
Making the world a safer place at @angelcamcom. Co-founder @StartupYard, @Node5legacy. #500strong #startups #IoT #ConnectedSecurity
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Peter Ocasek retweeted
My quick takeaways on the Anthropic S-1:
1. This is a historical moment
2. $6.6M in revenue per employee!! Hard to even comprehend how good that is but Anthropic is AI native as it gets so makes sense.
3. I always thought OpenAI would drop their S-1 first
4. Customers spend about 9x more after a year. Net Revenue Retention is approximately 900% as of Sep 30, 2026. Good SaaS companies brag about 120%.
5. Cowork is growing faster than Claude Code did. Goes to show you the demand for consumer products. Duo will probably rip.
6. 3 years ago this company did $41M in revenue. In the first six months of 2026, it did $16.3 billion. I don't think anyone has a mental model for that curve yet, I sure don’t.
7. Nearly half of revenue comes through cloud marketplaces. About 48% comes from customers buying through them. Big companies buy where their budget already lives, and the lesson for founders selling to enterprises is to get listed where your buyers already spend.
8. Their run rate formula is published: the last 28 days of usage times 13, plus subscriptions times 12, which i guess is the new ARR math for founders?
9. It looks like They're merging Cowork into Claude dot au which tells you the chat box era is ending and the "go do the work for me" era is here.
10. Thousands of Anthropic employees are about to become liquid at once, so expect the biggest wave of new AI startups and angel checks San Francisco has ever seen. Reminds me when Facebook went public but this is way bigger.
Let’s go!
11. Buried in the filing, Anthropic says the gap between what Claude can do and how widely it's used is one of its biggest growth opportunities, so the company itself is telling you the models are ahead of the market and someone has to close that gap for dentists, landlords, and plumbers.
12. Whatever happens, exciting times to be building in AI.
Anthropic has filed an S-1 registration statement with the SEC related to its proposed IPO.
Read more: anthropic.com/news/s1-sec
Legal disclaimer: A registration statement relating to these securities has been filed with the SEC but has not yet become effective. These securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post does not constitute an offer to sell or the solicitation of an offer to buy these securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction.
Peter Ocasek retweeted
This is an excellent example of how to document company lore.
The Slack story is a compelling illustration of a startup with clear values getting absorbed by a massive corporate machine.
It’s a wild read for startup people, maybe unsurprising for anyone who has worked in a big company.
“I only got about one hour of total facetime with Marc before the deal was announced. My last meeting with him was cut short because McConaughey arrived,”
Matthew McConaughey is paid $10M a year to be a spokesperson for Salesforce.
Latest (and probably penultimate) Building Slack post is up: buildingslack.com/salesforce…
What it's like being eaten by the whale
Peter Ocasek retweeted
If you've ever wondered why smart TVs are so cheap, this is why.
@log4j rooted his Samsung and found an always-on hot mic, automatic content recognition, geolocation, network mapping, ad targeting and user profiling, shared with Samsung's "400 partners".
A lot of it can be blocked in <15 min, wrote a basic guide below.
What your TV is doing
The main culprit is ACR (automatic content recognition). Your TV screenshots what's on screen, fingerprints it, and sends it home to build your ad profile. Samsung does it every 500ms, LG every 10ms [1].
What is insane: it happens on connected devices too.
Plug in your laptop, your console, your work machine, and your TV can fingerprint that via HDMI [1].
He also found that if your Samsung doesn't have a mic, it'll look for one from a connected soundbar or bluetooth device.
nitter.gq/log4j/status/211376224…
It's on by default, and you likely agreed to it on the setup screen you clicked through in 10 seconds.
Step 1: Turn off ACR
Samsung: Terms & Privacy → Viewing Information Services
LG: Live Plus
Vizio: Viewing Data
Roku: "Use info from TV inputs"
Sony/Google TV: Samba Interactive TV
Menus vary by model, but those are the names to look for. While you're in there, opt out of interest-based ads, reset your advertising ID, decline every optional privacy agreement, turn off voice recognition, and delete apps you never open.
Step 2: Give smart devices their own network
Put the TV, cameras, speakers and vacuum on your router's guest/IoT network. The logic is simple: these devices rarely get patched. If one gets compromised (getting drastically more frequent with AI), it shouldn't be able to see your other devices or home network.
