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@"Cracking the Digital Code: Mastering Social Media Strategy in the Age of #AI "linkedin.com/pulse/cracking-… on @LinkedIn
Atchison Frazer retweeted
Verkada is worth $5.8B and does close to $1B a year in revenue.
A big part of the machine behind it is cold outbound.
Their reps book about 6 meetings a day each, against 1.5 on the old SDR model.
I broke down their whole GTM strategy:
- The MDR program
- A campaign for every buyer type
- A landing page for every prospect
- Hardware trials
- The partner channel
- The sales hiring programs
Full breakdown is in the article:
Atchison Frazer retweeted
Just got a call from a founder I backed at pre-seed.
He just received a term sheet for his seed round, and I was one of the first people he called.
When I wrote that first check, there was no product, no revenue, and not much interest from other investors. Just a founder I believed in.
Being the first check means you’re there before anyone else. Nights like this are special.
Atchison Frazer retweeted
This might be the first major anniversary of 9/11 where watching the footage really feels like an older world. It was a different world. And those of us who came of age in it have an obligation to never forget what happened that day and after.
To those with no memory of 9/11, I recommend visiting the 9/11 Memorial and Museum. There were so many witnesses to this horrific crime and so many details we never discuss. Too many victims had to make the unthinkable choice about their last moments.
The last time I visited, I stopped on this testimony from a man who witnessed the moment a woman jumped to her death:
"She had a business suit on, her hair all askew. This woman stood there for what seemed like minutes and then she held down her skirt and jumped off the ledge. I thought, how human, how modest, to hold down her skirt before she jumped. I couldn't look anymore."
The other thing you see at the Memorial is just how many heroes were minted that day. How many men ran into the towers knowing they were running towards their deaths. So many people died in service of their fellow Americans that day, and their courage inspired the many men and women of my generation who decided to enlist and serve the country after watching the towers fall.
The legacy of 9/11 is the heroism of our fellow Americans. The courage of so many to lay down their lives for their neighbors. May they rest in peace and may we never forget.
Atchison Frazer retweeted
It’s no secret that I’m bullish on Florida as a federalist project that’s attracting capital and businesses from across the country. It’s an extraordinary place to live and build.
West Palm Beach is the epitome of this kind of growth—and Stephen Ross and team are building a truly dynamic city and ecosystem. It’s been an incredible story of growth in America and we’re excited to become a larger part of it.
The American Dynamism team at @a16z is excited to open our West Palm Beach office.
It's time to Build 🌴🇺🇸🚀
Exclusive: Andreessen Horowitz is the latest venture-capital firm to open a new office in Florida to invest in startup defense companies on.wsj.com/3UGyUmI
Atchison Frazer retweeted
Wow
Quincy, Washington shows what a good data center deal looks like.
About 30 facilities shoulder an estimated 57% of local property taxes, funding a $120M high school, library, hospital, and police and fire stations.
cnn.com/2026/08/11/business/…
The Future Is for Everyone: Free AI Glasses for Every Blind Veteran in A... youtu.be/gatpk6BhN5w?is=wleD… via @YouTube
Brilliant! 🇺🇸
Atchison Frazer retweeted
Beyond the "Viking Row": An Invitation to Explore Norway
To support the Norwegian national team competing on the world stage, the Viking family from across our river, ocean and expedition fleet came together to perform the "Viking Row."
Now, we invite guests to journey with us to Norway, where majestic fjords, distinctive traditions and a rich cultural heritage await: explore.viking.com/3SqvmUL
Atchison Frazer retweeted
MEMORY IS THE MOAT
@nikesharora, Chairman & CEO of @PaloAltoNtwks , interviewed by @HarryStebbings (@20vcFund )
Summary: Nikesh Arora took Palo Alto Networks from an $18 billion company to one worth $225 billion, and his read on enterprise AI is blunt: most companies are doing it wrong, and most of the products are not ready. His core claim is that consumers forgive AI's mistakes while enterprises cannot, so the money will flow to whoever builds the depth (the context, the memory, and the edge-case training) that lets an agent act without a human catching its errors. The companies that win will redesign themselves around AI instead of adding it to yesterday's workflow, and the lasting advantage will be the memory a system builds up about you. He expects token prices to fall 90%, half of G&A roles to disappear in 3 years, and more engineers and salespeople, not fewer.
