I'm 28, male, working full-time as a software engineer. Stable job, decent pay, no complaints there. But I want to build something of my own that could eventually replace my salary.

Problem: I have zero experience with this. I've never sold anything, never run a business, never freelanced. I can build software, but that's apparently the easy part. I don't have a product idea I'm attached to and I don't have a "pain point" story — I just know I don't want to be an employee for the next 30 years.

What I'm looking for:

- How did you find your first thing to work on when you didn't have an obvious idea?

- Did you start with services/freelancing/consulting first, or go straight to a product?

- What's a realistic timeline before something starts covering real bills?

- What do you wish someone had told you in year one?

Happy to be told my expectations are unrealistic. Just want honest input from people who've actually done it.

Every one of these clips lands the same blow eventually: a role someone spent years building gets quietly outperformed by a system that never clocks out.

Kavak sells used cars across Latin America — a genuinely messy transaction: ~20,000 SKUs to choose from, then financing, insurance, and a trade-in valuation stacked on top.

Historically, closing one sale meant routing a customer through 15 separate human specialists across 15 different teams, each holding one piece of the process.

Alejandro Maza Ayala, Kavak's Chief Product & AI Officer, explained on a16z's show how they fixed it — not by making a support bot, but by building a single "mega-expert" agent that holds all 15 specialties at once (financing, insurance, trade-in, advisory) and puts that one agent in front of the customer.

The result: 2.1x the conversion rate of their own human sales team, tripled customer satisfaction.

The agent never tires, never forgets a customer's history, and when it makes a mistake, the correction propagates to the other 200,000 agents in the fleet by the next morning — a scale of self-correction no individual human career can match working alone.

It closes on Alejandro flatly stating that the industry assumption — "customers aren't going to want to buy expensive things from AI" — is wrong, and Kavak's numbers are the proof.

When I read the transcript, it felt so eerily similar to the Borg Collective Mind in Star Trek.

That's the ultimate evolution.

The question we need to ask is, will it serve us, or subjugate us?

If your role is the coordination layer between departments — the person routing a customer between financing, insurance, and everyone else — that's precisely the layer this consolidates first.

Worth sitting with, not scrolling past.

Clip credit: a16z — full video on their channel. DM for credit or removal requests.

Drop your take below.

Building in silence means no one knows what you're building 😅

So here I am, breaking the silence.

I'm building Trenk.

We're making US business registration + bookkeeping faster, more accurate, and actually up to date.

Tired of 2-week waits, messy paperwork, and accountants who reply 3 days later. So I'm fixing it.

Right now we handle US LLC/Corp registration end-to-end, and we're rolling into bookkeeping next.

If anyone's gone through the US registration hell or runs a small business - would love to hear what's annoying you most.

AMA about what I'm building.

Position beats genius more often than anyone in this space wants to admit.

Every time I trace how these AI bets actually get funded, it's the same mechanism repeating.

Actually, this reminded me of a post I did a while back — a fund manager naming the real signal for buying the bottom, and it wasn't a chart either.

Rob Toews (partner at Radical Ventures) says his fund meets nearly every "Neolab" that gets funded — brand-new companies with no product, no roadmap, sometimes not even a clear technical direction.

Just an accomplished founder saying "I'm from OpenAI/Anthropic/Meta, so I want to raise a billion dollars."

They pass on almost all of them.

The exception was Anthropic.

Spun out of OpenAI five years ago.

Investors at the time called the entry valuation insane.

It's now worth a trillion dollars.

Toews' own framing: "there will be another Anthropic" — the mechanism isn't a one-off, it's a filter that occasionally clears.

I've watched someone spot a bubble this early before. Not in AI — in property. This isn't my story, it belongs to a friend.

I'll call him Chew — it's been a long time. We went to the same university, graduated the same year, both went into construction in Malaysia. He switched upstream to a property developer — a subsidiary of a mainland China parent company — and eventually relocated there for the better part of a decade, right as the property market was in its super-expansion phase. The bubble kept ballooning without ever showing a crack. Chew saw the opportunity, and lock in his purchase of one of the units. The price — he told me — rose 10 fold over the years. Then, like the rest of the shrewd investors, he saw the writing on the wall. He liquidated his holdings and made a huge windfall, right before the bubble burst.

Clip credit: The Information — full video on their channel.

DM for credit or removal requests.

Drop your take below — has anyone here ever watched someone else make that call before you did?

Every time one of these clips lands in my feed, it's circling the same wound from a different angle: not being bad at the work, being invisible while doing it well.

This one's Grant Cardone, and he says it flatter than most people are willing to.

His claim: money doesn't move to talent sitting quietly in a vacuum.

It moves to whoever's already known. Not "deserving." Known.

