Joshua Kibbey

Reality is analog but our perception is often digital.

[Joshua Kibbey @KibbeyJoshua]

Our observations often say more about us than that which we observe.

[Joshua Kibbey @KibbeyJoshua]

@jordihays Garbage collection is necessary for a healthy ecosystem.

[Slava Akhmechet @spakhm]

Braindump on what made Stripe great (c. 2018):

- almost everyone was agentic, smart, and conscientious.
- agentic matters because ppl go out and find new ideas without being told. Also creates very high positive energy that's impossible to replicate merely by top down pressure.
- intelligence matters because ideas, execution, process, etc. are just better (and more fun).
- conscientious matters because you get no slop and great delivery. Ppl chase things down to bedrock, then actually follow through. Everything you read is super high quality. (But it does demand tremendous energy expenditure; not for everyone)
- tons of experienced ppl from world-class institutions. You can call it credentialism, but it also meant any question you have, there is a world-class expert on that topic. Pricing, engineering, m&a, product, ops, finance, whatever niche topic you might care about, etc.
- creativity was amplified by a very lightweight process that kept ppl from doing dumb things. Basic stuff-- talk to customers, validate hypotheses, decide what you're not doing, fast demos, etc. Blindingly following the template would alone produce surprisingly good results.
- an ambient value that quality is its own reward. Stripe didn't need good design but had a killer design team for this reason. But you'd see this in everything.
- the org produced tons of very high quality signals that were aggregated up to the exec team, they'd process the signals, guidance would diffuse down, the process would repeat. You could clearly see information pulse up and down the org, which gave a distinct feeling that every single person had tangible input into company direction.
- incidentally, the previous point results in a much better company strategy. It only works if the signals are high quality though, which can only happen if the talent bar is high.
- charismatic founders. That goes a really really long way.
- frequent reorgs. A lot of ppl see it as a negative (which I can understand-- reorgs can be stressful). I always saw it as continuous org-level garbage collection and refactoring. A counterfactual in which a fast-growing company isn't doing this would produce much more painful problems imo.

There is probably a lot more stuff, but I'm running out of steam.

[Chris Bakke @ChrisJBakke]

I'm becoming increasingly concerned that the Italian engineers buying massive saas companies for 2x revenue are only doing it for a paycheck, as opposed to the company’s mission.

[Joshua Kibbey @KibbeyJoshua]

Good Morning

[Deedy @deedydas]

Startups regularly underestimate how difficult hiring gets, especially after an expensive Series B/C.

1. Mission matters more.
The people who join you at Seed/A might want to build a sales intelligence tool because they like seeing 0 to 1. They know that once this gets big, they’ll take home a good chunk of change. After a B/C, they think “is this really what I want to be working on?”

2. Financial incentives are lower.
You easily see a path for a $30M valued startup to 10x. Usually this means going from $0 to $10M in revenue. Seeing a path for a $1B valued startup to 10x is far harder. It can mean going from $10M to $200M+ in revenue. And given the incrementally lower equity employees get, they’re counting on that 10x.

3. You attract a very different persona.
They’re usually more risk averse and riding on the coattails of the success and name your company has already built. Culture can easily dilute if you’re not careful. The builders get replaced by the certain kind of BigTech person who wants “startup experience” without taking on the risk. They might still be smart, so it’s tricky to catch in any sort of technical interviews.

4. Culture degrades with size.
It’s almost by law. In the beginning, you’re under 50 people. You’re all working on a startup you stood up from nothing. This builds a strong sense of camaraderie. As you go to 200 people, your early builders become managers. You start seeing more and more unfamiliar faces in the offices. At some point, you don’t even know everyone in the company. Everyone is eager to do “new” things and leave their mark, but what needs to be done is quite straightforward. The sales team feels like a different kind of person that takes up half the office. You’re eagerly watching the revenue, and your emotions ride on the back of it now, not the joy of creating. Management is in disarray. Now, projects keep getting killed. People keep getting roped into a new “customer issue” and can’t do their main project. New employees feel like this isn’t the culture they signed up for. Old employees feel like they work as hard as they used to from day 1, but the new employees treat this like a “job”. You get your first set of departures. Morale is low. Lunch banter shifts to “what if we just went to <x> instead?” Keeping the company from tearing apart at the seams seems like an insurmountable task.

Growing past these rounds can be very challenging and many founders are left blindsided. The awesome company they once had can quickly become a shadow of its former self. And it’s a stage which often separates the elite founders from the great ones.

The answer here is usually having a mission worth going the distance for or a culture worth fighting for.

[James Cham @jamescham]

Life makes much more sense once you realize that other people are better at social puzzles than cognitive puzzles and they actually prefer the former over the latter!

[jack @jack]

https://t.co/WFWSz5jEpc

[pash @pashmerepat]

Absolutely beautiful rant about AI in Linux Kernel from Linus yesterday:

I realize that some people really dislike AI, but this is an area
where I'm willing to absolutely put my foot down as the top-level
maintainer.

Linux is not one of those anti-AI projects, and if somebody has issues
with that, they can do the open-source thing and fork it.

Or just walk away.

AI is a tool, just like other tools we use. And it's clearly a useful one.

It may not have been that "clearly" even just a year ago, but it's no
longer in question today.

There are other questions around AI (like what the economy of it will
actually look like in the end), but "is it useful" is no longer one of
those questions. Anybody who doubts that clearly hasn't actually used
it.

Yes, it can also be a somewhat painful tool, both for maintainer
workloads and just from a "it keeps finding embarrassing bugs"
standpoint.

But the solution is not to put your head in the sand and sing "La La
La, I can't hear you" at the top of your voice like some people seem
to do.

The solution is to make sure those LLM tools _help_ maintainers
instead of just causing them pain. There's no question on that side.