1. Context Stickiness. The lasting advantage in AI is the context a system holds about you, not the model itself. Arora says the frontier labs are racing to remember what you asked over the last 30, 60, 90 days so each new answer gets easier and you stop wanting to leave. The more a model knows about a user, the higher the cost of switching, and that stickiness is the moat. For enterprises the same logic holds: the company that owns its context wins, not the one renting the smartest model.
2. Breadth Versus Depth. The frontier model problem is a breadth versus depth problem. Consumers tolerate false positives and enterprises have none to spare. Arora had Gemini write a passable investment memo in 4 minutes, and a wrong line or two did not matter because a person was sitting in the middle to catch it. An agent acting on its own has no person in the middle, so a false positive becomes a live failure. Consumer AI wins on breadth and brand, while real enterprise revenue comes from depth.
3. The Waymo Standard. Waymo is the biggest agentic product in the world, and it shows what depth actually costs. Replacing one human, the driver, took tens of billions of dollars of edge-case training and data that exists nowhere on the internet. You cannot drop the next Anthropic model into your Mercedes and tell it to drive you home. Every enterprise agent that truly replaces a person needs that same depth, which is why most agentic enterprise products are not ready.
4. Rethink The Workflow. Most enterprises are losing because they add a little AI to an old workflow instead of redesigning the workflow around AI. Arora's example: scanning an invoice 20% faster is the trap, while the real win is letting AI do 80% of the thinking, like reading every CV and telling you which 20 people to interview and what to ask each one. That means giving up human control, which is exactly what companies resist. The winners over the next 3 years rethink the company with AI, not the task.
5. Software With Opinions. The next wave of enterprise software will have opinions, and that is the real change Arora is pointing at. Coded SaaS gives you the output you defined for the input you fed it. An AI marketing assistant reads your copy, tells you it is off-brand, and says how to fix it. That opinion makes an average employee smarter, which is why Arora expects half the people in G&A functions like marketing, finance, and HR to be gone within 3 years.
6. More Engineers, Not Fewer. The fear that AI shrinks headcount is half wrong. Process-heavy G&A roles compress, but Arora wants more technical and more sales people. His teams keep asking for resources to rework marketing and HR, and for people who can prompt frontier models, build harnesses, and bring in data nobody else has. A good product also needs more sellers: he met 20 customers in Europe last week and half did not know what his 20-year-old company already ships.
7. Tokens At One-Tenth. Long-term token pricing should be a tenth of what it is today. Compute costs 2 to 4 times what it did 2 years ago because more than half of it feeds loss-making consumer AI, which forces the pricing pressure onto enterprise and coding workloads that have to pay. As compute gets more efficient and consumer usage gets capped, prices fall hard over the next 3 to 5 years. The model from 2 years ago was already good enough for 90% of tasks; the problem was it cost too much to run.
8. The Token Allocation Trap. Capping token spend punishes your best people. Arora runs a "use judiciously" model, not a free-for-all, because the smartest AI-savvy employee can burn 20 times the tokens of an average one. Playing whack-a-mole with cost hurts the high performers most and slows the learning you need. The better move is to track usage, leave the power users alone, and cap only the genuine outliers.
9. The Attacker's New Edge. Powerful coding models cut both ways. Trained to write good code, they are just as good at finding bad code. Pointed at his own systems, a model found in 6 weeks what would have taken his team 5 to 6 years. It cannot safely auto-patch, because it would "fix" 30% of things that are not broken, so it arms attackers faster than defenders. The result is urgency: every enterprise has to fix its systems faster, which is good for security companies.
10. The FTE Tell. If a startup needs forward-deployed engineers to sell into the enterprise, the product is not finished. Arora's read: enterprise AI is barely 12 months old, agents keep changing what the product even is, so vendors send engineers to build the product inside the customer while the technology keeps moving. A real forward-deployed engineer brings code back and folds it into the product; many are just adoption consultants. Expect customers to churn from one tool to the next, the way coding went from Windsurf and Devin to Codex, Claude, and Factory.
11. Three Missed Tricks. Miss one trick and you survive, miss two and you are partly impaled, miss three and you could be obsolete. This is why Arora spends more time than ever learning, pinging founders building things he does not yet understand. He buys early and cheap on conviction, treating an acquisition as a 10x or 100x bet where paying 1 or 2 times more does not matter, rather than waiting to buy the proven winner for a billion. He runs a twice-weekly "AI EIO" meeting so his top 15 leaders compete to show what they shipped.
