Fin

@gumsays Did this last month with Fartcoin 😅.

So many people are still stuck in the horrible habit of trying to find what will pump next instead of bidding what literally everyone is looking at but isn't deploying because they want to bid what will pump next It's a never ending loop that ends with you bidding the absolute generational top because you couldn't do it before

@inversebrah Almost on par with the Zerocovid crowd

banger

@Pivot922 Fuk it we ball

What if? ethereum:0x232ce3bd40fcd6f80f3d55a522d03f25df784ee2

@Trade_IV Which tg?

if u aren’t in the tg idk what ur doing

@simpelyfe If dont have a therapist, then start there for mental health. Ensure you physical health is there as well. Small changes will compound.

I'm not happy. Has nothing to do with the current state of crypto; it has to do with getting in my own head, and not knowing if this repeating pattern of alienating the people closest to me has to do with my bipolar/schizo, some internal character flaw, or not being understood. I really don't know, which is strange because I'm very intimate with my characteristic mentalities, but I'm out of touch with human connection. I'd like to think I'm a great problem solver, so for the sake of character building, please tell me when I can do better.

@61Ape_ @Leveraged_Labs Oh man, my condolences sir.

Much love to the @Leveraged_Labs squad. All of your messages are very appreciated. Losing mom is tough, the baton is passed on. I am beyond grateful I was able to be there for her last moments.

@doppel_ichi Heavenly gaze

you'll look back in decade and realize how good of an opportunity space frontier investing was.

@simpelyfe weird gut feeling about shorting 73.

GM. Don't try to force a trade today. Burgers took an early weekend. You can see that the SLS monitor is is repetitive and not stochastic whatsoever.

@moneyfetishist Holy shit on understanding the ai game clearly for the first time. I don’t qualify but this will require a reread.

@moneyfetishist Recently completed this analysis within our company. Salesforce alone accounted for 30% waste and found handfull of other Saas platforms that were aquired to support SF... Regardless, the real questions is how do I get in front of said CFO?

low hanging fruit series. post 2 of 7 the average enterprise wastes $21M a year on unused SaaS licenses. this is not my number. this is Zylo's 2025 SaaS Management Index. more than half of all purchased licenses across enterprise companies go completely unused a VP buys a tool. the VP leaves 8 months later. the team gets reorganized. the new manager uses something else. the old license auto-renews on a corporate card that nobody reviews because it is buried in a P&L line item called "software and subscriptions" that finance looks at once a quarter in aggregate and never at the individual tool level. multiply that by 200 tools across 5,000 employees and you are lighting millions on fire annually and the smoke is invisible because it shows up as "operating expense" and nobody breaks it down the play is so simple it is almost insulting. you connect to a company's SSO provider. Okta, Azure AD, Google Workspace. you pull login activity for every SaaS application. you generate a report showing which licenses have not been accessed in 30, 60, 90 days. who holds them. what they cost. total annual waste. the entire technical complexity of this business is an API integration and a PDF you walk into a CFO's office and say I will audit your SaaS spend for free and if I find less than $500k in waste you owe me nothing. no CFO on earth says no to that because the downside is literally zero and the upside is a documented cost reduction they can present at the next board meeting as something they proactively identified. you are handing them a win for free you will find waste. you always find waste. a mid-market company with 1,000-5,000 employees will typically show $1-3M in identifiable waste. you take 20% of first year documented savings. that is a $400k engagement from reading login timestamps but here is where it stops being a consulting gig and starts being a real business after you audit 50 companies you have the most comprehensive dataset on enterprise SaaS usage patterns that exists outside of Okta itself. you know which tools get abandoned fastest. you know the average active lifespan of every major B2B product by company size, industry, and department. you know which categories have the highest shelfware rates. after 200 companies you can predict what a new client is wasting money on before you run the audit based on their industry and tech stack. the audit gets faster and more accurate with every engagement. the data compounds and then the second business opens up inside the first one. SaaS vendors will pay you six figures for anonymized churn prediction intelligence. "companies in financial services with 500-1,000 employees have a 67% probability of abandoning your product within 9 months." that data is worth more to their retention team than any customer success initiative they have ever run. PE firms evaluating SaaS acquisitions will pay $50-100k per deal for your usage benchmarks. a target company claims 10,000 enterprise seats? your data tells them how many of those seats are actually active across your client base. that due diligence layer does not exist anywhere else I would move on this deal structure faster than almost anything I see come across my desk because the initial engagement model eliminates the most expensive part of enterprise sales entirely. the risk objection. "free audit, pay on savings" compresses the sales cycle from months to weeks. the close rate on a zero-downside value-share proposal to a CFO is absurdly high which means capital-efficient customer acquisition which is the single metric that separates businesses that scale from businesses that stall the transition from project revenue to $5-10k/month ongoing monitoring is where the valuation changes. PE will not pay platform multiples for services. but a company that enters through services and converts to recurring monitoring with 90%+ retention is a platform. that conversion changes the exit multiple from 2x revenue to 12x overnight and the competitive moat is the dataset. someone can build the audit tool in a weekend. they cannot build the cross-company usage intelligence without auditing 200+ enterprises over 2-3 years. by the time they get there you have 500 and the gap has widened. the moat deepens with every client you sign