Step 3: Block trackers for the whole house with DNS-level filtering
NextDNS (cloud-based) is easy and has a solid free plan. Pi-hole is a little bit more work if you prefer self hosting. For simplicity we'll focus on the former.
1. Sign up at nextdns.io (free tier is plenty)
2. Privacy tab: add a blocklist (OISD is a good bet) and turn on Native Tracking Protection for Samsung, LG, Roku, Amazon (see attached image)
3. Setup tab: copy your endpoint
4. Paste it into your router's DNS settings as DNS-over-HTTPS/TLS (or use the IPs + "Link IP" if your router only does plain DNS)
5. Bonus: block outbound port 53 except to your router. Some devices hardcode their own DNS to get around you
Then open the NextDNS logs and watch how often your TV phones home. It's eye-opening. If an app or update breaks, find the domain in the logs and allowlist it.
Why they do this
TV prices are down 97% since 2000 [2]. Most of that is better manufacturing and brutal competition. But once margins on the hardware hit zero, the cost moved to you.
In Q3 2024, Vizio lost $6.7M selling TVs and made $115.8M in gross profit from ads and viewing data [3]. They've said on earnings calls that they keep TV prices low to grow the audience they sell to advertisers. Walmart bought them in 2024.
This isn't a conspiracy theory either. Vizio paid $2.2M to the FTC in 2017 for tracking 11 million TVs without consent. Last December, Texas sued Samsung, LG, Sony, Hisense and TCL over ACR. Samsung and LG have since agreed to stop collecting that data without explicit consent [4].
TL;DR
1. ACR off
2. Ads + voice off
3. Smart devices on their own network
4. NextDNS filtering on the router
Sources:
[1] ACR study: arxiv.org/abs/2409.06203
[2] Cost of US consumer goods: aei.org/economics/chart-of-t…
[3] Vizio Q3 2024: sec.gov/Archives/edgar/data/…
[4] Texas v. Samsung: texasattorneygeneral.gov/new…
Peter Ocasek retweeted
My kids now have to solve age appropriate math problems before each episode of Bluey, thanks to the miracle of AI reverse engineering and upgrading my TV 🔥🔥🔥
Peter Ocasek retweeted
Foursquare was acquired last month. The outcome was disappointing. It's taken me a while to write this, but I think I'm finally done grieving it. Here are some thoughts on our final years, an effort to honor the team who helped build & maintain FSQ's legacy, and my attempt to finally get some closure. teendrama.substack.com/p/som…
Peter Ocasek retweeted
Replying to @dhh
A very bitter pill to swallow: peace is only secured through violence or the possibility there of.
Every nation has police, military, etc... Pacifism is a noble ideal but not a real possibility in this world.
Before: hoping.
Now: knowing.
Your camera records for the one day it matters. Angelcam now makes sure that footage will be there, clear and correctly timed.
Catch camera problems. Before the footage lets you down.
New in Angelcam: AI video defect detection. It flags what “online” hides:
🎯 Camera moved
🕷️ Lens blocked
📺 Image artifacts
⏰ Wrong clock
Runs daily, weekly or monthly. Included in every plan.
angelcam.com/video-defect-de…
Peter Ocasek retweeted
10x a year for 3 years? I've seen a lot of growth, and that is truly exceptional. It's not unusual for startups to grow 10x in a year, but to keep it up for 3 years is close to unheard of. That's 1000x.
Exa just passed $100m in annualized revenue.
We've grown almost exactly 10x per year for 3 years. We now handle 2 billion requests a month from 200k+ teams. And it’s still so early:
We predict agents will search 1000x more than humans by 2030.
Agents don't search like humans. They write long, complex queries and want all the world's data, not just the web. We've spent 5 years building a search engine designed for them.
We now serve personal agents, AI labs, coding agents, GTM agents, really any agent. Exa gives these agents access to 100s of billions of web documents and tons of proprietary data.
Our customers are increasingly noticing that information is the bottleneck to agent performance. While the world seems close to perfect intelligence with models like Fable and Astra, we are very far from perfect information.
To our small but legendary team, thank you for getting us here, from engineering to research to GTM to ops.