12. The Sunk Cost Walk. A board member taught Arora to separate effort from wanting the outcome. After months grinding through a near-billion-dollar acquisition, he was told to take a long walk and ask one question: if this deal walked in the door right now with zero effort, would I still write the check? You have not spent a dollar yet, so the only thing that counts is whether it stands on its own merits. The same trap catches investors who confuse beating 8 VCs to a term sheet with the deal being good.
My new roundtable, This Week in AI, just hit 11 episodes, and we are getting the greatest minds every week.... week after week.
If you want to go deep on AI, it's worth subscribing... thanks, @matanSF, @dsa, and @gsivulka, for a great discussion this week!
follow @ThisWeeknAI
"Any feature we release, a competitor could release within two weeks."
@MatanSF (@FactoryAI) on why the moat isn't software anymore. @dsa (@livekit) on building the framework for voice, video, and physical AI. @gsivulka (@HebbiaAI) on what it takes to win in vertical AI.
They join @jason on This Week in AI, Episode 11:
00:00 Intro & AGI debate
03:30 Factory: autonomy for software engineering
04:29 LiveKit: open source to ChatGPT voice
10:31 Hebbia: AI for capital markets
13:21 SpaceX-Cursor $60 billion deal breakdown
26:28 Moats in the age of vibe coding
38:10 Deterministic agents vs. open chaos
45:56 DeepSeek V4
01:05:23 OpenAI's spend problem
01:12:08 P-doom scores
Atchison Frazer retweeted
A good assessment of the NYC political situation.
⚡️The real signal is that a city that produces a meaningful fraction of global financial output just elected someone running explicitly on taking property from the people who produce it.
This is not a protest vote. This is the coalition stating its actual preferences. The preferences are incoherent with the city continuing to function as a financial center. One of those two things is going to give. The city is going to stop being a financial center, or the coalition is going to be politically defeated, or Mamdani is going to govern nothing like he campaigned. The third option is the most likely because it’s the standard pattern, but the first two are live.
The actual structural situation in New York: the top 1% of filers pay roughly half the city’s income tax. The top 10% pay around 75%. The math is that a small number of high earners subsidize services for everyone else, and the subsidy is what makes the city livable for the people who aren’t high earners. When those earners leave, the subsidy leaves with them, and the services they were funding get cut or the taxes on the remaining population rise. There is no version where you tax the rich into staying. They have options. The options are better now than they were five years ago and will be better in five years than they are now. Every marginal tax increase moves the departure math.
Mamdani’s voters believe the rich will pay more and stay. This is empirically false and has been for decades. The Laffer curve is a caricature but the underlying phenomenon is real at the state and city level because the substitution cost is low. You don’t need to emigrate. You need to move to Connecticut, Florida, Texas, or Tennessee. Millions of people have done this. The pattern is documented, measured, and predictable. Pretending otherwise is the policy equivalent of pretending gravity is optional.
The deeper thing Mamdani’s election reveals: a substantial fraction of urban voters now hold a worldview in which productive activity is theft, wealth is evidence of extraction, and redistribution is the primary function of politics. This worldview has specific intellectual lineage running from certain strains of Marxism through the academic left through social media radicalization. It’s not a serious economic framework. It’s a moral framework dressed as an economic one.
The moral intuition is that inequality is itself the injustice, regardless of how the inequality arose or what it produces. A serious economic framework would ask whether the inequality produces good outcomes for the median person, would note that high-productivity cities produce enormous surplus that funds services, and would balance extraction against the ecosystem that generates the wealth to be extracted. The Mamdani framework skips all of that and goes straight to: they have it, we want it, take it.
This framework, when operationalized, destroys the thing it feeds on. Every case study confirms this. No case study contradicts it. The cases where redistribution worked, Scandinavia in the twentieth century, post-war West Germany, Singapore, involved redistributing from productive economies that were allowed to stay productive. The redistribution was moderate, rule-bound, and applied to a capital base that couldn’t easily flee because international capital mobility was constrained. None of those conditions hold in New York in 2026. Capital mobility is near-frictionless for the high end. Rule-bound redistribution is not what Mamdani campaigned on. The ideological content is much closer to expropriation than to Nordic social democracy.
The broader United States pattern is that this dynamic is concentrated in the cities that already had it, and those cities are where the productive economy is also concentrated. The country has decoupled into two economic models. One model, roughly blue-state urban, runs on high-productivity services, high taxes, high housing costs, declining quality of services relative to what’s paid for them, and increasingly extractive politics.