@Pivot922 Appreciate the transparency, you’ll make it all back after the mid terms. I think we chop till then.

Rough Q1 for me, March cooked me in the final days Not down a significant amount tbf since I sized down dramatically to start the year This is perp book stats only I share when I am doing great, I think it would be dishonest to not share when I am also in a trading slump Only 41 trades on the year so far I have said it several times in GC over the years When we are in a ranging chop environment, I am not the person you want to look to for an opinion on markets Give me vol, give me some sort of direction and I will cook 90% of this timeline on performance GGWP to the bro's who walked out this quarter with a positive perp book PNL

@Pivot922 Brother once in a while its okay to admit our king is being a fucking retard.

Just yesterday they claimed donny was telling fibs And accounts on here really agreed and believed Iran state backed media Some of these TDS accounts and bears would have believed nazi propaganda before Trump I dont take 99% of this tl seriously Buncha parots Fwiw, half of what donny says is to cause confusion and disarray His comments are not for you anon You hold zero importance on the world stage to be spoken to

@gumsays well said. Too much incel energy out here

Men need to stop monitoring every situation. It genuinely consumes your brain and removes leftover energy to think about what matters: making money. You criticize women for caring about what color Taylor Swift's new t-shirt is but you do the same shit with wars, what some random KOL said, what trade was made by person Y, etc. The internet will only get worse if you can't voluntarily withdraw from all the noise

How are my little moon boys doing today!

@simpelyfe All that for just one elon comment. Jeez

If I liked your tweet just now, private beta for you. This is crazy... if you don't follow me, A LOT of tweets are missing + missing from the search. It's cause I made that Elon comment. YOUR FRIENDS DIDN'T FAIL YOU ELON! :D...

@Pivot922 we back

I think its time to become a bull again I have seen enough

@fuckyourputs Similar to zerocovid Reddit crew 😂

@Pivot922 bobo karma is real, I still enjoyed the collection, more to come at some point lol ?

I hope me being bearish and taking perp positions and selling some of my holdings doesn't confuse you If you do not see during this bear market that $HYPE Will be the biggest crypto asset besides BTC than idn man I think when we enter a bull market HYPE vamps the rest of the market There is zero justification to own any of the other coins HYPE is its own beast that no one can match, it is being tested during some crazy volatile times and is proving itself That view has never changed for me, does not mean it wont be a bumpy ride to 260 Never get my bear post confused with my overall thesis on hype Investing and trading are two different things And me wanting some cash is just to help me sleep at night, being a degenerate with zero conscious is not my style Some of us have responsibilities besides just our own lives

@karpathy @kristoph

@kristoph definitely. the current one is already 90% AI written I ain't writing all that

I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autor… Part code, part sci-fi, and a pinch of psychosis :)