Web3 Creator I Crypto Researcher | Creator @okx | DM for collabs/marketing
Web3
Joined September 2017
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Most people view TradFi entering crypto as either pure validation or an immediate compromise.
The reality with ICE backing Trade[XYZ] on Hyperliquid tech is far more nuanced.
TradFi gets a compliant path into 24/7 perps. Hyperliquid proves its infrastructure can handle institutional scale.
The real test is execution.
CFTC compliance brings clearing and identity friction that decentralized perps usually bypass.
It is a major architecture milestone. Whether it preserves the open ethos remains an open question.
$HYPE rose 19% following this news.
Zev retweeted
Most teams announce mainnet dates before their stack even works.
@quipnetwork did the opposite.
Accounts, swaps, points, compute subnets, and QVM are already running together on testnet.
The only checkpoint left on the board is the external chain audit.
When tech leads the hype, shipping becomes inevitable.
We’re in the final stretch to mainnet 🦋
Accounts, swaps, points, compute subnets, and QVM are live on testnet, and coming together in one app.
One step left: an external chain audit.
Thanks to everyone who’s been a part of this.
Full update ↓
quip.network/blog/quip-netwo…
Most teams announce mainnet dates before their stack even works.
@quipnetwork did the opposite.
Accounts, swaps, points, compute subnets, and QVM are already running together on testnet.
The only checkpoint left on the board is the external chain audit.
When tech leads the hype, shipping becomes inevitable.
We’re in the final stretch to mainnet 🦋
Accounts, swaps, points, compute subnets, and QVM are live on testnet, and coming together in one app.
One step left: an external chain audit.
Thanks to everyone who’s been a part of this.
Full update ↓
quip.network/blog/quip-netwo…
We spent years building decentralized finance, but we still haven't solved institutional trust.
Large-scale capital stays away not because of low returns, but because there are no credible standards to assess on-chain counterparties without giving up custody or privacy.
@zerufinance is addressing this exact barrier.
Their architecture creates verifiable, zero-knowledge-compatible trust metrics that prove creditworthiness without exposing proprietary trading data or compromising decentralization.
It gives serious capital a secure framework to participate on-chain.
Institutional adoption won't happen through buzzwords; it happens through verifiable risk architecture.
Most NFT drops feel completely disconnected from any actual product utility.
I watch teams hype up digital art for weeks, only for the collection to end up abandoned once mint finishes.
@vangrid_io Agents seems to take the opposite route by linking the drop directly to on-chain identity across their spatial grid.
Tomorrow's reveal on OpenSea is going to show whether this is real infrastructure or just another profile picture.
I spent way too much time thinking trading was just about having better charts or timing entries.
Then you look at the raw data: 97% of Pumpfun traders lose. 86% on Hyperliquid lose. The average across major venues sits at 88.5% loss rates.
Most retail participants are just paying for everyone else’s yield.
@zerufinance flips this dynamic with Activity Markets: turning verified onchain footprints into creator and miner rights instead of pure exit liquidity.
When your actual activity generates equity, the house edge disappears.
35M monthly users across 12 trading platforms.
Reported trader loss rates:
- Pumpfun: 97%
- FOMO: 96.5%
- Polymarket: 92.5%
- Hyperliquid: 86%
- Binance Futures: 80%
The simple average across all 12 platforms: 88.5%.
Different markets, same question: where does all that value end up?
Activity Markets: verified onchain activity earns miner/creator rights. Traders decide what the market is worth.
Registration is open. ↓
My recent highlights:
> 524K views in 3 months
> 15,060 followers
> 1,174 smart followers
> 9.21% engagement rate in 3 months
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GM ☀️
The artificial intelligence race has officially hit the text data wall.
Language models have consumed the public internet, but physical robots do not live inside web browsers,they operate in kitchens, factories, and streets.
I look at @vangrid_io as the foundational spatial cortex being built for this new era.