The other model, roughly red-state urban and suburban, runs on lower productivity but faster growth, lower taxes, lower housing costs, and more functional services. The sorting between the two is accelerating.
People and capital are moving from the first to the second at historically significant rates.
The first model is not reforming because its political coalition is locked in by the voters who benefit from the extractive politics in the short term.
The second model is not free of problems but is currently winning the migration competition by large margins.
Atchison Frazer retweeted
BREAKING: David @friedberg says "California is functionally bankrupt"
"People don't realize how screwed California is, & I worry that if California falls, so does the union.
"$250 billion to $1 trillion short."
"This is because for California to get rescued would be a big cost to red states, & I think it creates in the years ahead a lot of tension."
"California's functional bankruptcy is a major risk to the country. & I think we need to figure out what we can change to fix it."
How we got here:
"California has a public pension system, & that public pension system retirees have paid into it & they get some benefits out, & the amount that they're owed back out is somewhere between $250 billion - $1 trillion dollars more than has been paid in.
$250 billion to $1 trillion short.
If it was the federal government, it would be like, okay, we'll just print more money. California doesn't have the ability to print money, so California has to pay this out, and you can't restructure retirement benefits.
There is a Supreme Court case in California that said that once an employee has been offered retirement benefits, even if they're currently an employee, you can never restructure their retirement benefits.
It has to stay forever, and the state cannot declare bankruptcy. There's no way for the state to functionally declare bankruptcy. There's no law to allow it. No state has ever declared bankruptcy, and the retirement benefits sit senior to the bonds in California.
So you have to pay out the retirement benefits before you pay out all the bond holders that have loaned California the money that they use to run all their programs and services."
Hill & Valley Forum 2026 (@HillValleyForum)
California will be bankrupt by 2030.
If you’re expecting a state pension, it is at risk.
If you don’t believe it, check Grok or Gemini and explore how California politicians changed the reporting rules on your pension so they could hide how underwater it is.
The middle class citizens of California will soon be asked to pay a huge price to bail out the state.
Why them?
Because that is where most of the wealth of California resides. It’s easy to single out “billionaires” but there aren’t many of them and they can and will all leave before the bottom falls out. They are leaving in droves already.
The mismanagement in California is biblical - and the scale is huge because it’s the world’s 4th largest economy.
California politicians and their henchmen are now entering the coverup phase where they can no longer hide their financial incompetence so they are taking from average California residents to try and hide what they’ve done:
You will soon see ballot initiatives with fancy tiles like “billionaire tax”. But those are lies. They are mechanisms to tax everything, every way:
Excise taxes
Wealth taxes
Private property confiscation
It’s all happening now.
If you want to preserve California, you will need to stand up because California has become a kleptocracy.
Atchison Frazer retweeted
My notes with the 12 most powerful ideas & immediate action items.
xitter.cf/AnishA_Moonka/status/2…
Marc Andreessen (@pmarca) just sat down with David Senra for ~110 minutes on founders, managers, the birth of the Internet, and why Elon Musk might be inventing a new school of management.
My notes:
𝟭. 𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀 𝗵𝗮𝘃𝗲 𝘇𝗲𝗿𝗼 𝗶𝗻𝘁𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝗼𝗻.
Sam Walton woke up wanting to build more Walmarts. He did that for decades, never once stopping to examine his inner self. Andreessen says the modern obsession with self-analysis is a manufactured construct from the Freudian movement of the 1910s. Great builders throughout history just built.
We keep encountering this same pattern across every biography we study. The ones who do the most spend the least time wondering why they do it.
𝟮. 𝗧𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝘃𝘀. 𝗺𝗮𝗻𝗮𝗴𝗲𝗿 𝘄𝗮𝗿 𝗶𝘀 𝟭𝟬𝟬 𝘆𝗲𝗮𝗿𝘀 𝗼𝗹𝗱.
James Burnham's 1940s book The Machiavellians describes two modes: bourgeois capitalism (the founder runs it, name on the door, Henry Ford style) and managerialism (a trained professional replaces the founder). Business schools codified the second mode into gospel. The problem? It assumed managers would do a good job. Thirty years of evidence says they can't adapt when things change.
SpaceX settled the debate. No management school prepared anyone for reusable rockets.
𝟯. 𝗘𝘃𝗲𝗿𝘆 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝘀𝗵𝗶𝗽 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗴𝗼𝗲𝘀 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗯𝗮𝗿𝗯𝗲𝗹𝗹.