To our customers, it is an honor to serve you. We have some exciting releases coming soon and can't wait to share them 🫡
Peter Ocasek retweeted
New on our Engineering blog: Creating in-house source control.
In May, we merged around 2,500 code changes per day. In September, we merged more than 30,000 per day. As a result, we became bottlenecked by developer infrastructure built for human (rather than agent) scale.
Here, we share how we built a new version control system—and fully migrated our monorepo from git—in five months: anthropic.com/engineering/re…
Peter Ocasek retweeted
Assorted things I've been mulling over regarding agents in the economy:
• Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies.
• How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be.
• In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good!
• It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.)
• A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to).
• Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big.
• Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions.
Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.
Peter Ocasek retweeted
We just let in every Pro and Max user from the Claude Code Projects waitlist!
If you're new to Claude Code Projects, here's a 4 minute walkthrough to get you started:
Peter Ocasek retweeted
After six years in stealth, Atomic Machines is out. Our mission: on-demand, universal command of matter. First beachhead: the Matter Compiler, an AI-native manufacturing system that builds working micro-machines from code alone. No per-product tooling. No process development. Different code, different machine.
Peter Ocasek retweeted
Four vertical AI companies. Four industries. One pattern.
They all built their moat on top of the same models everyone else can rent.
OpenEvidence trained on 35 million peer-reviewed papers through licensing deals that took years to negotiate. Scores 82.7% on HealthBench Professional, 12.1 points above the best frontier model. 350,000 clinicians use it. OpenAI could build the tech. They will never spend what it takes to secure that content. Too expensive. Too vertical. Too long.
Hippocratic AI hired 6,234 licensed clinicians. Average 11.5 years of experience. Evaluated 307,000 real patient calls. Clinical accuracy went from 80% to 99.38%. Severe harm errors driven to zero. Anthropic is not hiring 6,000 nurses. Not their business. But it is Hippocratic's entire business.
Harvey wired into law firm workflows in ways no horizontal model ever will. Beat human lawyers on four of seven tasks in the Vals Legal AI Report. Document Q&A: 94.8% vs 70.1%. Transcript Analysis: 77.8% vs 53.7%. The model companies did not do that. Harvey did.
Abridge cut clinical transcription errors by 83% on new medications. Beat Google Medical ASR by 24% on word error rate. Google has spent a decade and unlimited budget on medical speech. Abridge still wins. Because Google does not care enough about the last mile. Abridge does.
None of them competed with the model companies. They used them. Rented the horsepower. Built the scaffolding the model companies would never justify building.
That is the entire play. The model companies gave you commodity intelligence priced per token. Your job is to wrap it in ten years of industry context nobody else has.
"We're about to see an absolute bloom in software development as the price of development plummets and everyone realizes how much automation we still have left to do in this world... Don't go down with the pencils. There's so much to build. We need you." world.hey.com/dhh/over-my-de…
For decades, researchers have sought materials that sort electrons by spin while their magnetism cancels.
In 3 days, 90+ Opus 5.5 agents helped us uncover two room-temperature magnetic semiconductor candidates in simulations: YBaMnFeO₅ and KV[Cr(CN)₆].
KV[Cr(CN)₆] was synthesized back in 1999. Its predicted ability to sort electrons by spin appears to have been hiding in plain sight for 27 years.
Peter Ocasek retweeted
Wow, @hark_labs made a straight up superior @Muse. Its harness fully supports computer use (pretty fast, at that) in an isolated sandbox with vault-based auth you can reuse across any app (huge for Google), and you can actually see the "computer" being used in the cloud. Plus, its UI is so clean and such a refreshing take compared to most cluttered 3-column chatbot interfaces.
Easily the best personal AI offering on the market right now and the most "task-capable" agent on the AI growth curve.
Peter Ocasek retweeted
Václav Havel was a hero of mine, and of so many others born behind the Iron Curtain. His humanity and humility were backed by courage and an unerring moral compass.
Peter Ocasek retweeted
Today, Nolla Health became the first organization in the U.S. (and possibly the world) to receive regulatory approval for an AI to issue initial prescriptions.
This makes Nolla the first ever actual end-to-end AI doctor.



































