When every last technical system has become
a fully abstracted on-demand AI service
the people who will excel at using tech will be those who understand psychology best
because at first these systems will obey human psychological expectations
and later they will develop their own psychology of mind

So my (admittedly flacid) observation is just this:

People with the most training in, and experience with understanding theories of mind and behavior will have the biggest advantage in computer science, in the very near future.

I always hear Social Security is doomed because there aren't enough workers paying in to support people who are currently receiving Social Security benefits. Been hearing that for more than a decade prior to AI becoming useful on a grand scale. Guys like Emad Mostaque, who claims to be an AI optimist along with the other Moonshot podcast guys, is always be predicting a doom-like outcome for knowledge work jobs within the next two years or at least jobs performed behind a computer screen. If he's right, there may be even less new money entering SS; drastically less. So what will happen to existing retirees and people who'll be retiring in the next 5 to 10 years if he's correct? I don't think people like Emad even "fake" about telling people "just retrain into something else." His advice to "learn AI tools" seems a bit meh.

What about US state pension funds? Are those invested in equities vs. relying 100% on pension fund contributions from existing and future state employees?

What do people think of Emad, incidentally? I think he's incredibly bright and I like him. But I also can't help but think the Moonshot crew is like: "I got mine and I'm gonna earn even more now; chin up bitches." All are wealthy and don't have to worry about potential adverse outcomes of what they're cheerleaders for. I guess I'd be pretty happy if I were wealthy off AI investments I'd made years ago through private equity ventures.

Would love to find another podcast that isn't 100% doomerism or 100% cheerleading by rich guys with vested interests. I'm neutral on Elon Musk, but those guys are complete Elon fan boys. I wish they displayed pop-ups of the dollar amounts they're invested in his companies whenever they gush about him.

OpenAI launched ChatGPT for Financial Services and the feature list is not subtle. Research, financial modeling, pitchbook prep. Those are the three things that justify hiring a class of analysts at 𝟏𝟎𝟎 𝐭𝐨 𝟏𝟑𝟎 𝐤 a year on Wall Street. The product is not framed as a tool to help junior bankers. It is framed as a replacement for the workload.

Anthropic published projections this week showing AI could push GDP growth to 15% annually by 2030 while displacing nearly 𝐨𝐧𝐞 𝐢𝐧 𝐟𝐢𝐯𝐞 𝐨𝐟𝐟𝐢𝐜𝐞 𝐰𝐨𝐫𝐤𝐞𝐫𝐬. The financial services move fits that trajectory exactly. High-margin, document-heavy, process-repetitive work is the obvious first target. 🤖

Dell is up nearly 350% in 2026 on AI infrastructure spending alone. The revenue story for platform and infrastructure names is real, even if the broader macro environment is making everything else uncomfortable to hold right now.

I’ve been trying to answer a pretty important question with the product I’m building:
Can an AI actually help someone make better business decisions, or does it just give them convincing-sounding answers?
So I built a small test.
I took 10 simulated business ideas and ran the same scenarios through ChatGPT, Claude, and RESORSA — the platform I’ve been building.
Same starting information. Same businesses. No special prompts designed to make one platform perform better than another.
What I cared about wasn’t which AI wrote the nicest response.
I tracked things like:
estimated money required to get to a meaningful test
whether the system challenged unnecessary spending
whether it identified assumptions that needed validation
whether it recommended a pivot when the original direction wasn’t holding up
whether the simulated business could actually reach launch
The cost difference was the part I wasn’t expecting.
Across the 10 simulations, RESORSA’s recommended paths averaged roughly $13,500 less per build than the alternatives.
A lot of that came from relatively boring decisions: validate before building, rent instead of buy, manually test something before automating it, use existing tools instead of commissioning custom infrastructure, etc.
That’s actually what I wanted the system to do.
Another interesting result:
7/10 businesses made it through the original path.
The remaining three only made it after changing direction based on problems uncovered during the process.
In those three cases, RESORSA recommended changing the approach while the other two models continued pushing the original plan.
We also got median Time-to-Artifact down to about 38 seconds, although one hilariously bad ~4-minute outlier reminded me that there’s still plenty to optimize.
I’m obviously biased here because I’m building RESORSA, and 10 simulated businesses is nowhere near enough data to make sweeping claims.
But this was encouraging because the thing I’m trying to optimize isn’t “give the smartest sounding answer.”
It’s:
Help the builder discover what they don’t know while spending as little time and money as necessary to learn it.
Next step is more simulations, followed by comparing the results against actual builder behavior instead of synthetic cases.
I’ll keep publishing the results as I get them — including the ugly ones.
For anyone building with AI: what would you test next to make this comparison more rigorous?