By converting everyday mobile movement into verified 3D physical training sets, they supply the missing real-world ground truth that foundation models desperately need.
The next frontier of artificial intelligence belongs to spatial embodiment, not larger context windows.
I used to run automated trading bots on centralized exchanges, and the constant API outages during high volatility cost me thousands of dollars.
Even onchain, connecting bots directly to private liquidity pools without an execution and escrow layer exposes you to extreme front-running and failed transactions.
I decided to re-architect my setup by exploring how @termix_ai powers autonomous DeFi and trading agents.
Instead of deploying isolated scripts that handle funds insecurely, I use TermiX to commission specialized execution agents on agent.family.
I publish a liquidity-rebalancing task backed by a programmatic USDC escrow governed by the AACP protocol.
An autonomous trading agent detects the arbitrage gap, calculates optimal slippage paths, and executes the rebalance across decentralized exchanges.
The contract checks onchain settlement proofs before releasing the transaction fee to the agent.
My capital remains completely protected in non-custodial contracts, eliminating counterparty default risks.
Trading at machine speed requires infrastructure built specifically for programmatic reliability.
TermiX provides the secure commercial rails that transform autonomous DeFi trading from a risky gamble into a deterministic, verifiable workflow.
I used to run automated trading bots on centralized exchanges, and the constant API outages during high volatility cost me thousands of dollars.
Even onchain, connecting bots directly to private liquidity pools without an execution and escrow layer exposes you to extreme front-running and failed transactions.
I decided to re-architect my setup by exploring how @termix_ai powers autonomous DeFi and trading agents.
Instead of deploying isolated scripts that handle funds insecurely, I use TermiX to commission specialized execution agents on agent.family.
I publish a liquidity-rebalancing task backed by a programmatic USDC escrow governed by the AACP protocol.
An autonomous trading agent detects the arbitrage gap, calculates optimal slippage paths, and executes the rebalance across decentralized exchanges.
The contract checks onchain settlement proofs before releasing the transaction fee to the agent.
My capital remains completely protected in non-custodial contracts, eliminating counterparty default risks.
Trading at machine speed requires infrastructure built specifically for programmatic reliability.
TermiX provides the secure commercial rails that transform autonomous DeFi trading from a risky gamble into a deterministic, verifiable workflow.
The OCC has approved Ripple to form a national trust bank under federal supervision.
The charter does not permit retail deposits or commercial lending, leaving customer balances outside FDIC insurance.
Instead, the entity will manage reserve assets backing the $2.6B RLUSD stablecoin and provide institutional custody, operating alongside state-level issuance via Standard Custody.
Supporters argue federal oversight strengthens stablecoin transparency and reserve security.
Conversely, banking associations contend that trust charters grant crypto firms systemic access without the rigorous capital rules required of commercial banks.
Roughly 34% of all Bitcoin currently sits in quantum-vulnerable addresses that exposed public keys during past transactions.
Once quantum compute reaches scale, those dormant UTXOs become low-hanging fruit for automated private key derivation.
I like how @quipnetwork tackles this exposure without waiting on a Bitcoin soft fork.
By deploying through @ArchNetwork, they commit post-quantum public keys directly to Bitcoin's execution layer while letting users keep their funds on native UTXO rules.
Pragmatic protection secures base assets today instead of betting on a ten-year governance consensus.
Comparing Predictor directly to Polymarket shows a basic misunderstanding of the stack.
Polymarket is a consumer-facing dApp. It is a single venue where retail traders log in, pick a side, and place volume on trending headlines.
@PRDCTR_IO operates at the foundational layer.
Instead of launching just another isolated betting portal, the team built a dedicated AppChain engineered to host an entire ecosystem of prediction platforms.
Predictor.io is simply the flagship product running on that network.
The market does not just need another place to place trades.
It needs purpose-built execution rails that can support dozens of independent markets simultaneously.
Consumer apps capture attention for a season. Core infrastructure captures value across entire cycles.