Andreessen and Horowitz studied private equity, hedge funds, investment banks, law firms, ad agencies, and talent agencies before starting a16z. Every single one went through the same structural shift: the middle collapsed, and what survived was solo specialists on one side and scaled platforms on the other. Department stores died. Gucci and Amazon lived.
The pattern repeats so reliably across industries that spotting it early is almost a cheat code for knowing where a market is headed.
𝟰. 𝗠𝗶𝗰𝗵𝗮𝗲𝗹 𝗢𝘃𝗶𝘁𝘇 𝘀𝗺𝗼𝗸𝗲𝗱 𝗛𝗼𝗹𝗹𝘆𝘄𝗼𝗼𝗱 𝗯𝘆 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗱𝗮𝘆 𝘁𝘄𝗼 𝗵𝗼𝘂𝗿𝘀 𝗲𝗮𝗿𝗹𝗶𝗲𝗿.
Every talent agency had its staff meeting at 9 am, then started calling clients at 10. Ovitz moved his meeting to 7am, started calling at 8, and also called other agencies' clients. By the time the old guard phoned Paul Newman at 11, CAA had reached him three hours ago. Twenty agents would show up to premieres in matching Armani suits, driving Jaguars with plates reading CAA-1 through CAA-20.
Mediocrity is invisible until somebody with a better system shows up and exposes it.
𝟱. 𝗔𝗻𝗱𝗿𝗲𝗲𝘀𝘀𝗲𝗻 𝘄𝗮𝘀 𝘁𝗵𝗲 𝗼𝗻𝗹𝘆 𝗼𝗻𝗲 𝗼𝗳 𝟭𝟮 𝘄𝗵𝗼 𝘀𝗮𝗶𝗱 𝘆𝗲𝘀 𝘁𝗼 𝗝𝗶𝗺 𝗖𝗹𝗮𝗿𝗸.
Jim Clark was the most famous founder in Silicon Valley at the time. Silicon Graphics had built the machines behind Jurassic Park and Terminator 2. He invited 12 people to dinner to join his new company. Only Marc Andreessen, a 22-year-old, said yes. That dinner became Netscape.
The single most underrated skill in the world might just be the willingness to say yes when the opportunity is real, but the outcome is uncertain.
𝟲. 𝗝𝗶𝗺 𝗖𝗹𝗮𝗿𝗸 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗲𝗱 𝗯𝗼𝘁𝗵 𝗡𝘃𝗶𝗱𝗶𝗮 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗜𝗻𝘁𝗲𝗿𝗻𝗲𝘁 𝗶𝗻 𝟭𝟵𝟵𝟭.
Clark told the CEO of Silicon Graphics: "Everything we sell for $50,000 will go on a chip that costs $300, and every computer will be networked together." He was right on both counts. One prediction became Nvidia. The other became the Internet. The professional manager the VCs had installed refused to pursue either idea. SGI is gone. Nvidia is worth trillions.
The founder saw the future. The manager protected the present. We have seen this story in every decade, in every industry. It should be mandatory reading for every board member.
𝟳. 𝗘𝗹𝗼𝗻 𝗠𝘂𝘀𝗸 𝗱𝗼𝗲𝘀 𝟭𝟮𝟬 𝗱𝗲𝘀𝗶𝗴𝗻 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 𝗶𝗻 𝗮 𝗱𝗮𝘆.
Five minutes per engineer, 12 per hour, 10 hours straight. He maps each company as a production line, finds the single bottleneck slowing things down that week, and fixes it himself with the engineer closest to the problem. Musk personally fixes Tesla's bottleneck 52 times a year. Legacy automakers are doing nothing even close.
We have been studying company builders for years. This is the clearest description of how one person runs six companies simultaneously that we have ever come across.
𝟴. 𝗔𝘁 𝗜𝗕𝗠, 𝟭𝟮 𝗹𝗮𝘆𝗲𝗿𝘀 𝗼𝗳 𝗹𝗶𝗲𝘀 𝘀𝗲𝗽𝗮𝗿𝗮𝘁𝗲𝗱 𝘁𝗵𝗲 𝗖𝗘𝗢 𝗳𝗿𝗼𝗺 𝗿𝗲𝗮𝗹𝗶𝘁𝘆.
