u/cen6wkf

Been thinking about this one. Hian Goh — sold a TV network for $65M, now runs a venture fund managing close to $1B — describes a conversation with a top Singapore lawyer who basically admitted his own firm could function with half the headcount, but he's scared to lower prices because it tips his hand.

The sharper point: it's not outside competitors who kill the old model. It's the firm's own junior lawyers — the ones with nothing left to lose — who spin up the AI-powered practice that eats the old one alive.

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#AIDisruption #LegalIndustry #WealthBuilding

Dell's own support org was buried under so much warranty data, call logs, and ticket history that, in his words, "no human could ever interpret all this." So they built an internal tool that reads all of it and hands the agent the single best next step — not a summary, the actual fix, in the fewest steps.

The part worth sitting with if you run something smaller: this isn't really an AI story, it's a retrieval story. Most of us treat a growing support backlog as a "we need to hire" problem. Dell's team treated it as a "we can't find the answer fast enough" problem — and fixed that first.

Curious how this scales down to businesses running on a fraction of Dell's budget? Link's in my bio. ⚓

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#AIforBusiness #CustomerSupport #SmallBusiness

A recent grad — valedictorian, honors grad, two internships — applied to 10 jobs a day for 11 months. Got nothing but silence. An AI filter was screening her resume before a human ever looked at it.

Clara Shih ran hiring at Meta and Salesforce. She's now tracking this at scale through the New Work Foundation, and the data isn't reassuring: this isn't a temporary hiring freeze, it's a structural shift in what "entry-level" even means — and it doesn't check whose name is on the resume first.

If you want the fuller breakdown on building around this instead of waiting on a broken pipeline — link's in my profile. 🔗

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#AIJobs #EntryLevel #NewWorkFoundation

Most creator-economy advice is about landing bigger brand deals. Jun Yuh's actual practice runs the opposite direction — he treats brand-deal income as disposable, almost incidental, and redirects nearly all of it into equity in businesses he controls outright.

The framing shift is the interesting part: he says he doesn't even count that money as "real income" anymore. It's seed capital for something compounding, not spending money.

For anyone stuck thinking "more income" is the goal — this is a decent argument for "more ownership" being the actual variable that matters.

Full context and the mindset breakdown behind this: link's in my profile if you want to go deeper. 🔗

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#WealthBuilding #Equity #CreatorEconomy

Heard this on Zuby's podcast and it's stuck with me. Joe Lonsdale (Palantir co-founder) describes a federal department where union rules made it legally impossible to test employees for performance — only for a "reorg." So his friend ran a basic, first-year-developer-level test on all 3,000+ of them anyway. 68 passed.

They're all still employed. He wasn't even allowed to fire the ones who were, in his words, doing "really crazy stuff" — people higher up were protecting them.

What gets me isn't the incompetence — it's that even with hard proof in hand, there was still no lever to pull. Proof and power turned out to be two completely separate things.

Curious what people think: is this a uniquely government problem, or does every sufficiently large organization eventually protect its own dead weight the same way?

Link in my bio if you want to go deeper on what building outcome-based leverage actually looks like when you can't rely on the system to reward it.

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#Accountability #Bureaucracy #Meritocracy

Sarah Guo (Conviction Partners) makes a structural argument here that's more useful than the usual reassurance: any large organization only has one A-team, and the rest of what they build is priority-constrained, not capability-constrained. So "you're not their priority" isn't a countdown — it's the actual room founders have to build in.

Worth internalizing if you're building anything AI-adjacent and keep hedging your roadmap against lab risk instead of your actual customers.

Link in bio if you want the fuller breakdown. 🔗

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#StartupStrategy #AIFounders #VentureCapital

This is one of the cleaner examples of a founder losing leverage on paper before he even realizes it's happening. ESPN's deal vested Portnoy's equity instantly the moment he was excluded — structured to look generous, functionally an exit clause.

 

What's interesting is the counter: he didn't fight the exclusion, he reframed the leverage entirely — instead of arguing legal standing he didn't have, he named the reputational risk ESPN was exposed to. That's the actual mechanism worth studying if you run anything you don't want diluted out from under you. ⚓

 

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#Ownership #Leverage #FounderStory

Joe Lonsdale tells this story about the early days of Palantir — and it's less about the company and more about who gets to decide what counts as "qualified."

He and Alex Karp went looking for funding post-9/11, trying to build something the government badly needed. Every major VC on Sand Hill Road turned them down. One investor at a well-known firm laughed at Karp on the phone — not over the business model, but because his doctorate "wasn't even relevant."

Benchmark passed. Sequoia passed. The list goes on.

What's interesting is what Peter Thiel told Lonsdale afterward: the rejection was good for them. It gave them a chip on the shoulder that outlasted every "no."

Worth sitting with if you've ever had your background, degree, or path called irrelevant by someone whose job is to gatekeep, not build. Their rejection is a data point about their imagination, not your ceiling.

Full mechanism (how they actually converted rejection into leverage) is at the link in my bio.

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#FounderStory #VentureCapital #CredentialTrap

Jack Zhang co-founded Airwallex and built it to $11 billion.

In a recent Kleiner Perkins interview, he made a point that's uncomfortable if you've been inside an institution for any length of time:

He hired people based on where they'd worked before — Citigroup, major banks, big tech — and watched every one of those hires create problems that took years to undo.

His exact words: "First-principle thinking is a lot more important than experience."

The mechanism here is worth sitting with.

