55,700 stars and the hardest marketing skill is still getting the founder to approve the copy
the founder of Conversion Factory just open sourced his entire marketing brain as Claude Code skills. 55,700 stars.
install it and tell Claude what you need done.
43 skills. one repo.
it covers:
→ CRO, landing pages, signups, paywalls, onboarding flows
→ copywriting, copy editing, cold email, lifecycle email
→ SEO, AI search optimization, programmatic SEO
→ paid ads, pricing, referrals, churn prevention, launches
→ influencer marketing and co-marketing strategies
skills cross-reference each other, your product marketing context feeds every other skill automatically.
works with Claude Code, Codex, Cursor, and Windsurf.
if you sell marketing services or run client campaigns, install this first.
github.com/coreyhaines31/mar…
someone on openai's content team said the tesla stunt gave no reason to buy. i pushed back: the future is the reason
Took me 2.5 minutes to think and write. Did nice numbers on LI ++ her followers are my icp
cheapest distribution online is a good comment under the right post
the reason content is so hard to hit consistently is that the audience is people, and people are fucking insane
if you haven't already, make a detailed post about your first paying customer
>who they are (industry, or the name if you're allowed to say it)
>the problem they had before you
>what you actually helped with
>the tangible results
guaranteed to attract multiple leads
learned this week that in SF, "what are you building?" is the equivalent of saying hi in the rest of the world
despite being a top dog at Meta he knows X is superior 🤣
after an exciting week of launches (muse wonder [full] & muse spark open), i want to write a note of appreciation to the amazing research teams at meta superintelligence labs on reaching such a special milestone ♥️
we started MSL and TBD a little more than a year ago and set a goal of producing a frontier model within a year or so. given where llama4 landed, that was an incredibly audacious goal, and we knew it wouldn't be easy. many people told us it would be impossible. we knew it was unlikely, but still worth doing. a remarkable group of researchers and engineers joined the effort from inside and outside meta. every single person came in, picked up a shovel, and got to work with earnestness and urgency. nobody asked whose job it was.
we assembled a team of the most brilliant people i have ever had the opportunity to work with (and remember, i was an HRT intern 🙃). i am surrounded by ambitious, visionary, technically excellent, hard-working, pragmatic, thoughtful scientists, engineers, and product folks—people who will chase a weird loss spike past midnight just because they need to know why. these models are the product of their passion, hard work, and brilliance.
somewhat paradoxically, when we started TBD, we set a principle of no deadlines. we knew we had an astronomical amount of work ahead of us—across pretraining, post-training, RL, multimodal, infrastructure, safety, data, AND frontier research. there was no use setting arbitrary timelines—we just had to get to work, be thoughtful, and build the foundations of a frontier research effort in record time. and run after run, this team did exactly that.
our researchers are magicians. i can only describe building these models with this team as a wondrous journey of scientific discovery. i am constantly amazed by what we can accomplish with scaling. i will remember this past year for the rest of my life—the late nights, the broken runs, the evals that came back better than any of us dared to hope. watching this team create wonder after wonder has been a true and deep gift.
more than just the models we released this week, we have built a machine that builds new models. it often sounds like a cop-out to say labs can just turn the crank to keep scaling, but now i have seen it first-hand. sure, it's a lot of work and a careful process, but we have built a scalable system to keep advancing at the frontier, and i am really proud of how fast this team keeps making these models better.
lastly, i get to work with researchers who care deeply about how their work benefits humanity. it's easy to forget when everything is changing so fast, but the whole damn point is to make people's lives better. time and time again, i have seen our researchers, engineers, and product folks build our technology with care so it can truly be good for the world—whether that's building the best models for muse, thoughtfully open-sourcing strong models, or making sure the alignment and security of our systems are rock solid. this is a team of people who never forget there's a real person on the other side of every prompt.
thank you to everyone at MSL for being part of this crazy journey over the past year. i'm so grateful for every one of you, and our work is not done!
Jensen would’ve made an excellent officiant
Chinese bride gifts her partner a flagship GPU at wedding — he breaks down in tears
She handed him an ASUS ROG Astral RTX 5090 that costs around $12,000
eighth grade: “you have to go to college”
high school: “you have to go to college”
in college: “why are you still in college, just drop out”
after graduating: “why did you even go to college”
If founders focused more on pissing people off on X than on providing genuine value in their content, they'd be much more successful
A full crew of humanoids hopping out of a dates Honda Odyssey school drop-off style is such a mindfuck
You can now book our humanoid cleaning service in Los Angeles at tau-robotics.com. If you don’t have an invite code yet, join the waitlist.
Watch our humanoids cleaning customers’ homes in the thread below.
Who can spot the hidden pint of Guinness?
Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.
Wu-tang alex Wang and Llama Drama Zuck becoming the new Washington and Lincoln
No one’s created a Tinder for strictly SF nerds to solve this problem ???
OPENAI to EMPLOYEES: If someone is trying to seduce you, first consider — could they be a spy???
OpenAI is warning its employees about honeypot spies and strangers with children in playgrounds ... a very fun one with @georgia_wells and @MeghanBobrowsky:
wsj.com/tech/ai/ai-companies…


















