_cjk

@PaulSkallas Or at least that’s their bet Possibly a terminally brand fucking bet. But only if battery tech doesn’t advance, which it will. And then we get a renaissance in car design

@PaulSkallas Savage I’d go further People don’t buy Ferrari for comfort and safety, that’s Volvo They buy status EV is virtue Virtue has more status than beauty

Let me try to defend Ferrari here. Cars aren't cool anymore. Most people don’t dream about sports cars anymore. They want SUVs or trucks with comfort and safety. Ferrari was built for a world where cars were emotional objects. That's all gone. This car is the non-alcoholic beer of cars. And a lot of people have quit drinking alcohol.

@prompterminal Great explanation, I get it now. But it’s fucked innit. Beauty cannot require explaining. Unless enuf just want the name + the virtue. The lines are just off. Not sexy. Wonder if anyone can get the correct angles within the constraints, or it’s simply impossible

The Ferrari Luce looks like a sedan because an EV battery pack is very heavy. The floor has to be thick with 15 to 25 cm of battery cells which means the entire passenger cabin gets pushed upward. You can’t have a low, flat, swooping roofline like a traditional Ferrari because your passengers are sitting higher up. The car has to be taller to fit people above the battery. A taller cabin means a larger frontal area means more drag. Which means there is a tradeoff between energy density per volume (high) and aerodynamic silhouette (large) 😥

“using AI forecloses insights that can set your text apart” Where can I get a ‘Not Thinking’ cap

@justalexoki I like this. Reminder to talk to my father even if I’ve got a plausible answer. Reckon dad answers will always be better. Thank you for posting

i have been asking chatgpt a lot of questions i now realize i otherwise would've asked my father. which.. doesn't feel great. and will probably affect society more than we know

@QiaochuYuan Sensational. Perfect skewering. Also an example of what AI cannot imitate. In style in content in humour. Wonderfully un-shareable in polite company.

sam kriss on AI writing, self-recommending samkriss.substack.com/p/if-you-let-a…

@jmrphy This is nit-picking. I get a lot out of AI, so he'd pickaxe me given the chance. But the whole piece perfectly skewers AI writing

I like Sam Kriss but he's totally out of his depth on tech. Fun guy, but out of touch and makes major, critical errors. These sorts of hallucinations are completely solved with the latest models. You can hardly stump them if you try (GPT 5.5 Pro).

Sun’s out Bentley’s Gonna Sort You Out

Typoslop

@jmj Openclaw a counter example, or exception that proves the rule? Kinda saying there’s no way to build without $$$ for big promo, because alternative was cult building in public. Don’t know if I agree. Something different about originator vs imitator energy

Building in Public was the playbook. Not anymore. If you're a founder, don't give competitors a sniff of what you're working on until you're ready for showtime. No benefit anymore to building in public. People are too busy to care what you're doing & they'll happily copy you.

@damian_b always was

“Taste is the new moat.” What does this even mean? I have 13 years of engineering experience, so I will attempt to qualify what taste means from my perspective. Despite being skilled (aka cracked) at engineering, I am not omnipotent. I do not know every detail of every technology. What I do have is these 13 years of (human) RL fine-tuning on what is a good engineering decision and what is not. This has imbued me with a 6th sense of sorts to identify what is a reasonable design. Note the word "reasonable", not perfect, not optimal, but reasonable. Engineering is all about tradeoffs and more often than not, reasonable is what wins. When the LLM presents a plan or an implementation, I can very quickly understand if this approach is reasonable or not. And if it is not, I iterate. I am also quite confident that this reasonable radar applies to more than just software engineering. I would bet that a lot of science is built on top of reasonable assumptions. I would bet design teams lead with reasonable patterns. Economists probably also incorporate reasonable signals in to their models. So no, I do not think "taste" is the new moat. The real moat is in the art of being reasonable.

@p_millerd Humanist twist on Parkinson’s Law

not enough people are taking seriously the very realistic scenario that we just keep creating jobs because we love jobs jobs should be modeled more of a collective desire than a economic truth at this point

@willsolfiac This. But think open question is, will people be interested in the writing of specific AIs / AI character actors. I suspect they might be. But I also suspect we underestimate the depth of weird context a human writer brings vs LLM context windows

I think, sadly, it's correct that ChatGPT-slop voice is mostly because it's been trained to talk like that. It's a mass market product after all. The way Claude talks, for example, is still annoying, but it's not the same kind of slop, and I fully expect that a model trained to sound like good writing could achieve this. However I also think that, much like chess, people are interested in writing because it's the view of a particular person, even if an AI can do it just as well or better.

@staysaasy @SethCronin Innit, paradox of our time

@SethCronin If it makes people build way faster then the product doesn’t even have to be AI based, it should just benefit from being built faster. Weird we haven’t seen that.

