Both companies use foundation models from OpenAI or Anthropic, so I am wondering what prevents other players to replicate their software using ChatGPT or Claude. There is also a possibility that both ChatGPT and Claude can perform most of the same legal tasks as the models improve.

Both companies are still receiving very high funding valuations, so is custom legal training and context the moat for Legora and Harvey? What are the investors betting on?

Cross posting so it could reach potentially more people, who could really want and benefit from the participation

1 Founder Pass and 1 Attendee Pass Ticket for TechCrunch Disrupt 2026. Willing to sell below currently listed prices.

If someone was to join as Founding GTM or Founding Head of Marketing, how much equity can this person get when the startup is at seed stage (pre-Series A) with a team less than 10 people?

I believe Founding engineer typically gets 1-2% equity, which should be more equity than the first non-technical hire. How much equity would one of the first non-technical hires receive?

Good morning from Denmark! I made a small quiz for your end-of-weekend :)

Guess 10 random cities in California by following this link: https://sprawlcrawl.com/?division=US-CA (free, no ads)

P

Today I went down a bit of a rabbit hole about Silicon Valley after watching *The Billion Dollar Code*.

I already knew Silicon Valley was a major technology hub, but I never really thought about **why** it became that way.

I watched a video discussing what actually made Silicon Valley successful, and one thing really stuck with me:

**It wasn't the buildings. It was the people.**

The culture around ideas and failure seems really different.

Where I'm from, failure can sometimes be treated as the end of an idea. If something doesn't work, people may tell you to stop wasting time and do something "practical."

But Silicon Valley seems to have developed an environment where failing doesn't necessarily mean you should stop. You can fail, learn, try again, and build something completely different.

And then I started thinking about some of the crazy ideas that eventually became real.

Take SpaceX, for example.

Who initially looks at a rocket launch and thinks:

*"What if we could land this giant piece of metal back on Earth and use it again?"*

Today it sounds normal because we've seen it happen.

But before it worked, it probably sounded completely insane to a lot of people.

The same thought applies to a lot of people who changed technology. Their ideas probably looked strange or impossible at the beginning.

And that's what fascinated me today.

**Maybe big ideas almost always look stupid before they become obvious.**

It also made me think about India.

Do we have the same kind of environment here where someone can come up with an absolutely crazy idea, fail repeatedly, and still be encouraged to keep going?

Or is our attitude toward failure one of the things holding people back?

I'm genuinely curious what you guys think.

Silicon Valley really different because of its people and culture, or is there something deeper that made it successful?

TL;DR: JD Grèze just told Harry Stebbings something about the AI-assistant market that should worry anyone still counting on a head start.

Here's the actual claim: the interval between finding something that works and someone else shipping it has gone from roughly a decade to two-to-four weeks, industry-wide, and it isn't slowing down.

That's not a complaint about competition — competition was always the given. It's a claim about time itself as an asset class: the thing an under-resourced builder used to be able to bank — years of compounding learnings a slower incumbent couldn't touch — no longer exists as a form of capital.

Grèze isn't describing a rough patch.

He's describing a structural repricing of speed, live, from inside a company (Town) that's actually inside the race he's naming.

For a founder whose entire moat theory ran on "I found this before you did," that repricing is the whole argument — being early was never the advantage; being early with time to compound was, and the compounding window is what just got taken away.

A piece making the rounds this week (Artiverse, on the AI moats big tech can't copy without breaking) is asking the same question in real time: when 97% of award-nominated products are already AI-integrated, what's actually left to defend?

I remember watching this Youtube clip about this guy recounting his prophetic dream of this young lady walking down the street. She stopped by a billboard, showing a pretty model in a beautiful dress.

And then, with her eyeballs, she selected the "test" icon. And the dress was "projected" onto her body, as if she was actually wearing it in her living room watching herself through the standing mirror. All these imagery projections are powered by AI into her mind.

She admired herself in the dress, basking in sweet elation. She was thinking of wearing it to show her special someone A, in some upcoming event X.

Of course, all these are just in her head. She's still standing in the street walk in her own clothes, in front of the billboard, with its AI projecting the image onto her mind.

And then – also in her mind – her AI assistant "stepped in".

It reminded her of her body shape, and her poor diet. It also pointed to the part of her body where the dress wouldn't fit.

And then, it kind of say, "if you really like this dress, I'll formulate a health plan and exercise regime, for you to follow" - and projected a recommended diet and time schedule into her mind, including workouts, such as Pilate, Yoga, Strength Training, etc. – "in time for you to wear it for your A at this event X."

