GRVT Booster task has been finalized. The top 300 need to confirm in the wallet before 8:00 tomorrow. Each person will receive 416 GRVT tokens. There are still 4 days until TGE—after it launches, let’s try to push for a wave! How about hitting highs of $1–$2? Looking forward to it! If you haven’t confirmed yet, hurry up and do it ~
A rollercoaster from start to finish: at 3 a.m. on July 20 in New York, Argentina faces Spain.
First, let’s talk about how these two teams got here—completely different styles.
Spain, on the other hand, has been rock solid. In the semifinals, they dispatched France 2-0 with ease, and they’ve notched 37 straight matches without defeat. The most terrifying part is their defense: in seven games, they conceded just one goal. Mbappé finished the match with zero shots on target, and Spain’s back line looked like an immovable slab of steel.
Argentina, meanwhile, makes every match a heart-stopping thriller. In the Round of 16 against Egypt, they were down 0-2, yet they leveled things up with three goals in just 13 minutes. In the quarterfinal against Switzerland, they only got the job done in extra time. In the semifinal vs. England, they trailed 0-1—then within the final seven minutes, they scored two to turn it around. Every match was a comeback from behind, every game a walk-off winner. If you’ve got a weak heart, don’t watch this team.
Then comes the wildest talking point—39 years old vs. 19.
Yamal has just turned 19. In the semifinals, he earned a penalty to send France packing. His idol is Messi. When Messi won his first Ballon d’Or in 2007, Yamal was only three months old. Now, at 19, he’s set to go straight against his 39-year-old idol in the final for the big trophy.
The head-to-head record is also pretty fascinating. They’ve played 14 times, with each side winning six. They only met once in the World Cup: in 1966, Argentina won 2-1. The most recent meeting was a 2018 friendly, where Spain thrashed Argentina 6-1. But most of the Spain players from that game have since retired; on Argentina’s side, Otamendi, Tagliafico, and Lautaro are still there.
As for my own take: Spain’s control of the game is strong, and their defense is as solid as a fortress. Argentina’s fitness could be a hidden risk—after consecutive extra-time games and comebacks, it’s hard to say how much fuel these older players have left. But for a player like Messi, one person can change a match by himself. The big data gives Spain about a 56% chance to win the tournament, but Argentina has been storming through despite being underestimated the whole way.
At 3 a.m. on July 20, the alarm is set and the beer is ready. A 39-year-old legend vs. a 19-year-old genius—defending champions against an unbeaten side. For this game, you’ll have to wait another four years if you miss it.
Drop your thoughts in the comments: do you think Argentina can defend the title, or is it time for Spain’s new king to be crowned?
This morning Spain eliminated France—now all the pressure is on this match. Tomorrow at 3 a.m., Argentina play England. Messi has faced England for the first time in his career—can you believe it? After 20 years of playing, taking on every top team, he’s somehow never met the Three Lions.
First, let’s talk history and grudges—when these two teams meet, tempers flare.
They’ve met five times in the World Cup: England have won 3 and lost 2, with the edge. In 1986, Maradona’s “Hand of God” sent England packing. In 1998, Beckham was sent off with a red card, and Argentina advanced on penalties. In 2002, Beckham fired in a penalty to seek revenge. After 24 years, old scores and new grudges are being settled together. England legend Scholes has already said outright: “This match will be completely out of control—reds and all that will happen.”
Both sides have their problems.
England: their right-back Quansah is suspended after a red card, and Reece James is in doubt after returning from injury. The good news is Rice has recovered from illness and can start.
Argentina: even worse—after two straight matches that went to extra time, they’ve already played 30 minutes more than England. Enzo felt unwell already in the first half against Switzerland, and Romero has cramped up every match. Do these old guys still have gas left?
Opta’s supercomputer data: England’s qualification probability is 51.9%, Argentina’s is 48.1%, and the chance of going to extra time is close to 30%.
I’ll blurt out a couple of predictions—just chatting, don’t take it as gospel.
Argentina’s veteran squad is the fitness concern, and England’s young team has stronger pressure and attacking momentum. But for a player like Messi—one person can change the game. Tuchel says they need man-to-man marking on Messi, but the question is: who can mark him for a full 90 minutes?
