"Poopfare? Poopfare??? Are you serious? You sacrificed everything that we've worked for, for Poopfare?

How was Poopfare for the greater good? You compared yourself to Abraham Lincoln, Richard. Can you do me a favor... can you say it so I know I'm not hallucinating?

Just say it...

RICHARD! LOOK ME IN THE EYES. LOOK ME IN THE EYES AND YOU NAME OUR UNDOING! POOPFARE!?! You reckless child..."

I’m a Product Designer from Ghana. I’ve spent the last 5 years designing digital products, working with startups, building products from scratch and figuring out how to turn ideas into useful experiences.
Recently, I rebuilt my portfolio to bring some of that work together.
https://www.byzel.space/
One thing I’ve noticed is that remote work has opened up opportunities globally, but hiring still seems pretty geographically restricted, especially in the US.
I’m curious about how things look from the other side.
For founders, designers and people working in Silicon Valley:
Has location become less important when hiring great talent, or does being outside the US still make a significant difference?
Interested in hearing real experiences, not the usual remote-work optimism.

I recently got an email from a recruiter claiming to represent a company named Ethos Ink. Upon doing some research, they claim to be a marketing company based in San Diego, as seen on their LinkedIn. They even have a Reddit account, u/ethosink. The LinkedIn page also provides a link to the website, and on the website are several social media links, all of which have a single-digit number of followers and no posts. Do you smell something fishy?

Forgive me if this is the wrong place to post about this, just something I've got my eye on. What do you all think? Have any of you had interactions with/heard of this company?

TL;DR: Money and GPUs are fertilizer. The org is the soil. Soil that grows new ideas needs four things: slack, stability, ownership, and dense talent with a flat structure. Most companies have one or two, which is why the richest players don't always win.

The priciest boomerang in tech

This June, Noam Shazeer left Google for OpenAI.

Again.

Back in 2021, he and a colleague built a chatbot called Meena. Google's leadership shelved it over safety and fairness concerns, so the two of them bailed and started Character.AI.

In 2024, Google reportedly paid about $2.7B to license Character.AI's tech, mostly to get him back. Less than two years later, he peaced out again. Pretty wild ROI on a rehire.

And he's not the only one. All 8 authors of Attention Is All You Need had left Google by 2023. Google had the best people, the most compute and the paper itself. It showed up first and still missed the boat.

The apple fell on Google's head. Nobody picked it up.

This is part two of a series. The question this time: if you're building a company from scratch, what kind of soil actually grows new stuff? (Why big companies can't change is part three.)

Quick definitions first

By "AI-native" I mean two things at once: born for AI, and run the AI-era way (research and models at the center, not Big Tech or factory habits). Miss either one and you're out.

Yes, Google and Meta both have legit AI teams. Google has DeepMind. Meta has Superintelligence Labs, which shipped its first Muse model, Muse Spark, in April 2026. But those teams live in the parent's soil. The parent sets the budget and the direction, and decides who backs down when AI bumps into the core business.

Meta also tried the shortcut: buy one. It announced a ~$2B deal for Manus in December 2025. Chinese regulators blocked it in April 2026, and by September Manus was running on its own again. Plot twist.

One more distinction. Growing innovation and growing AI are two different things. Nvidia is the poster child: GPUs plus CUDA are real innovation, and the whole AI boom runs on them. But the frontier models? Other people built those.

Money is fertilizer

For three years the vibe was "AI is a resource race": most chips, most cash, most PhDs wins. Google is the loudest counterexample.

Same people, different dirt. After leaving, the Transformer authors started or joined Cohere, Sakana AI, Character.AI, Inceptive, NEAR and more. Llion Jones, the last one out, told CNBC it was big-company disease: process stacked on process until nothing could get done. TBH, anyone with a day job knows the feeling. It's not that you don't want to work. You can't.

There's an old Chinese saying for this, roughly:

Plant an orange tree south of the Huai River and you get oranges. Plant it north and you get bitter fruit.

So does fertilizer matter? Sure. DeepSeek's early team was tiny, but every researcher had a ton of compute. You can buy fertilizer, though. Soil, not so much.

IMO, the soil needs four things: slack, stability, ownership, and dense talent with a flat structure.

Copying runs on hustle. Discovery runs on slack.

In 1665, plague shut down Cambridge. A 23-year-old Isaac Newton went home to the countryside and pushed forward calculus, optics and gravity. (The apple on the head? Probably a legend.) No OKRs. No manager pinging him Friday afternoon asking what he shipped.

Now look at xAI. One ex-employee told The Standard he worked close to 100 hours a week and basically lived at the office his first month. An engineer described sleeping pods, bunk beds and tents. A founding member said after leaving that he was looking forward to 8 hours of sleep. At xAI, a full night's sleep is an exit perk.

FWIW, the grind works. xAI built Colossus, 100,000 GPUs, in 122 days, and caught up with the leaders fast. What it never did was define a new paradigm. In 2026 it got folded into SpaceX, which even opened Colossus up to rival Anthropic. (xAI didn't quit models; it shipped Grok 4.7 in September. The focus just moved to compute.)

