there are demons on the 1 minute chart trying to convince you that the $BTC chart is somehow bearish stop listening to the demons, the pain trade is up

the markets do like symmetry. the only world where i see $zec sub 1k is if BTC accepts below 81k. else it seems unreasonable to think that the strongest asset is going to give you the perfect sub 1k entry that you want while the rest of the market drifts up. bull market.

look at programmable zcash

Buy hard assets

Chicago's Jewelers Row. 8:30 AM on a sunny Saturday. People gather underneath the soft rumble of the elevated trains, attracted by a prosperous coffeehouse. We don't always need to fear elevated transit.

Many things may piss you off about the CTA, but be grateful we have train connections at both airports

ONE OF 4 @acepyr stopped feeling like a test page this month. Tokenized stocks are on the same Live screen as BTC... The curve is gone. The price is a book. I am writing the journey down while the mechanism is still new, not after everyone has already memorized it. 🔍🔍

san ysidro ranch being the #1 hotel in the US now is making my goals to relocate to Montecito more and more out of reach

on $hood chain, lessons from base, and ecosystem development 1/ rh chain has the best setup any corpo chain has had, and it's making the same mistakes base made. here's what it controls, what it's getting wrong, and what i'd do. 2/ the constraint: stock tokens are closed to US persons under securities law. that's not rh's fault, but the chain's best asset can't reach rh's core users. so the levers it does control matter even more. 3/ the edge is real anyway. memes on the chain trade against stock tokens instead of eth or usdc. as of sept 1, the largest stock-paired meme, $ai, held 16%+ of all tokenized $nvda on the chain. on sept 2, meme/stock pairs did $217m in volume vs $127m for direct stock trading. 4/ speculation is deepening rh's equity liquidity. base speculation never did that for any $coin assets (non stable). so base cycled narratives (social, creator coins, then trading, payments, and ai) until armstrong conceded “content coins didn't work”. king-made $zora fell 99.8% from its peak; that’s ecosystem collapse. 5/ lever one is listings. the in-app listing is the main bridge between rh's distribution and the chain. on sept 10, asset pages for $juggernaut and $frong appeared, with no announcement, no criteria, and no trading. juggernaut still ran ~500% in an hour. 6/ showing proof that's the most powerful liquidity tool on the chain, and it was used without a process. each random use teaches the market the button is a lottery, not a signal. we don’t have infinite tools. we don’t have infinite opportunities. it’s not day one. we have lessons. this stuff matters. 7/ lever two is where new products go. at $hood summit, the centerpiece was agents. us perps route through bitstamp, rh's own cex. earnings contracts come from cboe. none of the headline launches i could find run on rh chain. nothing about the rwa narrative that literally birthed the chain. 8/ the base pattern: the chain is where ideas get tested, and the cex is where the value ends up. base builders publicly accused it of favoring insiders and leaving them out. many left. 9/ lever three is the narrative. equities are what made and make this chain different, and the vast majority of the keynote was about ai. base shows what narrative drift costs. focus, conviction, and constant reassurance or lose. ai will come either way. 10/ the counterexample: $hype built one core order book and lets outside builders earn fees for routing flow into it. the parent wins when builders win. 11/ what i'd do: a) an ecosystem fund for stock-native primitives first: stock-paired launches, equities as cashback, multi-equity pools, etc. b) one owner for listings, with public criteria (doxxed team, liquidity depth, time live, stock-token pairing) on a set cadence 12/ c) pay for stock-token flow. any app that routes volume into stock tokens earns a fee share. d) open agent apps to chain builders. integrate them. don’t compete with your ecosystem. e) concentrate support in a few leaders, so their gains spill over into the next wave of tokens. lead with strength. 13/ on talent, the crypto model is a small internal team that lives onchain and knows every serious builder by name. nearly all building happens outside, by builders in constant contact with that team, with grants, hiring help, and a real path into the app. 14/ rh has what base never had: speculation that deepens its core biz. it’s the rh thesis. the value will flow both ways. 24/7 trading, equities for all. but tokens are down ~80%+ from highs, and chain dex has now halved, while narrative slides and tools get used willynilly. rh has the opportunity to be the consumer crypto chain. hope they can lock in here.

Post mortem for the September 24th, 2026 exploit of Payy's bridge contract. Based on our investigation, it appears that an attacker submitted an invalid burn proof that Payy’s deployed Noir/Barretenberg verifier accepted. The first burn released 1,828,589.378132 USDC from the Payy rollup even though it appears that the transaction was invalid. A second burn of 1 USDC was paid early by a burn substitutor and later reimbursed. The second transaction released 90,202.820016 USDC to the same receiving wallet. It appears there was a proving-system vulnerability in the Noir/Barretenberg verifier, developed by Aztec. Full report: polybase.notion.site/Payy-US…

Shielded Bitcoin: Private Transfers on Bitcoin L1

1-bit Qwen3.8-27B just more than DOUBLED its MMLU-Pro score. They didn’t change the decoder. 29.04% -> 61.54%, according to a new paper from ISTA-DASLab. Same lab behind GSQ-RCO, some of the best tiny Qwen3.8-27B quants in my book. Their method is called Disaggregated Quantization. You use different weights to read the prompt and generate the answer. A trained NVFP4 prefiller processes your input and builds the cache. Then the tiny GGUF decoder takes over. They train the prefiller specifically for that decoder, so it learns to produce representations the heavily compressed model can use. The extra checkpoint is 12.8 GiB, but you don’t need all of it in VRAM. Stream it from SSD layer by layer, reusing GPU memory. With a long enough prompt, loading can overlap computation. That’s a pretty fucking good reason to pay attention if your GPU is short on memory. I want to test this on my 4x3090 rig with NVMe. The released implementation targets Blackwell, so this needs adaptation. First I’ll check whether the quality gains survive on Ampere, then measure whether offloading actually helps. Paper: arxiv.org/abs/2609.26333

The Hermes Agent you installed in March is not the Hermes Agent shipping today. 🪽 v0.2 → v0.21 in six months: 👉 One agent loop → multi-agent Kanban 👉 Terminal only → native desktop apps 👉 Text chat → streaming voice + wake words 👉 "Done" → verification contracts that prove it 👉 One bot → Bot Mode rooms where agents message each other Reading the change log is now a part-time job. So I turned it into 30 seconds. Save this before you upgrade. 🚀 #HermesAgent #AIAgents

🤯

> be coder > it's saturday, 85% codex left on your weekly > saved it all for sunday coding session > astra will burn through it in 8 hrs > but those 8 hrs will be glorious > next reset in 2 days > monday I'll be back on 100% > timbo presses the reset button > it's saturday > you're back at 100% > next reset in 7 days wake up sheeple.

You can put the hood on and go private by staking your $HOODS now! rhoods.xyz/hood

the ai you pay $20 to $200 a month for is a rental, and whoever you rent it from can swap the model, cap your usage or pull it whenever they want. in february openai retired gpt 4o from chatgpt, paying users asked for more time to move their work off it, and it was gone anyway. the weights on your own gpu don't get retired. a 12gb 3060 runs a 27b at 50 tok/s today and it's the same model next year, offline, no subscription, no usage cap, and nothing you type into it leaves the machine. own your thinking anon and keep it on your metal. buy a gpu, start at 12gb, and learn the stack while it still feels like a nerd thing.