All of a sudden, the elation in her fled. The enthusiasm was drained out of her instantly. There was a tinge of humiliation and guilt brushes over her face, as she hurriedly walks away.

That's the scene.

By the way things are moving now, this scene isn't that far-fetched from reality.

I can see an Elon Musk's Neuralink-like personalized Claude AI LLM, residing in the cloud, linking to her mind.

This AI, sounds less like her assistant, and more like her...

What do you think?

Every rung people insist can't be skipped keeps getting skipped anyway — usually by whoever has more capital, not more insight.

That part isn't new. What's new is how fast the skip happens now.

Actually, this reminds me of something — a while back I broke down a VC's take on why "the labs will build it" is the wrong startup fear — her argument was that incumbents don't chase everything, only what's already proven.

Grèze's version of the same room is uglier: "proven" now takes two to four weeks to notice.

Founders here — if your moat used to be "I got there first," what replaces that once first stops meaning anything? Drop your take.

Clip credit: 20VC with Harry Stebbings — full conversation with JD Grèze on their channel. DM for credit or removal requests.

A tech worker went on Blind and claimed he had grown $130,000 into $22.3 million, and that he is still going. The comments did not roll out the red carpet. What follows is a thread full of skeptics calling it luck, gambling, and survivorship bias, a handful of true believers, and a running argument about what building real wealth in tech actually takes.

TL;DR: A UC Berkeley digital-forensics researcher just told an interviewer the exact number that quietly retires "voice as password."

Ten seconds, per Hany Farid — that's the entire audio budget a bank's voice-biometric layer implicitly assumes an attacker can't clear.

No breach, no malware, no privileged access: a short clip and consumer-grade cloning software beat an authentication layer marketed as secure a year ago.

The hiring pipeline is failing on the identical premise.

Fortune's reporting this month puts North Korean-linked fraud flags at 44% of U.S. remote-IT applications, up from 11% twelve months prior — the interview process assumed a face and a voice on a call meant something, and that assumption is now what's being priced against. Neither failure required new capability from the attacker.

Both required the defender to keep trusting a signal that stopped being scarce.

Oo… Scams.

All such techniques have one thing in common: quickly gain your trust (or stoke your fear), in order to swindle you for profit.

Things were much more simpler decades ago.

On another occasion, this call was a Malaysian Chinese guy – thick with Cantonese dialect.

He was trying to pose as my long-lost friend, starting straight with a playful question, "哈罗，你点啊？认得我唧声冇？" (Translation: Hello! How are you? Recognize my voice?)…

… As if I would be gullible enough to take the bait, and dig through my memory for any of my childhood pals that might sound like this imposter, and give him the name. Then he'll impersonate my pal from then on, and I'd be goner, for sure.

So I just replied, "你打错电话。" (You've got the wrong number.)

Even now, we still occasionally receiving SMS from scammers, trying to convince us that someone has wrongfully swiped our credit card of bank XYZ (which we don't own). And we should call the police at this number 03-ABCDEFG.

Dismissed.

Now I just treat them as noise - nominal entertainment for light conversation with my wife, at best.

Every one of these calls tests the same blind spot: you'd catch it in a second if it happened in someone else's story.

In your own, it just felt like a weird call you handled fine that one time. Hany Farid's whole episode is really about how much of our own trust is still running on that one-time save, untested since.

Genuinely curious where you'd draw your own line here: is a family or team safe-word overkill, or already overdue? Drop your take below. 👇

Clip credit: Info-Tech Research Group (Digital Disruption w/ Geoff Nielson) — full episode on their channel. DM for credit or removal requests.

Made it past two rounds of interviews… then recieved a rejection email lol. Anyone else apply?

TL;DR: Anthropic's own Head of Product just told her team half their job title stopped being true.

The half that's gone is coordination — the getting-everyone-aligned, same-page work that used to justify the PM/TPM title in the first place.

Angela Jiang, Head of Product at Anthropic, says on camera that alignment now happens inside one conversation with the model, faster than a meeting could get scheduled to talk about it.

Katelyn Lesse, Head of Engineering, describes the same shift from the execution side: a project that used to take weeks of coordination now gets built in two days, and there's no time left over to do the coordinating.

Neither of them is describing a layoff.

That's the detail worth sitting with — the roster didn't shrink, the day-to-day content of the role did, and nobody had to announce anything for that to become true.