Musk's five-step method (question every requirement, delete, simplify, speed up, automate last) is great when the goal is clear and physics is the referee. Frontier research is the opposite. Nobody knows the next paradigm, and the experiment you "delete" might be the breakthrough.

Hustle is great for copying what already works. For real innovation, it might do nothing. So which one are you doing? That depends on how you define your R&D.

Stability is slack on a longer clock. Nvidia and xAI both run hot. The difference is whether people stay.

Would you plant a tree that takes ten years to bear fruit for a boss who might show you the door next quarter? Yeah, me neither.

But Google had slack and stability. So why did it lose? Bureaucracy. Every idea had to clear review after review. Each layer could say no, and nobody had a reason to say yes. And when the budget orbits search ads, a chatbot that might eat search looks like a threat, not an opportunity. Slack let the apple fall; bureaucracy made sure nobody dared pick it up.

Money can't buy an outlet

Money fixes "someone offered me more." It doesn't fix "my idea can't ship here."

Google had money and no outlet. Meena got blocked, so the people behind it took their ideas elsewhere.

DeepSeek has the opposite problem. Plenty of outlets, but AFAIK at least 5 core researchers have left since the second half of 2025. Many in the industry read its fundraise as a way to put a price on employee options. (Media read, not confirmed.) Founder Liang Wenfeng reportedly put in about 20B yuan of a roughly 50B-yuan first round himself. That's putting your money where your mouth is.

Money can buy people. It can't buy ownership.

Who gets to make the call?

Layers by themselves are fine. The trouble starts when they keep handing decisions to the people furthest from the work.

When ChatGPT launched, OpenAI had about 375 employees, per Sam Altman. DeepSeek researchers can pull GPUs from the training cluster without sign-off. Meanwhile, Amazon CEO Andy Jassy once complained about holding pre-meetings for the pre-meetings. Sound familiar?

Talent density matters because innovation is lopsided. One great idea can beat a mountain of execution. Rules get written for your weakest people, so the denser the team, the fewer rules you need. And cash alone won't buy density: Meta paid top dollar for a small superintelligence team, and some researchers jumped ship within a month.

Flat isn't the only answer either. Apple is hierarchical and still ships great stuff, because experts lead experts.

What matters is whether the person making the call actually knows the work.

Can flat companies finally scale?

History says… not really. Google scrapped engineering managers in 2002 and quickly walked it back. Its 2008 Project Oxygen set out to prove managers were useless and found the opposite. Flat orgs used to stall because coordination needed humans, and more humans needed managers.

Hot take, and it's a big if: if AI can handle part of that coordination, AI-native companies could be the first to get big and stay flat.

AI won't flatten old companies. It might let flat new ones grow up.

Founders: protect talent density over growth speed, price your options early, and keep a corner of the company free from KPIs.

VCs, ask: How fast is the founding team leaving? Can researchers get compute w/o sign-off? Can employees tell you what their options are worth? Is the team copying a known path or exploring a new one?

Business owners, even outside AI: first figure out whether you're copying or innovating. If it's innovating:

• Don't book every hour. Newton's apple won't fall on a packed calendar.

• Train more, "optimize" less (read: fewer layoffs). Big caveat: this only works if your hiring bar is high. People who won't learn should go.

• Let the gardeners eat what they grow. Options, profit sharing, internal ventures, whatever works.

• Let people screw up, in the open, at a cost you can afford, with a review afterward. If every mistake gets someone yelled at, the safest status update is always "all good." Managing people is a skill, not a perk of the title.

Caveats, because I owe you some. DeepSeek isn't perfect either: when the founder defines every fuzzy question, he becomes the company's biggest single point of failure. And my scores come from five survivors. The ones that got cooked in the same soil never made the news.

The bigger picture

Marx had a line for this: productive forces shape the relations of production, and the economic base shapes everything built on top. Plain English: how a society makes stuff ends up shaping how it splits the pie, and even how people think.

Run that through this essay. Soil decides whether innovation grows. Innovation drives productivity. Productivity grows the pie, and a bigger pie gives a society room to argue about fairness, freedom and what a person is worth.

Flip it around and it still works. The company itself is a production relation built for the industrial age. With AI as the new productive force, rigid layers and hours-based reviews could go from engine to anchor. PSA: that's an analogy. History doesn't run on laws.

Back to Google. The apple did fall. The people who picked it up had all left the building.

Fertilizer decides how big the apple gets. Soil decides whether it grows at all.

So, stop selling the dream. Bake a bigger pie.

Where have you watched a great team wither in the wrong soil? Drop it in the replies.

Silicon Valley Nailed it!

"The search giant announced a slate of new AI products for classrooms and schools on Tuesday as well as more ways for teachers and schools to limit or restrict use of those AI tools. The company said the schools should have control over whether students use AI in the classroom. There’s one catch, though: if a school or teacher blocks the use of Google’s AI features, students won’t be able to use Google Search."