Joined July 2022
Probably the most resilient and truly decentralized communities out there right now. Survived multiple vamps, macro shitting itself and liquidity suck from the dumbass “flying” car (that is not actually considered flight btw). People pumping out endless content for the love of the meme. We are all $swordcat.
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Looks like the daily farming of knightcat holders is almost complete 🥀 We are all solana:5tCju6YNxHq5zrA6tGndr6F7TK42mpUFmeE31cSFpump
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Knightcat holders getting farmed for the 9999th time 🥀 We are all $swordcat.
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Knightcat homosexuals in complete disbelief. We are all swordcat.
NEW: cat wif sword pairs are now live on @Pumpfun Pair new tokens with $swordcat. Toggle Holder Rewards for holders to receive $swordcat.
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Read this and try to understand what they’re building over at $STONKS
Management is pleased to report that $ASH and solana:Ga5ErptAQ5oHwB7G195UEq9FeJ5UNDoV9SCRCpebFeG7 rewards are now live on stonksonstonk.com/research/r… Unc $ASH has been onboarded and going through new hire training. solana:Ga5ErptAQ5oHwB7G195UEq9FeJ5UNDoV9SCRCpebFeG7, despite being ████████, has also been reconstructed. What management originally intended to build: A simple way to show how much solana:6GmAFSYs4gk3FDao5FzzySQpPZaWsa4rUJHacpMpUNgx people received What management has apparently built instead: - on-chain reward attribution - historical holder reconstruction - project-level indexing - canonical reward histories - rewards rankings + analytics - a Research Department that is becoming increasingly difficult to explain to accounting A few important distinctions: - indexing does not automatically mean a project will be surfaced on the public board - “we can reconstruct this correctly” and “we should display this publicly” are separate decisions - the objective is not maximum coverage at any cost - the objective is to build the machinery to index more things correctly What comes next: - automate project onboarding + indexing - expand coverage across additional reward universes - keep improving the rewards board + analytics layer - build canonical on-chain market history - get rewards, market history and the simulator operating from the same underlying source of truth That last part is important, because there’s a broader reason management thinks this data could become useful. Over the last few weeks we’ve watched a strange new market structure start appearing across @solana, @BNBCHAIN, @RobinhoodCrypto and elsewhere: - memes paired directly with tokenized stocks - memes paired with pre-IPO / private-market assets - tokens paired against commodities and other RWAs - increasingly creative combinations of speculative assets and real-world denominators - anything paired with anything (cc. @LaunchOnSF) This may all disappear in three weeks. Crypto has form here. But if the structure persists, the interesting questions get a lot more complicated than looking at a chart and asking whether number went up. You start wanting to know: - did the meme outperform, or did its quote asset? - how much return actually came from price vs rewards? - what happens when the underlying asset moves while the meme stays flat? - how do different pair structures affect volatility and holder outcomes? - which reward structures actually retain holders? - do liquidity, concentration, reward flows or underlying-asset moves contain any useful signal? That’s where the pieces start fitting together: - indexing + attribution → who held what and where the rewards went - canonical market data → what both sides of the pair were actually doing - simulator → what the holder experience would have looked like - normalized historical dataset → compare projects, pair structures and eventually chains on a consistent basis - statistical / ML research → test whether any of those variables contain repeatable signal The simulator is a big part of where this is going. Indicatively: - choose a historical entry point - choose a holding period - see price return - add the rewards actually distributed over that period - compare different entry points / projects / pair structures - eventually incorporate liquidity, changing reward regimes and broader market conditions The aim is to move it from a calculator into something closer to a research surface for understanding how these markets actually behave over time. Management has elected to collect clean data before training a model on garbage, despite considerable industry precedent to the contrary. If RWA-paired memes are a three-week fad, management will have built an unnecessarily sophisticated historical record of it. If they aren’t, the dataset gets a lot more interesting. Management remains uncertain when the meme coin became an analytics department, but the work continues.
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People still think $STONKS is just a meme
1/ Management has been informed that some stonkholders are visual learners. Management has also been informed that some of you have not yet entered the Research Department. A brief orientation follows.
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Again you’re all sleeping on the content $STONKS produces. Violent repricing imminent.
Stonkholders, After a busy few days with IT, the Chairman is finally back at the editorial desk. A transaction is easy to observe. Proving what it means is not. Brief 010 explains why rewards attribution requires more than a transfer—and what a project, pair, wallet and cycle record makes possible. stonksonstonk.com/letters/a-…
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People sleeping on the $STONKS content. Read the threads and the articles and you might actually learn something.
