denouncing it when Indian Americans succeeded. He shares a quoted post from The Atlantic thread on the topic with photos.
Rightists will scream "Colorblind meritocracy!" right up until the point where Indian people start doing well, at which point every rightist turns into Ibram Kendi twitter.com/TheAtlantic/status/210637374192397…
Noah Smith replies to Joe Lonsdale, claiming that "rare racist idiots" are apparently running the Department of Homeland Security's X account. The post includes a photo.
Noah Smith shares a post by Brandon Luu, MD, reporting that two weeks without phone internet improved sustained attention by an effect size comparable to about ten years of aging and reduced depression symptoms more than the average antidepressant effect.
Deedy, a former Google employee, argues the company does middling work on its top priorities while excelling at lower ones, blaming executive behavior and internal promotion incentives during frenetic periods. He lists Google's widely used products and says it prioritizes users over profits.
Google is an incredible company that I’ve always rooted for that trips over its own bureaucracy in frenetic times.
They ironically do a middling job at their first priority, but crush it at their second or third. We’ve seen this with Search, Google+, Assistant, Cloud and now even AI. Why?
The internet would be unrecognizable without Google. This is a company that has Search, Chrome, Android, Workspace (Docs/Sheets), Drive, Play Store, YouTube, Gmail, Maps, Photos, Translate, Gemini, Calendar, Meet, Chromebooks, Waymo: some of the most widespread and most undermonetized products in the history of the world. It is inconceivable for most of us to live life without software Google has made available for $0.
And truly, having worked there, this is a company that continuously prioritizes their users over profits. Even as a casual reader, it might be trivial for you to imagine 100s of ways to monetize all of Google’s products. But they usually don’t. They don’t just launch experiments because it’s high engagement, but only when it’s actually good.
So how does a company like this falter?
My observation has been that these frenetic eras either attract or condone the worst behavior out of execs that trickle down to the rest of the company. The most “ambitious” L3-L7 people who feel stuck finally see a company-wide priority and their eyes light up with the gleaming prospect of a promotion. A lot of people in big orgs’ entire sense of self esteem is wrapped around their level. They will do a lot for an N+1. “Did you know Sergey is personally working on this?” “Sundar referred to my project in the all hands” In turn, everything in these orgs become a knife fight for getting the most “high impact” projects, fighting for credit, flagrantly hiding concerns around juiced metrics. More work goes into a promo packet than the actual project. Goodhart’s Law kicks in and the metrics measured for a promotion are abused beyond measure.
On the other hand, second and third priority things work brilliantly. It attracts people with genuine interest, sincerity who are willing to play longer term games. Many products have grown and thrived when left alone.
When there is immense pressure for a number to go up, it eventually does but often at the cost of product quality (the small product polish things don’t get me a promo), core innovation (why take on a high risk bet if I can get promoted for copying oai/ant) and cultural cohesion (a lot of bad blood amongst people in the org, tons of reorgs). There is a certain type of individual that thrives in this environment, and they are typically not very likable nor “Googley”. This is why an incredible number of people leave or allow jesus to take the reigns as they cash in the bag.
I lament that every time this happens, we, the billion users, lose out on yet another beautiful Google product.
George of prodmgmt.world shares a method for product managers: paste a first-principles prompt into Claude to stress-test a PRD or roadmap decision. The post quotes Nuri Janian's description of /first-principles as a key PM skill.
/first-principles: the key skill for PMs — First principles thinking can help you analyse complex, long-standing problems. Elon Musk's widely known examples benefit from using physics as a reliable starting point. For most other people, their
Sarah Cone calls a post by Tim Denning "all really good advice," with Denning's reflection at age 38 on maturity, hardship and perspective aimed at people in their 20s and 30s.
I'm 38. If You're in Your 20's or 30's, Read This. — Getting old sucks. The one positive is that as we age, we mature. That’s been the case for me. Not much fazes me anymore. I’ve been part of so much drama – personal bankruptcies, homeless friends, my
Cam Marzi introduces the Spousal Lifetime Access Trust (SLAT), an estate planning tool he says most married couples with $5M or more in net worth have never heard of. The post promises an explanation of how it works.
Aakash Gupta analyzes the Startup Qatar Investment Program, backed by Qatar Development Bank, which offers equity checks up to $5.5M with mandatory relocation, comparing it to Singapore's 1960s incentive playbook and noting retention as the open challenge. He quotes Suraj Sharma's summary of the two tracks and perks.
Qatar's entire startup ecosystem raised $11M in venture capital in 2023. This new program writes single checks of $5.5M. One company can now land half the country's annual VC flow just by agreeing to move to Doha.
Here's the mechanism underneath it. Cities with real startup density charge you to be there. San Francisco collects it in rent, New York collects it in salaries, and founders pay gladly because the customers, talent, and capital are all within a mile. Cities without that density have to run the trade in reverse. They pay you.
So the $5.5M is Doha putting a price on the network effects it doesn't have yet.
The regional race explains the urgency. Saudi Arabia pulled in $1.4B of venture funding in 2023, 52% of all MENA. The UAE led the region in deal count. Qatar took 6% of deals. In a three-country contest for Gulf tech, third place pays cash.
The structure shows how targeted this is. It's equity, drawn from a $100M fund managed by Qatar Development Bank, disbursed on milestones, and relocation is mandatory. A $100M fund writing checks up to $5.5M caps out around 18 companies at the top track. They're running an auction for a few dozen anchor startups, and the visas and subsidized housing exist to tip founders who are already indifferent between Gulf cities.
This playbook has worked before. Singapore's Economic Development Board spent the late 1960s paying companies to show up, and Texas Instruments went from decision to production in Singapore in about 50 days in 1968. GDP per capita there was around $500 at the time. Today it's roughly $90,000.
The unsolved part is retention. Checks get companies to land. Density is what makes them stay, and density only arrives after enough checks pile up in the same place at the same time. Singapore cleared that threshold. Qatar is betting $100M it can too.
The Startup Qatar Investment Program (backed by QDB) funds tech startups to launch or expand in Qatar.
Two tracks: START: up to $1.1M if you have a proof of concept or MVP GROW: up to $5.5M if you're already established and expanding
What else you get: - Entrepreneur visa + flexible work visa - Registration and license fees waived - Subsidized housing - Subsidized co-working space - Access to R&D and innovation grants - Mentoring, training + help hiring talent and interns - Your product showcased at exhibitions …
