You should know better
Brokechain
Joined June 2014
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Onboarded noob friend to crypto this week
Tl;dr
=> Retail will flock to Solana because it is easy, cheap and straightforward
=> Coinbase Wallet (buggy) and marketing (confusing) needs to be improved big time
Asked to open a @coinbase acct on desktop & download app
1/4
ramaruro retweeted
The funds from the $3.8M NEAR Intents exploit have been returned, just one day later, and the investigation is closed.
Thanks to SHIELD, the AI security layer on Intents, along with some aggressive detective work, the Intents team identified the party responsible less than 24h after the hack, established communication, and got the funds back in full at 14:30 UTC today.
Thank you to @alexauroradev and the whole @near_intents team for this fast and clean resolution โ as well as the broader @NEARProtocol ecosystem and SHIELD partners for the support and help. Thereโs been relentless work over the past 24 hours by so many people to make this right and it is a great testament to this communityโs values and determination.
To echo Alex: for security researchers looking for exploits, we encourage you to use bug bounties. They exist for a reason.
At NEAR, we believe that privacy is a right, but not as a way to facilitate crime. Our technology is built to expand human agency and opportunity, not to facilitate criminal activity. The events of the last week have shown the value of SHIELD to find suspicious activity before things escalate too far, as well as to accelerate resolution so the vast majority of legitimate users are not affected. Confidentiality cannot come at the expense of lawfulness and I strongly believe it doesnโt have to.
Weโve learned a great deal from this incident and work is already underway to harden our security systems and further adapt to the changing cybersecurity landscape. AI may be accelerating exploits, but it can also help us defend against them. I hope our entire industry responds with vigilance and feels the same sense of urgency to work together.
ramaruro retweeted
You donโt fully grasp how much of your life is tracked until youโre sitting in a courtroom, watching federal prosecutors use your digital history against you, down to your most harmless Google searches. Your entire life becomes an open book, and even your most innocent actions can be twisted into something sinister.
They get to tell the most damning version of your story. To tell yours in your own words, you have to take the stand.
Just applied for the @zecpunksnft whitelist.
The first punks NFT collection on $ZEC.
You can also apply here : zecpunks.xyz/?ref=PUNKA8DE
You can use the same seedphrase in a Phantom wallet and you will see the token.
Much simpler approach vs a recovery tool
I just made possibly the biggest mistake of my life.
I sent 1.3 million $ZCAT tokens (~$150k) to my @coinbase solana wallet by mistake.
I have contacted support, only to be told that they cannot recover it, as it is currently an unsupported token.
If anyone knows anyone at @coinbase @coinbasetraders who could possibly help me, or has dealt with a situation like this before, I would be really grateful.
3
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ramaruro retweeted
When designing a fixed rates product for on chain finance, two initial questions you need to ask are:
1. Why none of the existing fixed rates product currently work?
2. Inversely: what makes floating rate work?
The answers are:
* Lenders do not want the extra decision complexity or management overhead - which is the same reason why one-click earn programs will remain popular
* Lenders want immediate liquidity aka no or little duration - they donโt want to be trapped for 6 months - which is why the pooled utilisation model works - the unutilised funds are immediate exit liquidity
โ
What solves this duration / liquidity / management complexity is the simple interface of a vault for the lenders.
Curators will absorb all the fixed rates decisions and mix durations to give as much of the instant liquidity experience of open-term lending.
And they should get paid for it.