Chances are it’ll go to extra time, and maybe even to penalties. Whoever scores first gets the advantage—England sit back and hit on the counter, while Argentina control possession and grind the tempo. For the first 60 minutes, they’ll probably just test each other.
My gut says it’s 50-50. But players like Messi are terrifying in matches that matter most. Set the alarm for 3 a.m., have the beer ready—this rivalry showdown can’t be missed.
Brothers, who do you think can reach the final and battle Spain for the title?
Newton Protocol further refines authorization granularity from the asset level to the transaction level
Studying low-level protocols for so many years, I’ve developed a habit: when I look at a protocol’s design, I don’t focus on what new features it adds—I look at what it breaks apart. Real architectural innovation is often not the appearance of a new module, but the splitting of something that used to be treated as a single whole into two independent parts. In the past two weeks, I’ve been looking at @NewtonProtocol ’s Mainnet Beta. At first, my attention was entirely on the verifiable computation that combines TEE with ZKP—after all, engineering a trusted execution environment together with zero-knowledge proofs is a thing in itself worth spending time on. But after going through several rounds of architecture diagrams, what repeatedly made me pause wasn’t that; it was VaultKit’s position in the overall execution flow. It’s placed too far forward—so far forward that it makes me feel the designers never intended to hand over execution authority in full to anyone.
An Architecture Overview of @grvt_io in the dead of night— the more I look, the more it seems like this project has something going for it, but the more I look, the less I feel confident.
First, the publicly visible parts. The official documentation is very clear: “matches and stores data off chain and provides smart contract level guarantees of their execution on chain”. Order matching happens off-chain, and the settlement results are guaranteed on-chain via smart contracts. This ZK Stack Validium architecture combined with a centralized limit order book can handle 600,000 orders per second—its speed is indeed close to that of CEX. Spearbit conducted a comprehensive security audit for 28 days in December 2024, and the team is doing real engineering work. That point has to be acknowledged.
But once I break down the technical details, I can’t help raising some doubts.
In the official “Architecture Overview,” there’s a line: “users requests are routed through our Backend infrastructure - the only permissioned entity allowed to execute transactions against our smart contracts”. All requests must go through the GRVT backend, which is the only permitted entity allowed to submit transactions to the L2 contracts. In plain terms: GRVT runs a private chain. If the backend gets compromised, the whole system is exposed. In the Validium mode documentation, the official text also admits that “operator keeps block data confidential”—meaning the data is controlled by the operator. Four-layer contracts plus a private backend entry point means every interface is a potential vulnerability. Audits can cover the code logic, but they can’t cover combination vulnerabilities across layers. Is this multi-layer defense truly blocking vulnerabilities—or just stacking more attack surface? I can’t say.
Now, let’s talk about the tokens. Total supply: 1 billion. Investors: 19.9%, team: 19%, community/airdrop: 28%, and future reserves: 33.1%. Investors plus team plus future reserves add up to 72%—a majority held by investors and insiders. The TGE was pushed from Q1 to the end of June. On the first day after launch, only 18% corresponding to Season 2 and early airdrops were opened. Meanwhile, for the large allocations held by investors and the team, the whitepaper says nothing about the specific unlock schedule.
After raising $33.3 million, backed by ZKsync and Delphi Ventures, the cumulative trading volume reached $177 billion in 2025. But the centralized architecture risks and the transparency issues in the token model are still right there. I’ll only be able to judge the value for ordinary players once the institutions’ unlock rules are completely transparent.
What do you think of this kind of hybrid architecture? Is it good enough, or are you also skeptical? #grvt
After years of on-chain analysis, there was one contradiction I couldn’t figure out: smart contracts are supposed to be tamper-proof, but regulatory rules change all the time, sanctions lists get updated every few days, and you try to connect an immutable thing to a changing world—this mismatch had never been addressed head-on. Only after dismantling the Newton mainnet Beta did I finally see the answer. @NewtonProtocol
Newton separates strategy from code. Rules are written in Rego and decoupled from the contract. Updates to the sanctions list and adjustments to risk thresholds are made by changing configuration—no need to touch code or redeploy. Traditional upgrades either drag on for weeks due to multisig processes, or they require migrating assets by switching contracts; on-chain and off-chain always end up a step out of sync. Newton compresses that gap to almost zero.
