One of the rarest and most lethal skills a person can master is REFUSING TO DIE
As you grow in age you’ll see how everyone dies around you
The “gangster” you knew in high school dies and becomes a barber
The trust fund kid dies, unable to 10x his dads networth, lapped by random people he never knew existed back in the day
The tall pretty boy that girls were naturally drawn to dies and becomes mortal, cucked by some bitch
The guy who was cool, a threat when he was 20 dies and becomes some worm at 30 - couldn’t sustain the same energy for decades
Most people “die” as they age and face real problems. The key is to remain retarded forever and to refuse to die - no matter what happens.
Winning long term depends on your ability to stubbornly retain childlike traits like foolish optimism, playfulness, relentless risk-taking and refusal to become jaded or “realistic” in a defeatist sense.
Namaste.
Iranians genuinely believe in the idea of martyrdom.
If the death of one member make the movement stronger, how can you believe you will kill to defeat such a people?
With the blatant aggressive style Israel has adopted in recent years, an American president will sooner than latter get the mandate by running an "anti-Israel campaign".
Prediction: In the AI age, taste will become even more important. When anyone can make anything, the big differentiator is what you choose to make.
https://t.co/3GQUlfH58t
AI coding agents offer the best glimpse into what the future of agents will look like in many other fields of knowledge work.
AI coding has accelerated faster than any other AI space because the builders of AI understand their own workflows deeply, and they’re incentivized to improve it for their own productivity.
It’s also a great petri dish because the ecosystem will adopt new tools (and dump old ones) faster than other space, which gives you better signal faster to what paradigms work and which don’t. The darwinian forces are very strong here.
While there are plenty of things that don’t translate from coding to other areas of knowledge work, in agents it’s clear that we’re starting to see the formulation of the core primitives for agents in knowledge work.
These foundations include: background agents that you kick off in a simple GUI or via another logical trigger, the ability to track their progress, add in relevant context, ability to pull in additional signal and tools, ways of reviewing the work and output at the end of the workflow, creating custom agents on the fly when workflows are repeated, and so on.
We’re in the earliest phases of what this will look like across software, but the fuzziness that we had a year ago is starting to get a bit more clear by the day. Incredible times ahead.
Considering that most human knowledge manipulation will now happen inside llms, what does that imply for search going forward? llms indexing themselves?
New essay: Viral Loops
From the inception of PayPal, Peter Thiel focused on viral distribution for both practical and philosophical reasons. Practically, he knew his small startup could never acquire millions of users through conventional marketing channels. Philosophically, he drew on René Girard’s theory of mimetic desire and believed that people mostly borrow their desires from others. Girard developed the theory to explain how imitation can escalate into rivalry, contagion, and even collective violence. Thiel saw in it a framework for technology adoption: if you could get a small group to want something and spread it, others would follow in a predictable cascade.
PayPal’s breakthrough came when the team realized money could be sent to anyone with an email address. That made the product inherently viral: every transaction pulled new people into the network because recipients had to create an account to get their money. Then they amplified it with a referral bonus that paid $10 to both inviter and invitee. At first $20 per user might seem like a lot, but in the middle of the dot-com boom when companies were spending hundreds of dollars to acquire a single customer, it was relatively efficient.
In November 1999, PayPal’s 24 employees seeded the network by emailing their friends with the subject line “PayPal User Beamed You Money.” Growth took off immediately. In five months, they went from a thousand users to a million, compounding at 7-10% a day. As the loop strengthened and network effects kicked in, they reduced the bonus to $5, then phased it out entirely. Two years later, PayPal went public and was acquired by eBay for $1.5 billion.
Ex-PayPal employees would go on to build their next companies around virality. The YouTube founders used an embedding strategy to spread their videos to millions of people on MySpace. Reid Hoffman devoted roughly 80% of LinkedIn’s early resources to viral growth. And it wasn’t just PayPal alumni. Facebook, Dropbox, Twitter, and almost all of the fastest-growing Web 2.0 companies relied on similar dynamics. In fact, the user bases for these products grew so large, so fast, that no traditional marketing channel could have created them.
Marc Andreessen eventually gave this distribution strategy a name: the viral expansion loop. Any strategy to grow virally begins and ends with a loop: someone tries your product, tells others, and some of those people become users too. Then the cycle repeats. The exponential growth these loops produce make it possible for founders in the internet era to build billion-dollar companies simply by designing their products the right way. No sales team or marketing budget needed.
In practice, viral loops take several forms:
- Word of mouth. The purest kind. The product is so remarkable that people tell others about it. Facebook’s earliest growth on college campuses was mostly word of mouth before they started building more explicit viral hooks (e.g. email invites, adding your friends via address books, etc.). Word of mouth drives the growth of many movies, books, diets, and TV shows.
- Inherent virality. The product only works if others use it. WhatsApp, Slack, and Zoom fall into this category. Facebook even manufactured it by refusing to launch on a campus until half the student body joined a waitlist.
- Collaboration. The product is useful alone, but better with others. Google Docs and Dropbox folder-sharing are good examples. This loop can take longer to spread if your customers don’t immediately need to collaborate, but once they do, strong network effects kick in and it’s extremely sticky.
- Communications. Every use advertises the product. Hotmail’s ”Get a free email account with Hotmail” default signature is the most famous example. Every email a customer sent spread the word about the product.
- Content. The product spreads through the media it helps people create. TikTok and Instagram grew because people saw watermarked videos and photos with cool filters on their Facebook and Twitter Feeds.
- Referrals. Direct incentives to spread the word like PayPal’s $10, Dropbox’s free storage, and Amazon’s Affiliate program. At one point, half of Uber’s new users came from referrals.
- Embeddings. Features designed to spread your product across the web. PayPal built software that let eBay sellers to automatically add a “Pay with PayPal” button to all of their listings. YouTube built a code snippet that let users embed a video on any website. Airbnb built a tool that let hosts cross-post their listings to the much-larger Craigslist.
The strongest products stack multiple loops on top of one another. Take PayPal for example. The payment product was inherently viral because sending money forced recipients to sign up, but the team amplified this with referral bonuses and embedded payment buttons.
To know if a loop is working, you have to measure two things: the viral coefficient and the cycle time. The coefficient (K) is how many new users each user brings in. If every customer invites ten friends and 20% convert, K = 2. Any value above 1 produces exponential growth. Cycle time is how long it takes the loop to spin. The shorter the cycle time, the more frequently the loop compounds. YouTube’s was minutes, which is why it grew so explosively: watch a video, share it, friend joins.
Small improvements in either lever bend the curve disproportionately. A modest increase in conversion or a slightly faster cycle time compounds into enormous outcomes when repeated thousands of times. That’s why great teams obsess over friction. Every second shaved from the path to value increases conversion and accelerates the loop.
However, it’s important to keep in mind that virality and retention are inextricably linked. Bringing new users in through the front door doesn’t help you grow if they immediately turn around and leave. Instead, you should think of retention as prerequisite for viral growth and a multiplier. A product people use every day has thirty opportunities a month to generate new invitations; a product they use once has only one. The math of the viral coefficient still applies, but you have to think of it across many sessions. This is why the highest retention products are almost always the most viral.
Viral loops aren’t magic. They are mechanisms, and like all mechanisms they either work or they don’t. Properly designed, they are the most powerful form of distribution available to startups. But they only endure when anchored in real product value and strong retention. Without those foundations, even the most spectacular loop collapses into nothing more than a temporary spike.