โ
(some of the existing models are outright flawed with no liquidation mechanism or 1d long fixed term, that are not even worth discussing - this is obviously a complex product so no wonder nobody got it right yet and many had such bad takes on it)
Introducing Kamino Fixed Rates
The definitive architecture for fixed-term, fixed-rate credit on-chain. Now live in private beta. Public launch in Q3 2026
Read the light paper: kamino.com/fixed-rates-lightโฆ
ramaruro retweeted
Introducing Kamino Fixed Rates
The definitive architecture for fixed-term, fixed-rate credit on-chain. Now live in private beta. Public launch in Q3 2026
Read the light paper: kamino.com/fixed-rates-lightโฆ
ramaruro retweeted
๐ฌ๐ฎ๐ซ๐ฏ๐ข๐ฏ๐๐ฅ ๐ ๐ฎ๐ข๐๐ ๐๐จ๐ซ ๐ญ๐ก๐ ๐๐จ๐ฆ๐ข๐ง๐ ๐๐ฎ๐ฅ๐ฅ ๐ฆ๐๐ซ๐ค๐๐ญ
here is a set of rules i think are good guidance to navigate the upcoming bull market.
๐๐จ ๐ง๐จ๐ญ ๐๐ฏ๐๐ซ๐๐ ๐ ๐๐จ๐ฐ๐ง
if a trade goes against you do not buy more on the way down. this is a recipe to get rekt (in aggressive narrative trading at least, might be different in building a longterm btc position). the market is showing you that your thesis or your timing is wrong, do not fight the market. do not fall into the illusion to think you are right and everybody else is wrong, because most of the time you are not. or in the words of Paul Tudor Jones: "losers average losers".
๐๐ฅ๐ฐ๐๐ฒ๐ฌ ๐๐จ๐๐ฎ๐ฌ ๐จ๐ง ๐ญ๐ก๐ ๐ง๐๐ฑ๐ญ ๐ฌ๐ก๐จ๐ญ
always keep your eyes forward and think about the next shot. do not entertain thoughts of "what if" and indulge in revisionist history thinking ala "if i had held y longer i would be up x amount of money". what is done is done, focus on the next shot. the same goes if you had hit a winner and are up fat. many people stay still and admire their shot instead of focussing of what other shots they might miss while doing this. best shooters have the worst memory.
๐๐จ ๐ง๐จ๐ญ ๐๐ฌ๐ฌ๐จ๐๐ข๐๐ญ๐ ๐ฒ๐จ๐ฎ๐ซ๐ฌ๐๐ฅ๐ ๐ฐ๐ข๐ญ๐ก ๐ฉ๐๐จ๐ฉ๐ฅ๐ ๐ฐ๐ก๐จ ๐๐ซ๐ ๐ฌ๐ญ๐ฎ๐๐ค ๐ข๐ง ๐จ๐ง๐'๐ฌ ๐ฐ๐๐ฒ
distance yourself from people who get defensive and butthurt when their trades are challenged or a contrary opinion about their investment is voiced. a good operator tries to see things from all angles and is always open to steelman a bear case. especially dangerous are groupchats where bears get ridiculed and discouraged to voice their opinion, the result of this is an echo bubble. leave these groups.
๐ข๐ ๐ง๐จ๐ซ๐ ๐ฆ๐จ๐ฌ๐ญ ๐จ๐ ๐๐
CT at its core has a very distorted view of money. whenever market puts a first green candle in people are freaking out and fall into some kind of psychosis about money and how much they gonna make. you can see it already starting with people tweeting about being in "7-figure hell'. unfollow / block these accounts, they will lead to a distorted view of money for yourself and open up the door for all kinds of bias traps. the same goes for all the people who always hindsight post how they are in all the runners and are up huge but forgot to voice their opinion before the asset went +200%. there is a huge amount of larps and liars on CT, and the result for many new entrants is that they get trapped in some kind of fata morgana where it seems everybody but themselves is winning huge. the results is often excessive risk taking and total loss of NW as a consequence.
๐ค๐๐๐ฉ ๐ ๐ฌ๐จ๐ฅ๐ข๐ ๐ซ๐ข๐ฌ๐ค ๐ฆ๐๐ง๐๐ ๐๐ฆ๐๐ง๐ญ ๐๐ญ ๐๐ฅ๐ฅ ๐ญ๐ข๐ฆ๐๐ฌ
stay in your lane and stick to your protocol, no matter what others are doing or how much somebody else is winning. there will always be somebody who wins extreme amounts of money by reckless betting. but thats survivorship bias at work here, because for everybody like this that you see are 10 dead bodies who lost it all. your NW will always regress to the level of your process (read that again, this is a very important concept to understand). profits made by excessive risk taking will be lost by excessive risk taking. live by the sword, die by the sword.