As a young intern, Andreessen counted 12 levels of management between himself and the CEO. Each layer spun the truth slightly to look good. After the truth passed through 12 filters, the CEO had absolutely no idea what was happening in his own company. They had a term for it: "the big gray cloud," the wall of men in gray suits who surrounded the CEO and prevented him from ever talking to anyone doing actual work.
Musk's method is the exact opposite. He only talks to engineers.
𝟵. 𝗧𝗵𝗲 𝗜𝗻𝘁𝗲𝗿𝗻𝗲𝘁 𝘄𝗮𝘀 𝗶𝗹𝗹𝗲𝗴𝗮𝗹 𝘁𝗼 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗶𝗮𝗹𝗶𝘇𝗲.
The NSF had an Acceptable Use Policy that strictly prohibited commercial activities on the Internet. Andreessen was personally fielding tech support emails for the entire Internet because he built the Mosaic browser as a college project. Some users emailed asking how to keep the cup holder from retracting into their PC. That was the CD-ROM tray.
When 400 commercial licensing requests piled up in his inbox, he took them to Jim Clark. That became Netscape.
𝟭𝟬. 𝗧𝗵𝗼𝗺𝗮𝘀 𝗘𝗱𝗶𝘀𝗼𝗻 𝘁𝗵𝗼𝘂𝗴𝗵𝘁 𝘁𝗵𝗲 𝗽𝗵𝗼𝗻𝗼𝗴𝗿𝗮𝗽𝗵 𝘄𝗮𝘀 𝗳𝗼𝗿 𝗹𝗶𝘀𝘁𝗲𝗻𝗶𝗻𝗴 𝘁𝗼 𝘀𝗲𝗿𝗺𝗼𝗻𝘀.
Edison was a proper, religiously devout gentleman. He imagined families gathering around the record player each evening to hear great preachers. Instead, the phonograph immediately became a music machine for ragtime and jazz. Edison was horrified.
If the inventor of the phonograph couldn't predict what it would be used for, the idea that any AI entrepreneur can forecast economic implications is absurd. The people who invent the technology are often the least qualified to understand the long-term consequences.
𝟭𝟭. 𝗘𝘃𝗲𝗿𝘆 𝗻𝗲𝘄 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗴𝗲𝘁𝘀 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗺𝗼𝗿𝗮𝗹 𝗽𝗮𝗻𝗶𝗰.
In the 1870s, the bicycle created "bicycle face," a fake medical condition invented to scare young women off bikes so they wouldn't ride to the next town and meet new people. Jazz was going to corrupt youth in the 1920s. Rock and roll in the 1950s. Hip hop in the 1980s. Jimmy Iovine was compared to mustard gas for funding hip-hop records.
The structure of the panic never changes: this thing will ruin society, ruin morality, and especially ruin the children. The technology always wins.
𝟭𝟮. 𝗔𝗻𝗱𝗿𝗲𝗲𝘀𝘀𝗲𝗻'𝘀 𝘁𝘄𝗼 𝗺𝗲𝗻𝘁𝗼𝗿𝘀 𝘄𝗲𝗿𝗲 𝗽𝗼𝗹𝗮𝗿 𝗼𝗽𝗽𝗼𝘀𝗶𝘁𝗲𝘀, 𝗮𝗻𝗱 𝗵𝗲 𝗻𝗲𝗲𝗱𝗲𝗱 𝗯𝗼𝘁𝗵.
Jim Clark (the visionary) gave him the will to bludgeon the world into adopting his ideas. Jim Barksdale (the operator) taught him to thread new ideas into a running business without burning it down. The collision of those two forces at Netscape is the template Andreessen and Ben Horowitz have replicated for 30 years.
The hardest thing in company building is knowing when to push the accelerator and when to hold the wheel steady. Having one person for each instinct, and trusting each other completely, is a cheat code very few partnerships ever figure out.
Full Podcast is worth listening to. Link in Thread.
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👀
Marc Andreessen just dropped ~105 mins on Lenny's Podcast covering AI, jobs, careers, and why everyone is panicking about the wrong thing.
Just the clearest macro framework I've heard on where AI actually lands.
My notes:
𝟭. 𝗔𝗜 𝗶𝘀 𝗮𝗿𝗿𝗶𝘃𝗶𝗻𝗴 𝗮𝘁 𝘁𝗵𝗲 𝗲𝘅𝗮𝗰𝘁 𝗺𝗼𝗺𝗲𝗻𝘁 𝗵𝘂𝗺𝗮𝗻𝗶𝘁𝘆 𝗻𝗲𝗲𝗱𝘀 𝗶𝘁.