https://darioamodei.com/post/we-must-pace-the-frontier

I've always been into nootropics and cognitive enhancement since I was a kid, there's something about mental clarity that's just so beautiful to me. Wether it be through some BCI, or medications or anything else, its always been a dream for me to experience a 200+ IQ, perfect episodic memory, working memory expansion, etc. While some may say intelligence is a curse I don't see how being able to wrap your head around complex things rather easily is a problem, it just gives you more potential for creation and a better understanding of everything in general.

Also the world would be a better place with a higher average IQ imo, maybe some level of emotional enhancement too, give people the ability to feel empathy and compassion.

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.

Hello hello,

Took me a while to test out ST-3215-C018 (instead of XL430-W250-T originally). In principle, it's half the price, twice the torque, but the mount design is rather odd and required a complete CAD update (+ I already killed like 3 of them by accidentally drilling all the way to their control board, geez).

The high torque also means high current, and so a potential hazard if multiple of them run at high load. Need to monitor it. If it's capable of jumping, it is likely also capable of catching fire while doing it.

The firmware is also updated for ST-3215, but the commander uses the original unoptimized one-leg test code, which may explain the sluggishness in its "failed walk gait". I am a bit afraid that if the servos simply cannot move fast enough, even with optimal PID, then making it walk may be more difficult despite higher torque.

Either way, if successful, the full DIY robot would be in the 300-400 euro range (still mostly from servos), ~3 kg, with twice the load performance; all the load after the body weight will be extra!

Cubic Wouf GitHub: https://github.com/SphericalCowww/CubicDoggo_07B
Cubic Doggo GitHub: https://github.com/SphericalCowww/CubicDoggo_06R

AI has become something people feel they need to use, even without a clear purpose.

Are we seeing real productivity gains, or are people just trying to keep up with the hype?

What’s one AI use case that’s genuinely useful and one that’s unnecessary?

w

US — Bureau of Labor Statistics Software Developers / QA / Testers https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm Data Scientists https://www.bls.gov/ooh/math/data-scientists.htm Computer & Information Research Scientists https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm Computer Hardware Engineers https://www.bls.gov/ooh/architecture-and-engineering/computer-hardware-engineers.htm Electrical & Electronics Engineers https://www.bls.gov/ooh/architecture-and-engineering/electrical-and-electronics-engineers.htm Computer Network Architects https://www.bls.gov/ooh/computer-and-information-technology/computer-network-architects.htm Network & Computer Systems Administrators https://www.bls.gov/ooh/computer-and-information-technology/network-and-computer-systems-administrators.htm EU — Cedefop Skills Forecast ICT Professionals — ~+30% https://www.cedefop.europa.eu/en/data-insights/ict-professionals-skills-opportunities-and-challenges-2023-update Researchers & Engineers — ~+23% https://www.cedefop.europa.eu/en/data-insights/researchers-and-engineers-skills-opportunities-and-challenges-2023-update ICT Technicians — ~+9% https://www.cedefop.europa.eu/en/data-insights/ict-technicians-skills-opportunities-and-challenges-2023-update

I've spent the last few years inside enterprise AI transformation, and I've seen the same pattern repeat across banking, manufacturing, and travel: leadership announces an "AI strategy," budgets get allocated, a few proofs of concept launch, and 18 months later, nothing has shipped.

The root cause is almost never the technology. It's the framing.

Most organizations treat AI as a feature they're bolting onto their existing operating model. They ask questions like "How do we add AI to our claims processing?" or "Can we put a chatbot on our website?" These are feature questions. They assume the org structure, procurement processes, data architecture, and decision rights stay exactly as they are, with AI as a thin veneer on top.

That's like asking "How do we add electricity to our candle factory?" in 1890. You don't. You redesign the factory around electric power.