๐ญ๐ก๐ ๐ช๐ฎ๐๐ฅ๐ข๐ญ๐ฒ ๐จ๐ ๐ ๐๐๐๐ข๐ฌ๐ข๐จ๐ง ๐๐๐ง๐ง๐จ๐ญ ๐๐ ๐ฆ๐๐๐ฌ๐ฎ๐ซ๐๐ ๐๐ฒ ๐ข๐ญ๐ฌ ๐ข๐ฆ๐ฆ๐๐๐ข๐๐ญ๐ ๐จ๐ฎ๐ญ๐๐จ๐ฆ๐
good decisions can have bad outcomes and still be good decisions, and vice versa. due to the influence of luck, chance and variance the quality of a decision cannot be judged by its immediate outcome. therefore do not categorize decisions by how much money they made or lost. think deeper, simulate outcomes for more than one possible outcome. the goal is to constantly make good decisions.
there is a bit more nuance to all of these, but you will figure it out if you want to. these are my basics. goodluck, see you in the order books.11320:58
ramaruro retweeted
Privacy is defining the next generation of apps, both financial and agentic.
Privacy-first AI platform @AskVenice ($VVV) has 3M+ users and is growing fast. NEAR is the infrastructure making it possible, from private inference to confidential execution.
How NEAR powers Venice ๐งต
$NEAR: the already functioning coordination layer of the upcoming AI Agent economy
TVL, TPS, dAPPS not the relevant metric anymore, but volume coordinated through NEAR (private) intents catering to Non KYC-able agents
ramaruro retweeted
Verifiably private AI is NEAR AI.
Major platforms and nation-scale systems like Venice, Brave, Abound, and the Government of Bermuda are integrating NEAR AI to bring confidential inference to their users ๐งต
ramaruro retweeted
Crazy, and not very fun fact
If you had been in t-bills OR cash the past 5 years and not taken a single trade, you'd have out-performed the total crypto marketcap, including BTC. And that's without adjusting for inflation
If we exclude stablecoins, btc, eth and just go with alts it's the only market in the world to not be or have made ath's during that period.
ramaruro retweeted
Wild story unfolding around the KelpDAO hack funds frozen on Arbitrum.
Quick context: in April, Lazarus Group (DPRK-linked) hacked KelpDAO for $292M via a LayerZero bridge bug. Some of the stolen ETH flowed through Arbitrum, and Arbitrum's Security Council froze $71M before the attacker could move it further.
The industry mobilized to recover. Aave, KelpDAO, LayerZero, EtherFi, and Compound co-authored a proposal asking Arbitrum DAO to release the frozen ETH to a multisig that would compensate hack victims. The vote is passing.
Then this week, a plot twist. Lawyers showed up with a restraining order. But not on behalf of the KelpDAO victims.
The plaintiffs are Han Kim and two other groups - family members of people killed in DPRK-backed terrorist attacks years ago. They hold combined ~$877M in unpaid US court judgments against DPRK. North Korea never paid. They have been hunting for any reachable DPRK asset for over a decade.
When Arbitrum's frozen ETH was publicly identified as "DPRK money," they saw a target.
Their argument: this is DPRK property, we have $877M in judgments against DPRK, give us the money.
The counter-argument: DPRK does not actually own this ETH - they stole it. The real owners are the KelpDAO hack victims. The old terrorism creditors are trying to grab money that was never really DPRK's.
Arbitrum is now caught in the middle. The industry wants to release funds for hack recovery. NY court is saying "do not move anything until we resolve this." If multisig signers transfer the ETH while the restraining order is active, they become personally liable.
This is the first real test of DAO funds against competing US court claims. The precedent set here will shape how every future DAO incident response handles legal pressure.
ramaruro retweeted
"so you staked your ETH on the Ethereum blockchain to earn yield?"
