Kyle Cooney

Father x3, Airbnb Host x2. Long-Term Rental x1. Software designer. Real Estate, Rivian, Globalization & Multiethnic Democracy Enthusiast.

[Kyle Cooney @kylec]

Neat.

[George Hartley ☄️ @gthartley]

I just sent our launch announcement to 10,000 people.

It took one prompt in Claude.

Today we're launching @nitrosendx - the first email platform with no dashboard.

→ https://t.co/AwAv8mP5KM

[one dozen rats at a keyboard @PanasonicDX4500]

I know it’s become pretty cliche and cringey to talk about at this point but if you’re under like 25 I cannot stress enough how one time Obama wore a tan suit and people spent a week arguing over whether or not it was demeaning to the Oval Office and they were serious about it.

[Kyle Cooney @kylec]

Does anyone use Gemini? I haven't touched it in months.

[Kyle Cooney @kylec]

Getting my permission to operate on my 2nd solar installation this week. Between solar, EV's, and free EV charging around town, figure I'm saving roughly $1500-$2000 a month on utility bills and gas.

[Kyle Cooney @kylec]

Hard agree. Clarity in communication design is where I focus.

[Paul Graham @paulg]

Having high standards for clarity is useful in lots of other kinds of work too. It's very useful when I'm advising startups at Y Combinator. I ask founders what they plan to do. Their initial answer is a muddy pool. Then we make it clear — not just what to say, but what to do.

[Kyle Cooney @kylec]

👀😬💯

[GREG ISENBERG @gregisenberg]

Bookmarking tweets and not going back to them has become an epidemic

[Kyle Cooney @kylec]

Starting to think the best test of AI models is getting companies to align on OKRs.

[Bojan Tunguz @tunguz]

Do you guys remember "Scrum Masters"? What was that all about???

[Kyle Cooney @kylec]

And every Ezra Klein podcast…

[Marc Andreessen 🇺🇸 @pmarca]

I have found it, the Platonic form of every New York Times op-ed.

[Kyle Cooney @kylec]

@robertcourson Literally been trying to build this same concept (harness on your harness). I think I need to start over, Codex didn’t understand my intent first go around.

[Kyle Cooney @kylec]

@devahaz I understand why people want to listen to Rabois, but I still don't get it.

[Kyle Cooney @kylec]

Worth reading, and listening to the pod. Great balance to all the AI fear mongering.

[Lenny Rachitsky @lennysan]

My biggest takeaways from @benedictevans:

1. We’re in 1997 for AI—it’s as big a deal as the internet or mobile, and only as big a deal as the internet or mobile. We’re at the stage where most stuff kind of doesn’t work yet, most of what people will build hasn’t been built, and it’s not clear how any of it will work when it does. Some people in tech have bought clusters of Mac Minis, while even among 13-to-18-year-olds, only about 15% to 20% are daily active users of AI. The companies that win may not exist yet, and the use cases that matter most are probably invisible to us today.

2. Every technology wave brings ways to ruin people’s lives, deliberately or by accident, and we need to be conscious of that without panicking. Every wave of technology—databases in the 1970s, social media in the 2010s, AI today—creates new ways to harm people. We need to be conscious of these risks, build safeguards, and hold people accountable. But we also can’t let fear of potential harms stop us from capturing the benefits. The goal is thoughtful deployment, not paralysis.

3. Things will probably be okay—but “on average” hides a lot of individual pain. We’ve been automating jobs and creating new jobs since 1800. Each time, you can see the jobs that will disappear but not the new jobs, because they don’t exist yet. We go through frictional pain, dislocation, people lose jobs, towns get hollowed out, and it all sucks. But we come through richer, and we’re not worried about crops failing anymore.

4. If you’re worried about your job, the worst thing you can do is stick your head in the sand and declare AI evil. Yes, some professions face major questions, particularly if you’re an associate or would have been thinking about becoming one. The pyramid structure of professional services may fundamentally change. What helps is submerging yourself in AI, understanding what you can do with it, how it changes things, and how you can be a great hire in this new environment. That may still not be enough, but it’s the only path forward.

5. The history of accounting shows us how automation often increases employment rather than decreasing it. Despite adding machines, punch cards, mainframes, databases, ERP systems, cloud software, spreadsheets, and PCs, the number of accountants keeps going up. This is the Jevons paradox: when you make something cheaper or easier, you don’t do the same amount of work for less money. You often do vastly more because the ROI changes.

6. Distribution is becoming a more valuable moat as software gets easier to build, which favors incumbents. As AI makes building software cheaper and faster, the market gets noisier. More products launch, more companies compete for attention, and breaking through becomes harder. This means distribution—the ability to reach customers and get them to use your product—matters more than ever.

7. Foundation AI model companies won’t have lasting pricing power, and value will likely accrue up the stack. The models don’t seem to have network effects, so there’s no winner-takes-all dynamic. If you have indefinite competition between three to six foundation model providers, and the models look like undifferentiated commodities to users, why would anyone have pricing power? The current pricing chaos—people spending $1.5 million on inference in a month—is temporary disequilibrium, like someone getting a $50,000 mobile data bill in 2010. The steady state will look different.

8. OpenAI and Anthropic are buying consultancies and PE firms. This seems counterintuitive—aren’t these the companies that should need consultants least? But the reality is that companies don’t have people sitting around waiting to reimagine all their internal workflows and figure out which could be automated with AI. That’s a project requiring five to 10 people spending months working it out, then actually implementing it across vertical and horizontal systems.

9. The fundamental question isn’t whether AI automates your job—it’s whether your profession is a "task" or a job. Some jobs are just tasks, and when you automate the task, the job disappears (i.e. elevator attendants). But in most professions, the task you think you’re being paid for isn’t actually what you’re being paid for. McKinsey doesn’t get hired to produce a 75-slide deck—they get hired to walk through your enterprise, understand the politics, talk to customers, and figure out what you actually need to do. The deck is just the artifact.

10. The anti-AI backlash is real, and a fuzzy mass of different concerns, some real and some not—much like the social media backlash. There are tangible concerns: electricity bills went up in some places, though this applies to very few locations objectively. The water consumption issue is largely false; data centers use about 0.017% of U.S. water consumption. There are real questions about jobs, though economists can’t yet find clear consensus in the data about AI’s employment impact. There’s also the culture war over AI-generated content and “AI slop.” The challenge is that all of this creates political pressure even when the underlying facts are unclear or contested.

[Suzie rizzio @Suzierizzo1]

Don’t forget when Rome was collapsing emperors would use Gladiator fights to distract the people from the Corruption of the State at that time! This is all starting to make sense now. Who agrees?

[Marc Andreessen 🇺🇸 @pmarca]

I have found it, the Platonic form of every New York Times op-ed.

[Kyle Cooney @kylec]

@sflorimm Claudex.

[Kyle Cooney @kylec]

@Jason @bouchon_bakery My kids are going to grow up knowing it as their local bakery. Kinda nuts.

[Kyle Cooney @kylec]

@stefanoscalia You should try Mexico.

[Kyle Cooney @kylec]

@laurenlself D underrated. Cole Valley, Lower Height, Hayes Valley and Golden Gate Park. I'll take it.

[Kyle Cooney @kylec]

@TheSaaSCFO Gamma has always been AI slop.

[Kyle Cooney @kylec]

👇💯

[Ben Kim @benkimbuilds]

I’m bragging but private chef has been the best allocation of $ ever.

Overnight oats + 2 juices daily, 5 dinners a week, basic meal prep on weekends and cut fruit always.

Shopping, cooking, and cleaning all handled. Service 3x a week.

Cost of food and services averages $500 USD/month.