US productivity growth has been running at half the rate of the 1940-1970 era and a third the rate of 1870-1940. The global population is declining below replacement in dozens of countries, including China. Without AI, we would be panicking about economies shrinking from depopulation, not job loss.
The timing is almost miraculous. This is what Andreessen means when he says the real boom has not started yet. We have been in a 50-year productivity drought, and most people do not even realize it.
𝟮. 𝗔𝗜 𝗶𝘀 𝘁𝗵𝗲 𝗽𝗵𝗶𝗹𝗼𝘀𝗼𝗽𝗵𝗲𝗿'𝘀 𝘀𝘁𝗼𝗻𝗲.
Isaac Newton spent decades trying to transmute lead into gold and never succeeded. AI does something more powerful: it converts sand (silicon) into thought. The most common material in the world is the rarest output.
This one metaphor reframes the entire AI conversation. You do not have a job loss problem. You have a philosopher's stone sitting on your desk that you are not using enough.
𝟯. 𝗔𝗜 𝗺𝗮𝗸𝗲𝘀 𝗴𝗼𝗼𝗱 𝗽𝗲𝗼𝗽𝗹𝗲 𝘃𝗲𝗿𝘆 𝗴𝗼𝗼𝗱, 𝗮𝗻𝗱 𝘃𝗲𝗿𝘆 𝗴𝗼𝗼𝗱 𝗽𝗲𝗼𝗽𝗹𝗲 𝘀𝗽𝗲𝗰𝘁𝗮𝗰𝘂𝗹𝗮𝗿𝗹𝘆 𝗴𝗿𝗲𝗮𝘁.
The best coders right now are not reporting 2x productivity. They are reporting 10x. The gap between "pretty good with AI" and "elite with AI" is widening, not narrowing.
This is the most important signal for career planning right now. If you are just using AI to do the same job slightly faster, you are leaving the real leverage on the table.
𝟰. 𝗧𝗵𝗲𝗿𝗲'𝘀 𝗮 𝗠𝗲𝘅𝗶𝗰𝗮𝗻 𝘀𝘁𝗮𝗻𝗱𝗼𝗳𝗳 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝗣𝗠𝘀, 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀, 𝗮𝗻𝗱 𝗱𝗲𝘀𝗶𝗴𝗻𝗲𝗿𝘀.
Every engineer now thinks they can be a PM and designer. Every PM thinks they can code and design. Every designer knows they can do both. And they are all correct, because AI enables each role to absorb the tasks of the other two.
I have seen this firsthand in the investing world. The analyst who can build models and write narratives is 5x more valuable than someone who can do only one. The same convergence is happening in the product.
𝟱. 𝗙𝗼𝗿𝗴𝗲𝘁 𝗧-𝘀𝗵𝗮𝗽𝗲𝗱. 𝗕𝘂𝗶𝗹𝗱 𝗮𝗻 𝗘-𝘀𝗵𝗮𝗽𝗲𝗱 𝗰𝗮𝗿𝗲𝗲𝗿.
Scott Adams could not have created Dilbert by being the world's best cartoonist or the world's best business mind. He needed both. The additive effect of two skills is more than double. Three skills are more than triple. Larry Summers puts it differently: don't be fungible.
The person who can code, design, and ship a product is no longer a unicorn. They are the new baseline for "extremely valuable." If you are only one of those three things, you are increasingly replaceable.
𝟲. 𝗝𝗼𝗯𝘀 𝗮𝗿𝗲 𝗯𝘂𝗻𝗱𝗹𝗲𝘀 𝗼𝗳 𝘁𝗮𝘀𝗸𝘀. 𝗧𝗮𝘀𝗸𝘀 𝗰𝗵𝗮𝗻𝗴𝗲. 𝗝𝗼𝗯𝘀 𝗽𝗲𝗿𝘀𝗶𝘀𝘁.
Executives never typed their own emails in the 1970s. Secretaries printed incoming emails and hand-delivered them. Both roles survived the transition, just with different task sets. The same will happen with AI and coding, PM work, and design.
Everyone obsessing over "will my job disappear" is asking the wrong question. The right question is: which tasks in my job are about to rotate, and am I ready to pick up the new ones?
𝟳. 𝗔𝗜 𝗰𝗼𝗱𝗶𝗻𝗴 𝗶𝘀 𝗷𝘂𝘀𝘁 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝗮𝗯𝘀𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗹𝗮𝘆𝗲𝗿.