"yes, Dave"
"except you didn't want your capital to be locked up so you actually staked it with a liquid staking protocol called Lido?"
"that's correct, Dave"
"and Lido gave you a liquid staking receipt token called stETH in return?"
"yes, Dave"
"and then you didn't think that was enough, so you juiced the yield even further by depositing your stETH receipt tokens into a restaking protocol called Eigenlayer?"
"you are correct, Dave"
"and now you didn't want to lock up your capital, so you actually restaked with a liquid restaking protocol called KelpDAO who provided you with a liquid restaking receipt token called rsETH?"
"you got it, Dave"
"and then that was surely not enough juice, so you then deposited your rsETH tokens into a lending protocol called AAVE so that you could open a leveraged looping position that borrows ETH against the rsETH collateral and restakes the ETH into rsETH which is then deposited as collateral, except it turns out rsETH used a cross-chain bridge called LayerZero whose security is held together by a 1/1 toothpick, which was obviously hacked by north koreans causing rsETH to become undercollateralized and now these looping positions are stuck and unprofitable, and everyone is pointing fingers at each other, and also DeFi is a very serious industry"
"you are 100% correct, dave"
jfc.
ramaruro retweeted
0/ DeFi needs circuit breakers and other safety mechanisms which slow down large transactions and provide time for reaction. Borrow lend protocols should not allow a new user to show up with a $300M position and take out a loan against it immediately. Some ideas:
ramaruro retweeted
Today is a monumentous day for quantum computing and cryptography. Two breakthrough papers just landed (links in next tweet). Both papers improve Shor's algorithm, infamous for cracking RSA and elliptic curve cryptography. The two results compound, optimising separate layers of the quantum stack. The results are shocking. I expect a narrative shift and a further R&D boost toward post-quantum cryptography.
The first paper is by Google Quantum AI. They tackle the (logical) Shor algorithm, tailoring it to crack Bitcoin and Ethereum signatures. The algorithm runs on ~1K logical qubits for the 256-bit elliptic curve secp256k1. Due to the low circuit depth, a fast superconducting computer would recover private keys in minutes. I'm grateful to have joined as a late paper co-author, in large part for the chance to interact with experts and the alpha gleaned from internal discussions.
The second paper is by a stealthy startup called Oratomic, with ex-Google and prominent Caltech faculty. Their starting point is Google's improvements to the logical quantum circuit. They then apply improvements at the physical layer, with tricks specific to neutral atom quantum computers. The result estimates that 26,000 atomic qubits are sufficient to break 256-bit elliptic curve signatures. This would be roughly a 40x improvement in physical qubit count over previous state-of-the-art. On the flip side, a single Shor run would take ~10 days due to the relatively slow speed of neutral atoms.
Below are my key takeaways. As a disclaimer, I am not a quantum expert. Time is needed for the results to be properly vetted. Based on my interactions with the team, I have faith the Google Quantum AI results are conservative. The Oratomic paper is much harder for me to assess, especially because of the use of more exotic qLDPC codes. I will take it with a grain of salt until the dust settles.
โ q-day: My confidence in q-day by 2032 has shot up significantly. IMO there's at least a 10% chance that by 2032 a quantum computer recovers a secp256k1 ECDSA private key from an exposed public key. While a cryptographically-relevant quantum computer (CRQC) before 2030 still feels unlikely, now is undoubtedly the time to start preparing.
โ censorship: The Google paper uses a zero-knowledge (ZK) proof to demonstrate the algorithm's existence without leaking actual optimisations. From now on, assume state-of-the-art algorithms will be censored. There may be self-censorship for moral or commercial reasons, or because of government pressure. A blackout in academic publications would be a tell-tale sign.
โ cracking time: A superconducting quantum computer, the type Google is building, could crack keys in minutes. This is because the optimised quantum circuit is just 100M Toffoli gates, which is surprisingly shallow. (Toffoli gates are hard because they require production of so-called "magic states".) Toffoli gates would consume ~10 microseconds on a superconducting platform, totalling ~1,000 sec of Shor runtime.