We're not forcing anybody to use it, but I will very loudly ignore
people who try to argue against other people from using it.

And no, AI isn't perfect. But Christ, anybody who points to the
problems at AI had better be looking in the mirror and pointing at
themselves at the same time.

Because it's not like natural intelligence is always all that great either.

The kernel project has been and will continue to be about the technology.

Sure, the social angle of working on open source is important and
often a very motivating part of the project, but in the end that's a
side benefit, not the _point_ of the project.

This is *NOT* some kind of "social warrior" project, never has been,
and never will be.

In the kernel community we do open source because it results in better
technology, not because of religious reasons.

And so we make decisions primarily based on technical merit. Not fear
of new tools.

Linus

[Polymarket @Polymarket]

BREAKING: Argentina will face Spain in the World Cup final.

[Joshua Kibbey @KibbeyJoshua]

@Jonathan_Blow @chamath Because each rule is tied to a spot on the code.

You look at the code and verify it was interpreted correctly

[Collin Rugg @CollinRugg]

Drone operator sends 2,500 drones into the air for a drone show celebrating America's 250th birthday in North Richland Hills, Texas.

"...For America 250, we celebrate in style!" said Sky Elements Drones.

Remarkable.

[Joshua Kibbey @KibbeyJoshua]

@NPGrothe @SawyerMerritt Live in the Austin suburbs and see cyber cab apparently mapping routes with some frequency.

Seems like they may try to hit the burbs soon.

[Cuy Sheffield @cuysheffield]

1/ Today, we announced Visa is joining Open Standard alongside Stripe, Coinbase, Mastercard, American Express, Blackrock, US Bank, BBVA, Standard Chartered and 100+ initial partners with the mission of issuing Open USD, a shared stablecoin designed for the global financial system.

[Justin Skycak @justinskycak]

When you hit a wall in math, coding, or any hard skill, do not immediately conclude that you lack talent. Most walls are just prerequisite debt finally coming due. Go back, fill the gaps, make the basics automatic, and the wall often turns into a staircase.

[Joshua Kibbey @KibbeyJoshua]

@Austen Sad and true

[Isaiah Taylor - making nuclear reactors @isaiah_p_taylor]

Tonight at 4pm PT, Valar Atomics will initiate a SCRAM and subsequently a Loss of Forced Cooling event on the Ward 250 plant. This will be our most important safety demonstration to date, showcasing how far advanced nuclear has come in fundamental safety.

Loss of cooling has always been the central challenge behind some of the most serious historical reactor incidents; it’s what caused the meltdowns in both Fukushima and Three Mile Island. After a reactor shuts down, the recently split atoms continue to give off heat as they work down their decay chains, causing temperatures to rise in the core. In traditional reactors, this means that it is necessary to continue running the cooling pumps for several days after a shutdown. In the case of both TMI and Fukushima, forced cooling of the core failed, causing meltdown.

So why are we going to initiate a Loss of Forced Cooling event tonight?

Because the Ward series of reactors are fundamentally different from the reactors of prior generations. We designed this reactor to be inherently and intrinsically safe, also called “walk-away” safe. Tonight, we’re going to demonstrate that.

After commanding a SCRAM of the reactor, our Senior Reactor Operator (SRO) will command the reactor operator to shut down the main circulator, turning off forced cooling. But the SRO will not stop there—we are going to simulate total electrical failure of the plant. In addition to shutdown of the coolant loop, we will shut down the chiller, the RCCS pump, and both building and nuclear HVAC systems.

This will leave the reactor without any active cooling of any kind, giving us a complete demonstration of the passive safety of this architecture. Over the next 24 hours, we will see the decay heat in the core safety distribute through the system and leave through the RCCS via passive circulation.

We are not going in to this blind. We did this test in Hawthorne late last year at much higher temperatures and with a simulated decay heat input more than 100x higher than we’ll be demonstrating today. But tonight, we’ll be doing it with real nuclear decay heat.

Join us live at 4pm PT / 7pm ET on the Valar Atomics X account!

[Luther Lowe @lutherlowe]

This is a bad plan for little tech and competition. Anthropic will just sort by its highest paying U.S. companies which will leave startups further behind.

[Special D. Circumstances @AJAlkaline]

@KobeissiLetter This is the worst possible outcome. This means that a handful of the most connected companies are going to get an absurd massive advantage over everyone else. This is the sort of thing I would consider boycotting Anthropic over.

[Chamath Palihapitiya @chamath]

At a very hi level, free cashflow = operating cash flow - capex.

The hyperscalers are deep into an investment cycle so they are consuming their operating cash flow. It is incorrect to look at this and assume their FCF has collapsed because operating cash flow has collapsed.

It hasn't. Capex has exploded.

This cycle should be eerily reminiscent of Amazon's approach over the past 20 years when they did the same thing related to e-commerce and AWS buildout. The question should be what moat did Amazon create at the end of that cycle and what kind of moat could the hyperscalers build now related to AI after this cycle?

[Joel Selanikio @jselanikio]

A Columbia ER doc wrote in @nytimes that she typed her own lab results into ChatGPT and got better care than her own doctor gave her — availability, patience, and truly customized diet and exercise steps (not just a generic handout).

Her doctor's response to the labs was "book another appointment to discuss." I have to say I've asked patients many times to do just that. But ChatGPT was available immediately, not in two weeks or a month. It asked about her day, analyzed the ingredients in her vitamin gummies, and came up with a customized plan right away.

For free.

When I talk about tech making healthcare better and smaller, this isn't the better part. It's the smaller part — while patients (even patients that are doctors) getting better care than healthcare can provide.

https://t.co/nhwzwgDpLD
#DigitalHealth #AIinHealthcare #FutureOfMedicine #healthcareAI