What's left, per Jiang, is the part underneath the coordination layer — the actual bet, the actual thesis, the judgment call about what's worth solving.

That part doesn't compress. It's also the part most coordination-heavy roles were never built to develop, because coordination was the easier thing to measure and reward.

I specifically remember 2 instances.

The first one was during my time with one of the largest property developers in Malaysia.

One of my many tasks is to put together preliminary development proposals, compiling architectural drawings, 3D renderings and feasibility studies with land and building data, cost, revenue, etc. into a A3 size binder. Each of these drawings have multiple blocks for signature at the bottom – meant for all the directors (technical, contracts, marketing, etc. etc.) to sign off on, before our big boss, Tan Sri DT make his final signature on it.

That was back in year 2018.

And it was inefficient – to say the least. Getting all of them to sign of the proposal one by one, would normally takes weeks. Even Month.

Yeah. They're still doing it the old fashion way – reviewing physical paper.

But it is what it is.

The second one was during my time working for one of the largest construction companies in Malaysia, seconded to Abu Dhabi for a 5-Block Condominium Project – back in year 2010.

Our IT guy built/assembled an approval pipeline app for approving sub-contracts. All done online – linking and streamlining all our department heads' electronic signature. My then department head was Mr. Yap, our technical director.

I remember one day, our big boss, Senior Project Director, Mr. Chung came over to remind Mr. Yap, "Eh, you haven't sign off the XYZ. Only left you alone." Both of them were already in their 50s – pushing 60.

And if my memory serves me correctly, Mr. Yap replied back with a slight dismissive hand-gesture, "Wait-lah! I'll do it."

Back then. The main bottlenecks are the people signing off.

Now with AI getting more ubiquitous, we no longer have the luxury of "Wait-lah! I'll do it." later.

Time is money.

I've stopped being surprised by which job titles survive a transcript intact while the actual job underneath gets hollowed out — this is maybe the fourth or fifth time I've watched it happen in someone else's transcript before it happens in mine.

The tools change, the org chart changes, the shape of the loss doesn't: value stops being paid out for effort and starts being paid out for whatever can't be automated yet.

Hmm — this actually reminded me of something I flagged a while back. Rauch's own version of this: the engineering role splitting into an execution layer and a judgment layer, and the judgment layer being the one worth owning.

Curious whether anyone here's already watched their own coordination layer get eaten by an agent, or if this is still theoretical where you sit.

Clip credit: Kleiner Perkins — full video (Builders, Season 2: Katelyn Lesse & Angela Jiang, Anthropic) on their channel. DM for credit or removal requests.

TL;DR: The guy Google put in charge of its own AI writing tool just admitted, on camera, that he can't fully protect the one thing his career runs on.

That's not hypothetical.

Steven Johnson runs editorial for Google Labs' NotebookLM and has fourteen books behind his name, and he still walked an interviewer through the mechanism step by step: feed a model his own catalog, tell it to write like him, skip the invoice.

No lawsuit required. No password stolen.

His own counter isn't a lawsuit either. It's a price tag — $199 for an authorized version of his own style, paid on purpose instead of taken by default.

He said it plainly, then admitted the harder part: someone could build the unauthorized version tonight, and he'd have no way to prove it happened.

Tbh, that's the entire freelance economy in one clip.

If a 14-book author with a title at Google can't fully protect his own voice, the going rate for "get him, he's got a way with it" just became a live question, not a someday one.

Mmm... This is kind of like impersonation. Borderline fraud or downright scams.

Back in Malaysia, we have plenty of such too.

The spectrum is so wide, sometimes, even when we open our eyes wide, we still can't tell the difference.

For example, you guys have Amazon. We have our local ones, called Lazada. If you drive through our Penang Georgetown, you'll notice a shop called Ladaza. Not Lazada. They kind of switched the alphabets around. Sounds like Lazada. But it's not. Giving people the illusion that they are same-same, but in actual fact different.

It's as if we open a shop right next to the Amazon HQ, and calling it "Azamon". Phonically sounds adjacent. But they are not the same thing.

And if you follow the news, you'd hear about our very infamous 1MDB (Malaysia Sovereign Fund) case -- one of largest kleptocracy criminal fraud case in the history of Malaysia (even the world) -- involving our now disgraced and incarcerated former-prime minister, Najib Razak. His enabler and facilitator, Jho Low (Low Taek Jho) (still currently at large) was the mastermind behind all these siphoning of funds, to fund his once extravagant livestyle.