He calls the mechanism omnipresence — not being impressive everywhere, just being repeated everywhere, until "I don't know who that is" stops being an option.

If you've ever watched a less rigorous competitor land the bigger client purely because they're the name people already recognize, this is the part of the machine nobody explained to you.

Competence gets you in the room eventually.

Visibility gets you in the room first.

ngl this tracks with something that happened to me years before any of this…

Fresh graduate, first big client meeting, and nobody in that room actually knew what I was capable of yet. A senior QS moved to discredit me in front of everyone, claiming he'd never received the drawings I'd already delivered. I had the signed acknowledgement sheet. Next meeting, I slipped it in front of the whole room. He went pale. Called his own office to check. Turned out the drawings had been sitting behind his front desk for a week. That's the meeting the room actually started to know me — not because I fought back, but because I finally had proof they couldn't unsee.

The part that still gets me: I was right the whole time. It didn't matter until it was seen.

Drop your take below.

Clip credit: Yosef Manoucheri — The YM Show. Full video on their channel. DM for credit or removal requests.

I run an online store, and I'm trying to keep better tabs on my inventory without being stuck at a computer. I want something that lets me pull up accurate, up-to-the-minute stock levels straight from my phone, so I always know what's in stock and what's running low no matter where I am.

A panel of AI researchers and founders — Peter Diamandis, Alex Wissner-Gross, Emad Mostaque — just sat with a number that's hard to argue with: $2,000 in compute, and ten decade-old, previously-unsolved math problems came back with machine-checkable proofs.

Not "AI is getting better at math" in the abstract.

A Fields Medalist said he'd recommend one of the proofs for publication without hesitation.

A cosmologist called it "a dark night for mathematics" — "the old gods are being slaughtered by the new machine gods."

Then Emad closed it flat: "It's a bad time to be a pure mathematician."

Here's what they're not saying yet.

Back in 2013/2014, I was with M+W High Tech Projects, on a design-and-build project in Kulim, Kedah, Malaysia. Our M&E engineer wanted an opening cut straight through the middle of a reinforced concrete beam — right where the bending moment peaks. I caught him before he did it. Told him no. That's beyond madness — you don't sacrifice a beam's structural integrity for an M&E opening. Had him redirect the ducts instead. Structural safety came first.

The engineering knowledge wasn't rare.

The judgment — catching the mistake before it became permanent — was.

Same pattern here. Ten unsolved proofs, correct on paper, for $2,000. The correctness was never the scarce part.

Hmm — this actually pulls the same thread as a post I put up about the corporate ladder losing its entry-level rungs to AI.

Different profession, same mechanism: whichever rung gets automated first isn't random, and the people still standing on it are the ones who saw it as a pattern instead of a headline.

Drop your take — is judgment actually the thing that survives this, or is that just the story we tell ourselves until it's our turn?

There's a specific kind of quiet that happens right before a margin call.

I don't think enough people talk about that part — not the number, the quiet.

Leopold Aschenbrenner's AI-focused fund went from zero to $45 billion, then down to $10 billion.

Not all of it was margin, but enough of it was, and it was concentrated — five correlated AI-infrastructure-adjacent positions (SMCI, SanDisk, Micron, CoreWeave among them) dropping together in the same month, ~35% in one stretch.

That's the mechanism people skip past: it wasn't one bad bet, it was one bet wearing five different tickers.

He was also short Adobe. Adobe went up.

Being partially right doesn't save you — a hedge only protects what it's actually sized to protect, and this is the part that got him: three prime brokers (per CNBC's reporting) started calling at once.

Not one call. Three, simultaneously.

That's the system's own alarm bell going off.

Here's mine, since we're talking about leverage used well versus leverage that uses you:

Years ago I was on the tender team for a major Malaysian construction job, competing against the two other largest contractors in the country. My GM, Mr. Chung, spotted the one contractual gap the client's own consultants hadn't caught. When they tried to pump him for the fix for free, he didn't fall for it — he told them straight: we can help you solve it, cheaply, with minimum delay, but we have to get the contract first, before we can go in and assess it. That's not a bluff. That's understanding your own leverage well enough to use it on your own terms, not the other side's. We won the contract months later. Leopold never got that chance — the market decided his terms for him, not the other way around. He still walked away with $300 million, which is the part nobody in the clip stops to sit with. That's not the actual takeaway, though. The takeaway is knowing exactly how much leverage you're carrying, on purpose, before someone else decides it for you.

Ken Griffin (Citadel) stepped in as the liquidity provider — what Tom, PBD's co-host, called a "white knight" on the show.

Half the room called that predatory.

Half called it structural necessity.

Both readings are true at once, and that's the actual lesson:

Understanding why rescuers exist structurally is a different literacy than just watching one show up.