1/ Management reviewed this week’s market action and arrived at a less convenient explanation than volatility. bitcoin:native , gold, long-dated Treasuries and AI infrastructure are all asking the same question: What actually supports the promise? Chairman’s Letter 006 · 23 Aug 2026. 🧵
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$STONKS Actually really cool tech. First wallet level rewards tracking for $STONK launches I believe.
Stonkholders, The Stonks on Stonk Research Department rewards board is now live. We’ve indexed historical $STONK rewards across the @LaunchOnSF ecosystem and built a project-level attribution layer showing which wallets received rewards, how much was attributed, payout history, coverage, methodology and current index health. You can also generate Research Department scorecards at both the token and wallet level — giving projects and individual wallets a clean, shareable snapshot of their reward history and position in the indexed ecosystem. Under the hood, this required combining StonkFun’s first-party APIs, @solana on-chain data, @Raydium market/pool data, and external ecosystem datasets including @dexscreener and @DefiLlama into one reproducible attribution pipeline. We’re starting with a small set of projects while the system soaks in production, beginning with $STONKS and $STONKDEX given they are both paired with $STONK. This is the beginning, not the finished product. Next comes broader StonkFun ecosystem coverage, more indexed projects, deeper wallet/project analytics, and additional Research Department tools built on the same underlying data platform. Management has determined that “number go up” is improved by an audit trail. stonksonstonk.com/research/r…
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Gogolollerskates retweeted
I will be sacrificing the lobster shortly to divinely protect and bless the triple platinum cat coin supercycle lock in
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inverse cramer gonna save our bags once again 🙏
JUST IN: Jim Cramer has said he's reportedly selling all his Bitcoin, per CoinDesk
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my brother in christ his shitty car almost killed you xitter.cf/solidwillity/status/20…
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lol $6/m output. it is well and truly over for american labs xitter.cf/alibaba_qwen/status/20…
📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: - Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub:github.com/qwen-code-dev-bot… - Real work, real results: Production-quality deliverables across hundreds of professions. - Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. - Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max! 🚀 📖 Blog: qwen.ai/blog?id=qwen3.8 ✅ Qwen Studio: chat.qwen.ai/?models=qwen3.8… ⚡ API: qwencloud.com/models/qwen3.8…
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this is basically insider access sold as a subscription - where are the drain the swamp folks now? xitter.cf/KobeissiLetter/status/…
BREAKING: Trump Media has officially launched its new paid data service, providing faster access to Truth Social posts from President Trump. The new service is called "Truth API" which gives firms "a direct, licensed, real-time feed of the platform’s most market-moving Truths," the company's CEO said in a press release. The service reportedly costs as much as $100,000/month.
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Gogolollerskates retweeted
Peezy Gateway is now #1 in General Chat on OpenRouter, and #11 globally. Also ranked #2 in Programming App, #3 in Productivity, #3 in Personal Agents, and #8 in Coding Agents. We're processing 2–3 billion tokens per hour and growing, with infrastructure holding strong. We're proud of this milestone. gateway.p0.systems
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Gogolollerskates retweeted
Seeing Qs on converting free to paying users. Already doing it: higher-tier models like 5.1 paywalled to ease transition. Subsidizing w/ 20-40% off. Seeing F2P switches. Paying users at 100M tokens/hr & growing!
We are dealing with a sudden influx of extreme load on the P0 Gateway. We are currently processing over 500 million tokens an hour and climbing fast. We are upgrading our infrastructure to handle this new demand.
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Gogolollerskates retweeted
do you believe in witchcraft ?
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Gogolollerskates retweeted
Lorb Update As most of you know by now the lorb is here and he’s doing really well adjusting to his new home. The issue with lobsters is they’re nocturnal meaning they do most of their cool shit when the lights are off/ low. The lights I have now are just too bright for him so I have ordered a new set that will have blue light for day time streams and a red light for night time streams (lobsters are unable to see the color red lol isn’t that funny) Going to hold off on getting the livestream back on till tomorrow night when I can install the lights / water clarity should be back to normal after adding the lorb, which will line up perfectly with his feeding schedule. We will do a lorb feeding (i’m thinking shrimp this time) and we’ll do some more interactive stuff. Tik Tok videos are being edited as we speak and will begin pushing content/ live streaming on TT as well as X and Pumpfun. Merch is next up followed by IRL Lorb campaigns / giveaways and weekly services. Reply below with any other ideas or things you think would be cool for the lorb or project as a whole!
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