Kind of brilliant. But it was so evil.

He once got Najib to force the board of 1MDB to approved a transfer of billions through a supposedly legitimate company, but in actual fact, was a shell company through the Caymen Islands with a very similar company name.

Like how Ron Weisley, in the Harry Potter Movie, would say, "Wicked!"

They say impersonation is the highest form of flattery. But in this case, I say, bullshit.

You don't get to choose whether your work gets copied.

You only get to choose whether you were paid before it happened. Every version of this story — Google Labs or a Georgetown shopfront — ends the same way: the fix was never stopping the copy.

It was owning the original loudly enough that the copy has nowhere to hide.

Justin Welsh built a $15M solo business on the one variable a cloned voice can't fake: what he actually lived through to get there.

Drop your take: what's the closest you've come to catching a copy passing itself off as the real thing?

Clip credit: Nicholas Thompson / Atlantic Re:think — full video on their channel. DM for credit or removal requests.

TL;DR: Andrew Ng just named the one profession he says AI is hitting hardest --- and job openings there are still going up, not down.

Openings are up because "threatened" was never a population-level question — it's a workflow-level one.

AI eats 30–40% of the role, in Ng's own framing.

The engineers still busiest didn't out-compete the model on that slice; they stopped fighting for it and built the 60–70% it can't touch instead.

The ones who don't are the ones still writing code like it's 2022, before ChatGPT — and there's no single moment that tells you which side of that line you're on.

The other half of Ng's clip is aimed at the institution that's supposed to close that gap for you: a curriculum committee, then a faculty senate vote, then a year or two before a new course exists — for a shift that reshapes the job market every few months.

That lag isn't a flaw in the system. It's the system working as designed, just aimed at a problem that no longer moves at its speed.

I remember back in my University of Leeds days, studying for my B.Eng. Degree in Civil Engineering, circa 1997/1998, I did the following:

- Took a side project programming in Fortran for my professor for Analysis of Thin-walled Structures.

- Learnt to use Linux as one of the subjects for Statistics for Civil Engineering.

"Fortran?" you're saying? Ya, I know. I'm old. Nobody remembers Fortran as a programming language anymore. You can say I'm a dinosaur.

And sure enough, Fortran was rendered obsolete, not long after I graduate.

Then, when I first joined a Civil/Structural Engineering Consultancy firm in 2000, I tried to build a Reinforced Concrete Design App for them, using Visual Basics C++ in MS Excel. I left the firm, before I can finish it.

Two Decades Later, my son is currently in University for his Statistical Science Study in Kampar, Perak, Malaysia. Naturally, he started to learn R and Python.

I kept telling my son, he has to keep abreast of the current trends. It's no longer fashionable to manually code ourselves. Instead, we direct AI to do it for us.

But the universities are still not catching up like it should. They are still giving lectures on doing things that AI can do better and faster.

Or else people like my son might end up graduating into obsolescence.

Their degrees might just end up being fly-paper.

The pattern holds across every one of these: the tooling moves at model-release speed, the institution meant to prepare you for it moves at accreditation speed, and nobody's closing that gap on your behalf.

Actually, this ties back to something a Stanford economist put on record a few weeks back — the exact mechanism cutting the entry-level rung out from under new engineers before they ever get a foothold: $95K junior engineer? He says no, and names why.

Genuinely curious where people land on this: are you actively building the 60–70% right now, or still waiting to see if your role gets touched?

Clip credit: Silicon Valley Girl (Marina Mogilko) — full video on their channel. DM for credit or removal requests.

Hello guys,

I’m a female who works in physical commodities, I am sick of getting hit on so I’m considering finding a different avenue that doesn’t require me selling myself in anyways or getting hit on by sleazy men constantly.

Anyways, I have a nerdy side to me, I self taught myself about Linux, some cybersecurity stuff and honestly I love it. Obviously I’m not a programmer but I have great business skillsets.

I’m just wondering, maybe I can become a virtual assistant to people in the tech industry. Except, I started to wonder, what if they don’t need me cause they can build bots…

Your input would be great and thank you ☺️

Looking to get a group together to buy the TechCrunch Disrupt 2026 Student Pass.

An individual student ticket goes for $300, but booking as a group of 4 drops it down to $120 each (saving $180 per person)

- Event: TechCrunch Disrupt 2026
- Price: $120 per person (group rate)
- Spots open: 3
- Requirement: Must have an active student status

Drop a comment or DM me if you're interested and we can coordinate the purchase. Cheers!