An is a monkey

Starting a podcast where I interview some really cool young people (<26) ‼️ Looking for people who found success their own way to 1) inspire and be the example I needed as a kid 2) share the tactics and third doors we took to get here & 3) enable weirder, bolder career paths

I think I am more interested in the individual / micro level of agency/leverage accumulation gdp will go up with ai sure maybe, but what does a person ascending this ladder feel?

$ value created per human hour I guess

AI will increase our leverage 10-100x, but is there currently a good way to measure that? Elon has trillions in leverage, a shift manager has leverage, and a barista with a coffee grinder has leverage, too Is there a standard measure as we ascend these layers of leverage?

@BexelInitiative productivity + tfp is too broad! What do you think a good measure is here?

@andotvu ? please go read some economics myfriend.

And the full code repo with all the BLS scraping, llm scoring prompts, data, and visualization is here: github.com/chrona-nyc/jobs

The full dashboard is here: jobs.chrona.nyc

Andrey Karpathy scored every job in America on AI replacement risk from 0-10. Then he deleted it. But I thought it was useful so I reuploaded it and added to it: > Scrapes all 342 occupations (over 143 million jobs) from US Bureau of Labor > Scores each job (0-10) with a rubric based on how digitally native the work is + how easily AI can do it > Over 32M workers + $2.4T in US wages are at high risk (jobs in the dashboard that scored 7+) Software devs - 8-9 Construction + electricians - 1 Nurses + retail - 4-5 Medical transcriptionists - 10 Red jobs are more at risk. If your job is on the screen, worth taking a look. Doesn't look great if your job is entirely behind a screen. I added some stuff to help you explore the data better: → a search bar (type your job, see your AI replacement risk score) → alternate career paths for high risk roles in the economy (based on transferrable skills + background) → AI risk tier filter to see all high/medium risk sectors → found 42 AI-resilient careers in the data that are both high growth + low AI exposure → had Claude score every job (who I trust more for economics research vs Gemini) → role-specific tips on how to use AI in your field to get/stay ahead the original one showed you the problem, tried to make this one a bit more helpful (and pretty!)

this is actually insane > be tech guy in australia > adopt cancer riddled rescue dog, months to live > not_going_to_give_you_up.mp4 > pay $3,000 to sequence her tumor DNA > feed it to ChatGPT and AlphaFold > zero background in biology > identify mutated proteins, match them to drug targets > design a custom mRNA cancer vaccine from scratch > genomics professor is “gobsmacked” that some puppy lover did this on his own > need ethics approval to administer it > red tape takes longer than designing the vaccine > 3 months, finally approved > drive 10 hours to get rosie her first injection > tumor halves > coat gets glossy again > dog is alive and happy > professor: “if we can do this for a dog, why aren’t we rolling this out to humans?” one man with a chatbot, and $3,000 just outperformed the entire pharmaceutical discovery pipeline. we are going to cure so many diseases. I dont think people realize how good things are going to get

A good measure of a full life is the amount of shared albums you have

@brianshinsh Do what makes you come alive !

having fun is the single largest moat you have as a founder so stop fussing over market size, tech stack, and whatever jargon midwits say is important just build what you can really care about

hehe making a mantras app that forces me to read my morning mantras and watch my favorite pieces of content, like feeding my mind veggies in the morning

For design, give it the best screenshots of designs you like For writing, paste in your favorite substack articles For research taste, point it at well reviewed meta analyses with high effect sizes

Prompt engineering is steering the model toward the most expensive parts of the training distribution: - research we've spent decades learning - aesthetics we've spent years designing - language the masters have spent their lives perfecting make sure it samples from greatness

@HcwXd @WonderingApp This is great!!! Amazing work!

I left NotebookLM a few months ago to solve a bigger problem in learning. Today, as the first step, we are launching @WonderingApp for early access. It's Duolingo for anything — turning any topic into a guided path with bite-size visual lessons that can fit into your busy schedule. But you don't sacrifice depth/effectiveness for convenience: Total Control: You decide how deep you want to go, how difficult the material should be, and how personalized the experience feels. Active Learning: We provide the tools you need to practice, test your understanding, and actually apply what you’ve learned. Long-term Mastery: It’s built to help you truly remember and master any subject, not just skim the surface.

PKM tools will come back because: - context is the gasoline of AI - notes now have practical value - being smart is cool again - text can now shape shift into photo, video, audio - your mind now has 100x the value: to run agents, complete work, and know more

AI has recursive self improvement and we have college lmao

algorithmic feeds are the first at-scale misaligned AIs

the goal of creation is more creation the reward for good work is more work a good idea allows more good ideas to come into the world goodness compounds and is often created in the last 20%, not the 80

technologies, buildings, products, communities all embody a set of values when done right, your work should convince people to see the world how you do you make things to help the world understand you better