We went from human calculators to machine code to assembly to C to scripting languages. Each layer was dismissed by the previous generation. Each time, the new layer won, and total coding employment grew. AI coding is the same pattern, not a rupture.
The Perl programmers of 2005, laughing at JavaScript, are the C programmers of 1995, laughing at scripting. History rhymes, and it always rewards the people who adopt the next abstraction first.
𝟴. 𝗔𝗜 𝘁𝘂𝘁𝗼𝗿𝗶𝗻𝗴 𝗱𝗲𝗺𝗼𝗰𝗿𝗮𝘁𝗶𝘇𝗲𝘀 𝗲𝗹𝗶𝘁𝗲 𝗲𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻.
One-on-one tutoring is the only method proven to move a student from the 50th to the 99th percentile (Bloom's two sigma effect). It used to require being born into royalty. Alexander the Great was tutored by Aristotle. Now, any kid with a phone can access the same quality of personalized instruction.
This is the most under-discussed consequence of AI. Every parent reading this should be supplementing their kid's education with structured AI tutoring right now. Not next year. Now.
𝟵. 𝗣𝗲𝘁𝗲𝗿 𝗧𝗵𝗶𝗲𝗹 𝘄𝗮𝘀 𝗺𝗼𝗿𝗲 𝗿𝗶𝗴𝗵𝘁 𝘁𝗵𝗮𝗻 𝗔𝗻𝗱𝗿𝗲𝗲𝘀𝘀𝗲𝗻 𝗼𝗿𝗶𝗴𝗶𝗻𝗮𝗹𝗹𝘆 𝗮𝗱𝗺𝗶𝘁𝘁𝗲𝗱.
Progress in bits masked stagnation in atoms. The built world is barely different from 50 years ago. Same bridges from the 1930s, same dams from the 1910s. Cartels, monopolies, unions, and regulations prevent the rate of change that people had 100 years ago.
This is also why AI will not transform everything overnight. Institutional sclerosis is real. Healthcare alone could take a generation. If you are building in atoms, budget for a war of attrition, not a blitzkrieg.
𝟭𝟬. 𝗠𝗼𝗮𝘁𝘀 𝗶𝗻 𝗔𝗜 𝗮𝗿𝗲 𝗴𝗲𝗻𝘂𝗶𝗻𝗲𝗹𝘆 𝘂𝗻𝗸𝗻𝗼𝘄𝗻.
Within a year of ChatGPT's launch, five American companies, five Chinese companies, and open-source all had roughly equivalent models. DeepSeek emerged from a hedge fund in China and basically replicated the American labs' work. The smartest AI insiders privately admit there aren't many real secrets among the big labs.
This is the most honest take I have heard from a top-tier VC. No one knows if the value accrues to models, apps, or infrastructure. Anyone who tells you otherwise is selling you certainty they do not have.
𝟭𝟭. 𝗔𝗜 𝗜𝗤 𝘄𝗶𝗹𝗹 𝗯𝗹𝗼𝘄 𝗽𝗮𝘀𝘁 𝗵𝘂𝗺𝗮𝗻 𝗹𝗶𝗺𝗶𝘁𝘀.
Human IQ caps around 160 because of biology. Current AI models test around 130-140. There is no theoretical ceiling stopping AI from reaching 200, 250, or 300. The concept of AGI as a "human equivalent" will be a footnote because AI will race past that threshold.
This is the frame that makes the "will AI take my job" debate feel small. We are not building a replacement for human thought. We are building something that will be better than the best human thought has ever been.
𝟭𝟮. 𝗧𝗵𝗲 𝗯𝗲𝘀𝘁 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀 𝗮𝗿𝗲 𝗿𝗲𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝘄𝗵𝗮𝘁 𝗮 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝗲𝘃𝗲𝗻 𝗶𝘀.
Layer one: AI redefines products. Layer two: AI redefines jobs within companies. Layer three, which has not dropped yet: AI redefines the very concept of having a company. The holy grail is the one-person, billion-dollar outcome, and the best founders are chasing it.
Satoshi did it with Bitcoin. Instagram and WhatsApp came close with tiny teams. The question is no longer if this is possible with software. The question is how many of these we will see in the next five years.
AI is the philosopher's stone. The question is whether you pick it up.
The full podcast is worth your time. Link in replies.






