The institutional voice — the one that says "you have 10 years at Citi, you probably know better than I do" — is not giving you a logic argument. It's deploying a credential as an argument-stopper.

And it works, because we've been trained since the start of our careers to treat pedigree as a proxy for correctness.

Jack trusted that proxy. Then had to rewrite everything it produced.

The uncomfortable extension: if you've been inside an institution long enough to have absorbed its logic, your own instincts may be running the same filter on your own ideas.

"I don't have enough experience to build this yet."

"Someone with more background would know better."

That's not humility. That's the credential trap running inward.

The link in my bio goes deeper on this framework if you want the full picture. ⚓

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#Entrepreneurship #StartupLessons #FounderMindset

Everyone frames this as a Hollywood success story. It's not. It's a category-repositioning case study.

Here's what actually happened:

Pratt was pre-rejected by both the director (James Gunn) and himself — simultaneously. Neither party pushed the door. The mutual conclusion was: he doesn't fit.

Then one proof point changed everything. 🔥

Zero Dark Thirty came out. Nobody laughed when he played a Navy SEAL. The category flipped — not because Pratt changed, but because the evidence the market had access to changed.

The audition technique he describes is a second mechanism entirely:

Walk into the room already being the thing. Not performing toward it. Not asking permission to be considered. Embodying the result before the result is granted.

He walked into James Gunn's room and refused the deference script. Asked no questions. Became the character in front of the director before the audition officially started.

Gunn gave him the role.

The transfer to non-Hollywood contexts is exact:

The market doesn't evaluate who you are. It evaluates the most recent legible proof point you've submitted.

Most professionals are filing the wrong evidence in rooms that stopped listening to that frequency years ago.

If this framing resonates, check the link in my bio — there's a resource that maps this into a practical framework for people building outside the institution.

No pitch, just the mechanism.

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#CareerStrategy #WealthBuilding #SystemsThinking

There's a specific kind of career risk that doesn't show up in a layoff announcement.

No meeting. No HR conversation. Just a slow recalibration of what your employer expects from you — and a gradual awareness that the baseline function you occupied no longer justifies the full cost of keeping you.

Gary Vee, in a recent interview, called it "smoked out." 🔥

His exact framing: 100 people can now do the work of 400. If you're competing against a firm that still has 400 people — and you cut to 200 — the output war isn't decided by who's more efficient. It's decided by whether the 400 also get the same tools.

And then he landed on something specific.

He said: if you're a project manager whose core function is taking notes — that person has already been kind of smoked out.

Not fired. Not made redundant in any formal sense. Just quietly asked to do more, because the thing they were valued for no longer requires them to do it.

This is the AI job risk nobody models accurately — not the dramatic restructuring, but the ambient erosion of the function that justified your salary.

If your professional identity is fully contained inside what a well-prompted AI can replicate, the smoke is already in the building.

The people who are navigating this transition well are not the ones running faster inside the same room. They're the ones who figured out what they own — and started building toward that, before the room got too smoky to think clearly.

If you want a framework for thinking through your position — not a hustle pitch, just the architecture — the link in my bio has something worth reading. ⚓

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#CareerStrategy #AIJobs #FinancialIndependence

Kevin O'Leary is building what's projected to be the world's largest data center. Tucker Carlson asked him, directly, what jobs will replace lawyers, financial planners, and the professional class that AI is projected to eliminate.

O'Leary's answer: space exploration. Defense robotics. New technologies we don't know yet.

Tucker's follow-up: I asked about jobs in America and you went immediately to defending Taiwan.

O'Leary reached for his water bottle. 🧱

This isn't a gotcha moment. It's a structural signal.

The person building the machine that eliminates the professional services category cannot name what replaces it. Not because he's hiding it — because the answer doesn't exist yet at a systemic level.

Which means it won't come from the system. It has to come from individuals who see the window before it fully closes and build something that isn't dependent on the category being stable.

The professional class — analysts, lawyers, knowledge workers in regional MNCs — has been running on the assumption that the automation threat is downstream, hitting physical and low-skill labor first. This clip is the clearest on-record moment of that assumption being directly challenged, by the builder, with no clean rebuttal available.

If you're in that category and you've been watching and waiting: the link in my bio has the framework that moves you from watching to building. 📡

The clip is from Tucker Carlson's YouTube channel — full timestamp 1:20:41–1:23:45 and 1:38:19–1:38:37.

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#financialindependence #FIRE #AIJobs

There's a version of the AI-and-engineering conversation that's just doomscrolling with better vocabulary.

This isn't that.

Rauch (CEO of Vercel — the infrastructure these conversations run on) made a point in a recent Naval podcast episode that I haven't seen pulled out the way it deserves to be. The short version:

Junior engineering — the task category — got taken over by agents. Junior engineers got promoted to senior engineers.

The role bifurcated. It didn't disappear.

And the new version of the senior engineer role isn't the person who writes more code faster — it's the person who builds the evaluator system: the test harness, the simulation suite, the type checkers, the consequence map. The infrastructure that gives you confidence to sign off on code you didn't write line by line, because you built the architecture that makes that confidence legitimate.

His exact framing: "Humans are becoming verifiers."

Not a threat. An observation. Delivered with the calm of someone who has already integrated it into how they run a company at scale.

The engineers who move fast on this — who deliberately build the judgment layer rather than competing with agents on output speed — are the ones who own the next decade's architecture decisions. The ones who wait are training the thing that will replace them. 🪝

If you want the actual framework for making this transition, the link in my profile points to a resource worth your time.

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#cscareerquestions #MachineLearning #financialindependence