Reminder that we’ve spent basically all human capital and attention on AI the last two years and there still isn’t a single cool consumer product to come out of it.

@thorstenball As a millennial I think they do. But the kids? Maybe only millennial-boomer coded. But… does it have to be smug, it is what it is

Do people still say "dead trees" to smugly refer to paper?

@Steve_Yegge @techgirl1908 The problem: do the people want to play

Brendan Hopper, Matt Beane and I have a thesis, one that I've been sharing around lately, and we want CEOs and boards to hear it. Before I get to the thesis, let's revisit Clayton Christensen's Innovator's Dilemma (ID), the theory he developed at HBS to explain why big companies often get eaten by upstarts during technology shifts. In short, the ID says incumbents serve their best customers so well, and tune themselves so ruthlessly for doing exactly what they do today, that they can't chase the disruptor tech coming up from below until it's too late. The classic solution to the Innovator's Dilemma is to create a "bubble" in your company. You carve out an innovation team with a budget and mandate, as unfettered as practical by the parent organization. This is to combat the 2-level trap presented by the dilemma. The economic trap is Christensen's original point: a disruptive technology can't justify itself under your existing P&L, because it serves smaller or weirder customers at margins your real business would never accept. The governance trap is what gets piled on top once you're big: SOC2, FedRAMP, etc. mean every new idea has to clear a lot of process before it can move. The bubble is intended to escape both at once, with its own economics and permission slips. The standard innovation "bubble" solution famously doesn't work very well. You may solve the problem inside your bubble, but you often can't roll it out to the rest of your company for the original reasons. Everyone is focused on doing their current stuff, and nobody has time for a major change. Our thesis is that there is an entirely different way out of the dilemma this time around. No bubble needed, as long as you follow a simple rule. That rule is, let your people play. Give them back any time they earn from automating their jobs with AI. Then incentivize them to use that time to improve the company's processes. When you see an engineering team announce a 40% productivity boost from adopting AI — a number that's been showing up in plenty of LinkedIn posts lately — your first reaction as a CEO or manager is probably to say, that's awesome, we can do more work now! Or you might simply expect to see 40% more output from the team. Either way, you have just asked them to spend their extra time building faster horses (your current business) instead of letting them go figure out what a car would look like for your company. They gained some productivity from AI, which could have been your ticket out of the Dilemma, and you immediately slurped it back for your existing business. This will get your company killed in the medium to long haul, because your company tomorrow will look almost nothing like it does today. Conway's Law says your software and your org chart mirror each other; as AI rewrites how you build software, the org has to shift to match. But if you're stealing the hours back saved by your employees, then you're not letting your org pivot naturally in the direction it needs to shift. @RealGeneKim and I saw this in person at @arkanalabs a few weeks back. As long as your people know they'll be recognized and rewarded if they improve the company's processes — public credit for cross-team workflow wins, promotion criteria that actually count process improvements, managers who treat freed-up hours as a feature rather than a budget line — then they will use their "play time" to seek out other teams, and start pivoting you to becoming AI-native. This way it can unfold in whatever bespoke way is most natural to your company, rather than in some ivory-tower research bubble. For every company, the way it unfolds will be a bit different. I think of this approach, of giving the time back to the humans who automate parts of their jobs with AI, as the new solution to the Innovator's Dilemma. The old bubble solution was to separate a bunch of people from their regular jobs, and try to give them the freedom to solve the problem in isolation. In contrast, by giving your regular employees their hours back, the innovation bubble is still there, but it's now dispersed across the company, as lots of very tiny bubbles: one bubble per person who has liberated some hours. If you've ever read Slack by DeMarco and Lister, a great book from back in the 90s, then our thesis should resonate. What companies need is to empower their own employees, the ones who actually work together (even across departments)--the ones who know how the business works--to shift the company in the new directions together. Gradually, but with intentionality. You still have the frankly awful problem of token budgets. For every employee you upskill into baseline AI literacy (which I'd define loosely as using coding agents throughout the workday), you've added a non-trivial opex spend — for the heaviest agentic users it can run into five figures a year. I won't sugar-coat it; you need to find that money somehow. I don't have a magic solution, but I'm very happy that other models are catching up to Claude, because they're becoming good enough for real work now. But token budgets alone aren't enough. To live through the Innovator's Dilemma this time around, your employees need a time budget, too. Give it to the ones who earn it using AI, then incentivize them properly, and I think you're headed in roughly the right direction. Thank you for coming to my TED tweet.

@nateberkopec With you about X != Y. Think it’s mindfucking our generation. Everything around me is ruled by it’s not this it’s that. But— I like em dashes. Using em outside of slop is a ‘26 idgaf flex

I'm so sick of reading em dashes and "it's not x, it's y." I'm so sick of it, man.

@zeeg Hahaha cold

Software Engineers

@lennysan Stone mason

Question on my mind right now: What role is least impacted by AI (so far)?