โ latency optimisations: Two latency optimisations bring key cracking time to single-digit minutes. The first parallelises computation across quantum devices. The second involves feeding the pubkey to the quantum computer mid-flight, after a generic setup phase.
โ fast- and slow-clock: At first approximation there are two families of quantum computers. The fast-clock flavour, which includes superconducting and photonic architectures, runs at roughly 100 kHz. The slow-clock flavour, which includes trapped ion and neutral atom architectures, runs roughly 1,000x slower (~100 Hz, or ~1 week to crack a single key).
โ qubit count: The size-optimised variant of the algorithm runs on 1,200 logical qubits. On a superconducting computer with surface code error correction that's roughly 500K physical qubits, a 400:1 physical-to-logical ratio. The surface code is conservative, assuming only four-way nearest-neighbour grid connectivity. It was demonstrated last year by Google on a real quantum computer.
โ future gains: Low-hanging fruit is still being picked, with at least one of the Google optimisations resulting from a surprisingly simple observation. Interestingly, AI was not (yet!) tasked to find optimisations. This was also the first time authors such as Craig Gidney attacked elliptic curves (as opposed to RSA). Shor logical qubit count could plausibly go under 1K soonish.
โ error correction: The physical-to-logical ratio for superconducting computers could go under 100:1. For superconducting computers that would be mean ~100K physical qubits for a CRQC, two orders of magnitude away from state of the art. Neutral atoms quantum computers are amenable to error correcting codes other than the surface code. While much slower to run, they can bring down the physical to logical qubit ratio closer to 10:1.
โ Bitcoin PoW: Commercially-viable Bitcoin PoW via Grover's algorithm is not happening any time soon. We're talking decades, possibly centuries away. This observation should help focus the discussion on ECDSA and Schnorr. (Side note: as unofficial Bitcoin security researcher, I still believe Bitcoin PoW is cooked due to the dwindling security budget.)
โ team quality: The folks at Google Quantum AI are the real deal. Craig Gidney (@CraigGidney) is arguably the world's top quantum circuit optimisooor. Just last year he squeezed 10x out of Shor for RSA, bringing the physical qubit count down from 10M to 1M. Special thanks to the Google team for patiently answering all my newb questions with detailed, fact-based answers. I was expecting some hype, but found none.
ramaruro retweeted
Pine Analytic's just made the bear case for Bittensor.
(You might want to save this one).
Here's a condensed summary of their thesis:
โ $TAO trades at $275 with a $2.6B market cap.
โ Grayscale filed an S-1 for a NYSE-listed ETF.
โ Jensen Huang gave it a public endorsement.
โ It has Bitcoin-style tokenomics with a 21M hard cap.
None of that is being disputed by @PineAnalytics.
The question is whether the network can generate enough real revenue to justify the valuation.
Starting with how the money flows...
Bittensor has four player classes:
1. Subnet owners build AI marketplaces (18% of TAO emissions).
2. Miners do the AI grunt work (41%).
3. Validators grade the miners (41%).
4. Stakers dump TAO into liquidity pools.
TAO is the entry ticket for everything. Mining, staking, subnet tokens, services. All roads lead to TAO.
The supply side? Completely transparent. Emissions, halving schedules, staking ratios - all onchain.
The demand side? Crickets.
No dashboard tracking real revenue by subnet. AI work happens offchain (inference requests, compute jobs, training calls) none of it touches the blockchain.
This isn't a bug they're fixing - it's baked in.
So what does demand actually look like?
Chutes is the biggest subnet. 14.4% of all emissions. It sells serverless AI inference at prices "85% below AWS."
The usage numbers look great:
- 400,000+ users
- 5M+ daily requests
- 9.1 trillion tokens processed
But those cheap prices aren't from efficiency. They're from subsidy.