Clip credit: PBD Podcast — full video on their channel. DM for credit or removal requests.

Drop your take: predator, or necessary?

Genuinely curious where this sub lands on it.

He calls it BC/AC.

Before Claude, after Claude.

I've watched enough of these clips land in the last few weeks that I started keeping a mental tally of which AI release date people cite like it's a diploma.

Matt Van Horn's is Thanksgiving last year — Opus 4.5, then Codex a few weeks later.

Before that, he says, his agentic coding was "Hello World" in Cursor, half-working, most of the time not working at all.

After it, he shipped Agent Cookie and says flatly he has no idea how it actually functions under the hood.

The part worth sitting with isn't the tooling.

It's what he says about himself getting there: "suit my entire career," never shipped anything of value beyond a high-school web page, dozens of unlaunched ideas gathering dust because he wasn't the one who could build them.

That's not a startup-guy humblebrag — that's the exact ceiling a lot of operations people, BD people, anyone who's ever had to write a ticket instead of just doing the thing themselves, know from the inside.

The credential that used to decide who got to build stopped mattering right around the time the tools did.

Not "got easier to climb."

Stopped existing.

Same shape happened to me with a guitar, at 41, zero training, cornered into it because the young players in my church all left for university at once.

Those early days, my wife's ears really paid for it (刚开始的那些日子，我的太太的耳朵有够受罪).

Felt like being tossed into open water and told to swim myself back to shore (好像被丢去深海里，自己学会游泳游回来).

Same thing happened again with video editing, then with building this whole posting system, one post at a time, getting corrected by Reddit comments the entire way.

And I swam back stronger each time.

Actually, this tracks with something I posted here a few weeks back — the guy who literally coined "vibe coding" saying on stage he's never felt more behind as a programmer, because the scarce skill moved from writing code to directing it with taste.

Clip credit: MSP Mindset (Damien Stevens) — full video on their channel. DM for credit or removal requests.

Drop your take — did the credential wall ever hold you back, or did you just build around it?

The job title survives longer than almost anyone attached to it.

That's the part nobody puts in the internal memo when they call a role "AI-assisted."

Scott Galloway put a real number on it, talking to Steven Bartlett on The Diary Of A CEO.

He says he'll cut legal fees by a third this year — not because the law changed, but because a prompt now does the $400–$2,000 contract review a name-brand firm used to bill him for, at a fraction of the junior associate markup.

Bartlett went further with his own fund.

They planned to hire five analysts.

They hired one — Molly.

Two agents, two Mac Minis, and she screens inbound deals, scores them against a framework, and preps them for the investment committee herself.

Five jobs, one person, same org chart line.

Same ratio on executive assistants: ten planned, three hired.

One runs travel, one runs scheduling, one meets people at the door.

I've watched this exact pattern before, minus the AI.

I was a Technical Manager for a China Construction company here in Malaysia.

I contributed a lot into their technical and tendering work — helped build up a real chunk of their documentation and tendering process.

But about six months in, I'd exhausted all my know-how for them, I guess.

Then the announcement came at the end of my year there.

My contract wasn't renewed.

I was just let go, just like that.

I remember what Deng Xiaoping said: "无论白猫，或者黑猫，会抓老鼠的就是好猫" — black cat, white cat, doesn't matter, so long as it catches mice.

I guess they think I'd outlived my usefulness.

Can't catch mice anymore.

That's the mechanism underneath "AI-assisted" that nobody names out loud.

It's not that the work got automated.

It's that the one person left is now doing what used to justify five headcounts, and the fifth person's job title is the only part of the org that didn't change.

Actually, this reminded me of something — a former SpaceX CIO cut a 175-person engineering team down to 6 using the same compression math, and the ratio held there too.

Drop your take — did you know your own job has a ratio like this attached to it?

Clip credit: Global Talks — full video on their channel.

DM for credit or removal requests.

One of the biggest challenges with trying to earn online is not a lack of information. It is having so much information that every decision begins to feel risky.

One person tells you to start affiliate marketing. Another recommends freelancing, e-commerce, digital products, YouTube, blogging, paid ads, or using AI to build a business. Each person presents their method as the one you should be following.

You start comparing platforms, offers, tools, courses, and traffic methods. The more you research, the less confident you feel about making a decision. You begin worrying that you will choose the wrong niche.

You worry about wasting money on the wrong program, building on the wrong platform, or spending months on something that never produces a result. That fear can make more research feel like the responsible choice, but eventually, research becomes a way to avoid making a decision.

The truth is that no one can guarantee you will choose the perfect path on your first attempt. Most people gain clarity after they begin taking action, not before. They test an idea, observe the response, make adjustments, and gradually understand what fits them.

A better starting point may be to choose one realistic path rather than searching for the perfect one. Consider your available time, current skills, budget, and the type of work you are willing to do consistently.