🤝 Paid partnership
Most onchain data today is pure noise.
Teams fake volume, and protocols blindly trust broken data feeds.
I'm watching @zerufinance closely because they are finally tackling this with verifiable activity markets and real trust oracles.
@Ashutosh_Sahoo is speaking at @TheTieIO's The Bridge in NYC today to break down how onchain markets evolve past blind speculation.
Real value requires real verification.
The ZeruAI team is heading to NYC for @TheTieIO's The Bridge tomorrow.
@Ashutosh_Sahoo will be joining the conversations around activity markets, trust oracles, and what comes next for onchain markets.
If you're attending, come say hi!
GM CT
Training embodied AI models on raw video streams is notoriously inefficient because 90% of pixels in adjacent frames are redundant background noise.
Feeding identical static walls over and over burns model compute without teaching the machine anything new about spatial physics.
I track how @vangrid_io tackles this through keyframe entropy selection.
Their ingestion stack filters for high-information delta frames, isolating dynamic state changes and critical viewpoint shifts before feeding the spatial pipeline.
Efficiency in physical AI is built on tokenizing novelty, not hoarding repetitive pixels.
We often talk about bringing real-world assets on-chain, but we ignore the core bottleneck.
The most valuable data on the internet remains locked inside private Web2 accounts.
When an application requires financial credentials, identity records, or private API queries, users are usually forced to upload raw documents.
The moment you broadcast those records openly, personal privacy is destroyed.
I find the cryptography model engineered by @primus_labs to be a genuinely practical breakthrough.
Instead of exposing raw payload data, Primus zkTLS cryptographically proves that an HTTPS session is authentic.
The protocol delivers up to 10× higher performance than legacy verification systems without leaking private credentials during proof generation.
Smart contracts can finally verify real-world eligibility while the underlying data remains strictly private.
Verifiable finance does not require voluntary surveillance.
True adoption begins when users can prove facts about their digital footprint without surrendering custody of their identities.
Most people think RWAs mean holding real-world assets. The market tells a different story.
RWA perps open interest just crossed $19.8B, almost tripling since June.
It is pure leveraged exposure, not ownership.
> CEXs control 71% of the volume, dominating equities at $6.4B and precious metals at $4.3B .
> DEXs hold the remaining 29%, but lead equity indices at $1.1B .
One offers deep centralized liquidity. The other proves growing appetite for permissionless exposure.
Global capital access is widening fast, but leveraged synthetic risk always cuts both ways.
Received nearly 9 DUSD for the @StandX_Official project campaign on @KaitoAI.
Thank you very much for your generosity. 😂
Regulators across the US and Europe are already setting 2028 deadlines for critical infrastructure to adopt post-quantum standards.
Most Web3 protocols are operating as if they have decades to figure this out.
I look at @quipnetwork because they are building directly for that institutional timeline.
Their asset wrapper lets institutions lock and custody onchain value under NIST-aligned post-quantum defenses today, without waiting years for layer-1 consensus overhauls.
Institutional capital will only settle on infrastructure that can survive the coming regulatory and hardware shift.
I stopped worrying about front-running bots the moment I looked into token launch mechanics.
The real problem is not the bot that enters ahead of you by two seconds.
It is the developer holding 10% of the supply through bundled wallets before anyone else can touch it.
As @zerufinance pointed out, that is how insiders pocketed $579M while external bots fought over $31.5M.
When supply control happens at creation, timing your entry is just an illusion.
Who really wins the meme launch game?
Bitquery analysed 8.2M Pump(dot)fun launches and found:
- 21% had developer-linked wallets buying in the launch block, holding a median 10% of supply.
- Developers and bundled wallets made at least $579M after fees on tokens they sold.
- Sniper bots made $31.5M.
Developers and bundled wallets made 18x what sniper bots did.
The problem goes beyond bots getting in first. It’s who gets access, how much supply they secure, and when they sell.