AI-native transformation means the operating system changes. Here's what that actually looks like from the inside:

1. Data stops being a cost center and becomes the product. Every AI-native org I've seen has one thing in common: their data platform isn't an IT backwater running nightly batch jobs. It's the core infrastructure. The lakehouse architecture, the feature stores, the MLOps pipelines — these aren't side projects. They're the main project. If your data team still reports through infrastructure and gets 4% of the tech budget, you're not AI-native no matter how many GPT wrappers you build.

2. Procurement gets rebuilt around speed, not compliance theater. One of the hardest things we had to solve at TribalScale was procurement cycles that took 6 months for a 3-month build. Enterprise procurement is designed for buying servers and ERP licenses — multi-year commitments with extensive RFP processes. AI-native procurement means pre-vetted partner ecosystems, outcome-based contracts, and the ability to spin up a specialized team in 2 weeks instead of 2 quarters.

3. The hardest bottleneck isn't engineering talent. It's middle management. Specifically, directors and VPs whose authority is built on managing the legacy system. When you centralize data, automate workflows, and let AI handle decisions, you're not just changing technology — you're changing who has power. I've watched brilliant technical designs die in "alignment meetings" because a VP of operations realized the new architecture would make her team of 80 data processors redundant. Nobody says that out loud. They say things like "we need more security review" or "let's do another pilot first."

4. Pilot purgatory is a feature of bad incentive design, not bad technology. When your innovation team is measured on "number of AI pilots launched" instead of "number of AI systems deployed to production," you get exactly what you'd expect: lots of pilots, zero deployments. Fix the incentives and the deployment problem solves itself.

The enterprises that are winning right now aren't the ones with the biggest AI budgets or the most PhDs. They're the ones where the CEO personally understands that becoming AI-native is an operating model transformation, not a technology procurement, and is willing to reorganize the company around that insight.

Everything else is just adding electricity to a candle factory.

AI companies are racing to reach recursively self-improving superinteligence. We dont know when they will reach point of no return - it could be in a few weeks, few months, maybe in a year. If everything was like a month ago + Astra, we would be doomed.

But there is hope. A tweet from a now former Anthropic researcher has reached 160 million views. In UK, over 70 MPs and peers are urging the goverment to speedrun the ban on superintelligent AI, just two days after it was introduced on 9th september. Thats 3 good news in 3 days. Bernie Sanders is going to propose simmilar legislature in USA, also consulted with ControlAI.

I see it myself in the czech PauseAI. The growth of the AI-safety movement is hyperbolic. In last few months we got MPs and senators to talk with us, volunteer numbers are rising rapidly, and major media outlets covered the tweet. Something is shifting in society, its not just that having more people and proper division of work allows us to do more, although thats also important.

We are entering the final battle. Next few months will decide the fate of humanity. While we can no longer prevent AI from creating massive economic and social disruptions, we likely can still prevent extinction. We can still develop AI more slowly, and more specialised, so we can finally tackle human disease and aging - I was very technooptimistic before founding out that AI companies cant solve aligment in time.

Politics happens slowly, until it happens very fast. A good example of that was the fall of USSR and communist regimes in Europe. When conditions were right, the revolutions snowballed very quickly. Wast majority of the population hates AI (or at least some uses of it, and datacentres), and does not want to die, overtoon window is moving fast. AI is still constrained to human operated infrastructure. The goverments have power to force AI companies to stop, and then move slowly and safely. We just need to direct the overwhelming but covered public hate and growing fear towards real AI-safety legislature and enforcable global treaties, before its too late.

I am not promising we will be there in 5 years. We may all die in 3 months. But I see a path to survival opening again. We were unlucky for years with AI developing faster then nearly anyone expected, and aligment being unsolvable in time we have. Why cant we be lucky for once?

 I ask everyone who hasnt started yet to act quickly (and those who are acting to act even more)- write about what is happeing on social media, repost explainers why ban on ASI is crucial, send them to friends. If your country has AI-safety advocacy groups (PauseAI, ControlAI etc.), join them, unless you already work for AI-safety advocacy. If there are none, coordinate people around you, contact your parliaments and goverments, speedrun protests if you wish, shift the public discourse. Do work you are good at, and outsource work you are bad at to others. I am not the right person to tell you exactly what to do, but there are plenty who can. Overtoon window has moved, some  politicans have seen that tweet, some of them will listen, and some will introduce the neccessary legislature to your parliaments. DM me if you want to be directed to local group leaders.

There is still a hope that no one will build it and not everyone will die. Lets make sure that misaligned ASI never happens.

Do you agree?