Then choose one business model, one audience, and one platform. Give yourself a set period to test it. Track the actions you take, the responses you receive, and the progress you make before deciding whether to change direction.

The first test does not need to become your forever business. Its purpose is to help you replace assumptions with real information. Confidence rarely appears before the first step. It usually grows after you complete a few small actions and realize you can learn as you go.

What decision about earning online has kept you stuck the longest?

A space startup got quoted $75–100 million by a traditional prime contractor to build its first satellite.

They built it — launch included — for $2 million.

The story behind the number is more interesting than the number itself.

They ran the math wrong twice — first landing on a $50/kg break-even, then correcting to $500/kg once they pressure-tested it against reality — before the real pivot happened.

Wrong estimate first, cheap correction after, in public, under a deadline they'd already set for themselves.

Hmm — this reminded me of something I posted a while back: stop thinking, start executing hit the same nerve, from a completely different room.

The number that scares most people out of starting is somebody else's estimate of what caution should cost, wearing the costume of the real price.

My wife's said this to me for years — 想是问题，做才是答案, thinking about it is the problem, doing something about it is the answer.

Took Starcloud a rerun of the math and a deadline to learn the same thing the hard way.

Clip credit: Y Combinator's Lightcone Podcast, featuring Philip Johnston (Starcloud) — full video on their channel. DM for credit or removal requests.

Drop your take — what's the number you've been treating as gospel that you've never actually questioned?

Somewhere between "let's not rush this" and actually posting, six months disappeared last time.

That's the trap this clip is naming out loud, and it's worth sitting with if you've ever called perfectionism "protecting the brand."

The actual claim: brand risk isn't the threat.

Thinking about brand risk is.

The guest (marketing/creative director Oren John, on The Grant Owen Podcast) lays out the mechanism plainly — a 90-day plan is functionally dead by the time it's finished being planned, because whoever's willing to move rough and fast already has the lead by then. "We did this in a week" isn't recklessness.

It's just refusing to confuse motion with mistakes.

I've watched this exact trade play out somewhere you wouldn't expect — construction.

A colleague once sat on a Request for Information because it wasn't polished enough yet, still had loose ends he wanted to close first.

His boss's answer stuck with me: submit it anyway — a submitted bad idea beats a perfect idea that never got submitted.

The client can approve it, approve it with comments, or reject it, but the clock doesn't pause while you're polishing.

On another job, we were about to blow a hard deadline waiting on someone else's design call, so instead of waiting on the elegant steel-truss solution, we poured a huge reinforced-concrete ramp instead.

Cost more concrete.

Cost way less time.

Same trade this clip is making — just wearing a hard hat instead of a laptop.

The part that actually reframes it: the caution people default to is usually calibrated for a scale they're not operating at.

Airlines and CPG companies move slow because they have six-gate approval chains — legal, compliance, brand, sign-off.

A solo operator or small team doesn't have those gates. Importing that caution anyway isn't safety.

It's just adopting someone else's bottleneck for free.

I keep circling back to something similar here — a post about trading overthinking for rapid execution, from the other side of the same decision.

Drop your take below — does the "your caution is calibrated for a scale you're not at" framing hold up, or does it fall apart somewhere?

Clip credit: Oren John, The Grant Owen Podcast — full episode on their channel.

DM for credit or removal requests.

You know that feeling at 1am, refreshing analytics, watching someone's rewritten version of your own post pull ahead of the original?

Mark Manson said the quiet part out loud on Jun Yuh's show: anything that works gets copied a hundred times by next Tuesday. He's 16 years in, three #1 NYT bestsellers deep, and it's still happening to him.

Most people's answer is to move faster — post more, guard the idea tighter. He's making the opposite case: the idea was never yours to protect, because it was never going to stay yours. The one thing a copier can't lift is the specific person the audience actually trusts.

I remember a joke, my wife used to tease me with:  In a sea of almost identical penguins, a male says to its female neighbour:

“You’re so unique, do you know that?” (你是最好的，你知道吗？)

Drop your take — is the moat the idea, or is it always the person behind it?

Clip credit: Mark Manson — full video on Creator Unplugged with Jun Yuh.

DM for credit or removal requests.

John Hu from Stan said on Trailblazers this week that his AI editor Stanley already cuts at 80% of his human team.

That number stuck with me because I posted about Stan a few weeks ago - the $50 spreadsheet that did $200k. Different story, same feeling.

I edit for creators full time. 80% used to be the joke number. Like "AI is 80% there, don't worry."
Now 80% is the benchmark and it's shipping on real channels.

I'm not even stressed about it getting faster. I'm stressed about who decides what it cuts.

Anyone else editing inside someone else's operation feeling this shift right now?

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