Chutes receives roughly 518 TAO/day - about $142,000 ($52M annualized).
Estimated actual revenue? $1.3M to $2.4M/year.
For every $1 customers pay, the network kicks in $22 to $40 in emissions.
Kill the subsidy and do the math. 101B tokens/day, $142K in daily costs. That's ~$1.41 per million tokens.
Market rate? Together ai charges $0.88. DeepSeek runs $0.40โ$0.80. Smaller models go as low as $0.18.
Without the subsidy, Chutes isn't 85% cheaper - it's 1.6x to 3.5x MORE expensive than centralized options.
The cost advantage doesn't shrink, but actually flips completely.
"But this is the Uber playbook! Subsidize early, raise prices later!"
Except Uber built switching costs during the subsidy period. Driver networks. Proprietary platforms. Enterprise integrations.
Bittensor subnets build none of that. The models are open source. The APIs are standard. Users can bounce to any provider serving the same weights with zero friction.
When the subsidy shrinks, nothing keeps anyone around.
One more thing on Chutes: the team behind it (Rayon Labs) also runs two other subnets. Together they command nearly 24% of total emissions. One team. Almost a quarter of the network's incentive pie.
What about the rest?
Targon is the highest-revenue subnet. Run by Manifold Labs ($10.5M Series A). Enterprise GPU compute. ~$10.4M annualized revenue against a $48M valuation - a 4.6x revenue multiple. The most grounded number in the ecosystem. But it's a projection, not audited.
Templar built Covenant-72B, a 72B parameter model trained on 1.1 trillion tokens. $98M market cap. Zero external revenue. Paid products "in motion" but nothing shipped.
The remaining 120+ subnets? Either no revenue, pre-product, or just farming emissions.
The big picture, as @PineAnalytics sees it:
Total identifiable revenue across the ENTIRE network: roughly $3Mโ$15M annually.
A single subnet's emission subsidy ($52M for Chutes) exceeds the upper bound of what the whole network earns from actual customers.
Against a $2.6B market cap, that's a 175xโ200x revenue multiple. Against FDV of $5.8B, roughly 400x.
For context: CoreWeave and Lambda were valued at 15xโ25x revenue. High-growth SaaS rarely sustains above 50x.
Bittensor's implied multiple is 4xโ10x higher than the most aggressive comp in crypto OR traditional infra. The market is pricing TAO on supply scarcity, institutional catalysts, and AI vibes - not economic productivity.
Now the squeeze.
Subnets are getting crushed from both directions.
From above: Self-hosting. Every model on Bittensor is open source. Weights are on Hugging Face. One H100 serves a 70B model for $40โ$50/day. Tools like vLLM and Ollama make local deployment trivial. Any org with volume is already cheaper running it themselves.
From below: Hyperscalers. Microsoft, Google, Amazon, and Meta spent over $200B on AI capex in 2025. First-priority hardware. Purpose-built data centers. Enterprise relationships already in place. Bittensor's entire annual incentive budget ($360M) is less than Microsoft's weekly AI infra spend.
Then there's the moat problem.
If a subnet builds something valuable, the underlying model and methodology are public by design. Covenant-72B is Apache licensed. Any competitor can copy the approach without touching the TAO economy.
The community says the incentive mechanism IS the moat. But that only works if emissions stay large enough to attract compute. And they shrink with every halving.
So what is TAO actually pricing?
At $2.6B, it's not priced on demand fundamentals. $3M-15M in annual revenue doesn't support that under any framework.
The market is pricing: Bitcoin-like scarcity. The Grayscale ETF catalyst. AI sector rotation. Long-term optionality on decentralized AI.
Legitimate speculative factors. Also entirely supply-side and sentiment-driven.
A TAO position based on scarcity and narrative? Might do great regardless of demand economics.
A TAO position based on Bittensor becoming a real AI services network? That requires evidence that doesn't exist yet - and faces structural headwinds that might prevent it from showing up.
Know which thesis you're holding.
(P.S. Read the full article below ๐)
