Sabitlenmiş Tweet
introducing Odysser (again)
we've built lovable for video editing
try it now for free: odysser(dot)com
English
Kaito | 海斗
4.7K posts
Kaito | 海斗
@_kaitodev
🇲🇦 | building the missing piece of video storytelling @joinodysser | prev. @_buildspace | 51.2k on IG | not from @uwaterloo
San Francisco, CA Katılım Şubat 2018
1.7K Takip Edilen7.5K Takipçiler
In 2026, I’m inviting 1,000 founders to San Francisco to start their companies.
Are you in?
English
Going to be Twittermaxxing a bit. Dropping something big today/tomorrow, turn on notifications.
Hint: I’m on video.
English
i really thought i had my playback speed on 2x
David Senra@davidsenra
My conversation with Marc Andreessen (@pmarca), co-founder of @a16z and Netscape. 0:00 Caffeine Heart Scare 0:56 Zero Introspection Mindset 3:24 Psychedelics and Founders 4:54 Motivation Beyond Happiness 7:18 Tech as Progress Engine 10:27 Founders Versus Managers 20:01 HP Intel Founder Legacy 21:32 Why Start the Firm 24:14 Venture Barbell Theory 28:57 JP Morgan Boutique Banking 30:02 Religion Split Wall Street 30:41 Barbell of Banking 31:42 Allen & Company Model 33:16 Planning the VC Firm 33:45 CAA Playbook Lessons 36:49 First Principles vs. Status Quo 39:03 Scaling Venture Capital 40:37 Private Equity and Mad Men 42:52 Valley Shifts to Full Stack 45:59 Meeting Jim Clark 48:53 Founder vs. Manager at SGI 54:20 Recruiting Dinner Story 56:58 Starting the Next Company 57:57 Nintendo Online Gamble 58:33 Building Mosaic Browser 59:45 NSFnet Commercial Ban 1:01:28 Eternal September Shift 1:03:11 Spam and Web Controversy 1:04:49 Mosaic Tech Support Flood 1:07:49 Netscape Business Model 1:09:05 Early Internet Skepticism 1:11:15 Moral Panic Pattern 1:13:08 Bicycle Face Story 1:14:48 Music Panic Examples 1:18:12 Lessons from Jim Clark 1:19:36 Clark Versus Barksdale 1:21:22 Tesla Versus Edison 1:23:00 Edison Digression Setup 1:23:13 AI Forecasting Myths 1:23:43 Edison Phonograph Lesson 1:25:11 Netscape Two Jims 1:29:11 Bottling Innovation 1:31:44 Elon Management Code 1:32:24 IBM Big Gray Cloud 1:37:12 Engineer First Truth 1:38:28 Bottlenecks and Speed 1:42:46 Milli Elon Metric 1:47:20 Starlink Side Project 1:49:10 Closing Includes paid partnerships.
English
Magyar
English
Whoever solves this first will be a millionaire.
Rob Hallam@robj3d3
How is there still not a good vibe video editing software??? If there is, please tell me.
English
vibe video editing is being solved.
watch me 1) remove dead spaces, 2) cut sections based on a prompt I give it, and 3) send it to premiere/davinci to tweak it
Rob Hallam@robj3d3
How is there still not a good vibe video editing software??? If there is, please tell me.
English
@_kaitodev Tbh the problem isn't with just cutting which already a lot of tools like (Davinci Resolve Paid version) and Descript can do..it's the transitionz, effects, overlays, texts, zooms and b-rolls - in short the taste!
English
fayt tla9it deri li mcha viral w elon musk jawbo fi tweet
Kaito | 海斗@_kaitodev
5 minutes ago, @karpathy just dropped karpathy/jobs! he scraped every job in the US economy (342 occupations from BLS), scored each one's AI exposure 0-10 using an LLM, and visualized it as a treemap. if your whole job happens on a screen you're cooked. average score across all jobs is 5.3/10. software devs: 8-9. roofers: 0-1. medical transcriptionists: 10/10 💀 karpathy.ai/jobs
HT
It’s time to build in San Francisco again
Rohin Dhar@rohindhar
WSJ today on the San Francisco real estate market Pretty good summary what’s going on, and it’s not overly complicated: “An uptick in demand coupled with the city’s notorious lack of housing supply means that fierce bidding wars are breaking out again for single-family homes and condominiums in desirable neighborhoods”
English
Andrej Karpathy says roofers and janitors are safest from AI
so the career advice in 2026 is:
→ don't get a CS degree ($100k debt)
→ don't grind leetcode (6 months wasted)
→ don't join FAANG (they'll lay you off)
→ just fix roofs
the most expensive education
leads to the most replaceable job
we do not talk about this enough
English
@ThePrimeagen jobs being optional is plausible. the high income part is where i'd need to see the math
English
high universal income just means universal income which means low income
Elon Musk@elonmusk
@_kaitodev @garrytan @karpathy All jobs will be optional. There will be universal high income.
English
My boy @_kaitodev just making my weekend even more peaceful 🧘🏽♂️
TLDR: Train li drebna derbo train 😂
Kaito | 海斗@_kaitodev
5 minutes ago, @karpathy just dropped karpathy/jobs! he scraped every job in the US economy (342 occupations from BLS), scored each one's AI exposure 0-10 using an LLM, and visualized it as a treemap. if your whole job happens on a screen you're cooked. average score across all jobs is 5.3/10. software devs: 8-9. roofers: 0-1. medical transcriptionists: 10/10 💀 karpathy.ai/jobs
English
thank you 🙏 the people’s reaction was overblown and completely justified at the same time
honestly the data itself is still the most interesting part to me. even if the scoring methodology is somehow rough, the pattern it reveals ( that exposure tracks almost perfectly with “can you do this from a laptop” ) is a real insight worth checking out
ppl weren’t panicking about the data but more about what the data actually confirmed.
English
This was a saturday morning 2 hour vibe coded project inspired by a book I’m reading. I thought the code/data might be helpful to others to explore the BLS dataset visually, or color it in different ways or with different prompts or add their own visualizations. It’s been wildly misinterpreted (which I should have anticipated even despite the readme docs) so I took it down.
English
5 minutes ago, @karpathy just dropped karpathy/jobs!
he scraped every job in the US economy (342 occupations from BLS), scored each one's AI exposure 0-10 using an LLM, and visualized it as a treemap.
if your whole job happens on a screen you're cooked.
average score across all jobs is 5.3/10.
software devs: 8-9.
roofers: 0-1.
medical transcriptionists: 10/10 💀
karpathy.ai/jobs
English
Karpathy scored every job in America on AI replacement risk. Then he deleted it.
It went viral Last night. Elon replied. News outlets picked it up. So I brought it back to life.
Cloned the entire repo to play with before it went down. Every file. The scoring data, the full pipeline, the interactive visualization. All of it.
It's back up here: github.com/JoshKale/jobs
The data was too noteworthy to let vanish. 342 occupations scored 0-10 on how much AI will reshape them. Average exposure across the entire US economy: 5.3/10.
If your job lives on a screen, it's worth taking a look.
English