There’s also a technical choice that’s been underestimated: strategy verification uses zero-knowledge proofs. Institutions can prove compliance without disclosing their positions and trading counterparties. For institutions, this is a hard requirement—nobody wants to publish their entire order book just to prove they’re clean.
Taken together, these two points mean Newton solves a triangular contradiction: on-chain things must be verifiable; institutions need privacy; regulators need to keep up with changing requirements. The three demands used to clash with each other, but this architecture now covers all of them at once.
Still, governance makes me uneasy. Protocol upgrades are split into two layers: economic parameters can be adjusted by voting, while core logic requires a hard fork. That sounds reasonable, but I couldn’t find the exact thresholds—51% or 66%? Based on staked votes or token holdings? Since the mainnet Beta went live, there hasn’t been any formal proposal. All parameters have been changed via announcements from the foundation. If only foundation nodes need to agree to a hard fork, what’s the difference from just upgrading directly?
$NEWT is currently around $0.04, down quite a bit from the highs. Some in the community call for a rebound; others call it “a PPT in the compliance space.” I understand that divide. Early token circulation supply can be released in ways that easily get battered by sentiment, with little to do with the protocol’s value. From the technical route, making verification a prerequisite and turning it into infrastructure is a self-consistent logic I rarely see in the compliance track. Can this zero-knowledge proof system plus strategy separation really hold up under pressure from large capital? #newt
Tonight at 3:00 a.m., this semi-final between France and Spain: world No. 2 vs No. 3. In six matches, Mbappé scored eight goals—against Spain, who conceded just 1 goal in six matches. Spear vs shield—who wrote this script?
Let me point out a few details for you to savor.
France’s attack is indeed fierce. In six games, Mbappé hammered in 8; Olise in six matches provided 6 assists. The whole team scored 16. But France has a fatal weakness—at the 2024 Euro semi-final and the 2025 Nations League semi-final, they were sent home by Spain two times in a row. Facing Yamal, Mbappé has won only 2 of their last 10 meetings. Those numbers alone already make you hold your breath for Mbappé.
On Spain’s side, it’s even more ruthless. Unai Simón kept a clean sheet for a stretch of 649 minutes at one point; in six matches, he recorded shutouts in all of them—setting a World Cup record. The 19-year-old Yamal is basically Mbappé’s nemesis; he’s been locking him down. Coming off the bench, Merino delivered match-winning goals as a substitute in two straight games—this bench depth is really scary.
Even more heartbreaking: the semi-final is on France’s National Day. Macron said he’d personally attend if they reached the final. If France loses, that National Day turns into a national mourning.
Here are my random personal predictions—just chatting, don’t take it too seriously.
This match probably won’t be pretty. Spain will definitely control the ball slowly, wearing France down. France will probably sit back and hit on the counter. For the first 60 minutes, it’ll likely be 0-0. Whoever scores first wins. Mbappé’s pace sprinting at the Spanish veteran’s flank is the only chance—but Spain’s back line is too solid. It’s likely to drag into extra time, even penalties.
My feeling is Spain has a slightly bigger chance—63/37. After all, the psychological edge is there: they’ve knocked out France in consecutive major-tournament semi-finals. This team knows exactly how to play France. But for a player like Mbappé—one person can completely change a game. Honestly, it’s really hard to say.
Set the alarm for 3:00 a.m., have the beer ready—who makes the final, we’ll see in the comments section.
#BinanceTurns9 #币安9周年 Nine years of shared adversity—thank you, Binance, for guiding us as we explore the world of crypto and unlock limitless possibilities! From 0 to 9, from trading to the Web3 ecosystem, we’ve witnessed countless miracles together. Wishing Binance a happy 9th anniversary 🎂—let’s Build the future together!
The Change in Authorization Granularity: How Newton VaultKit Breaks Trust into Per-Transaction Verification
A few years ago, I used an automated strategy tool and set up a pretty strict set of rules: a price range, slippage tolerance, and an upper limit on position size. Then the market suddenly went through a period of intense volatility, and during the two idle intervals between trades, the strategy liquidated my entire position. I spent the whole night going through on-chain logs trying to figure out whether the strategy itself was written wrong or whether the execution layer had gone awry. In the end, I found that the strategy’s logic wasn’t the problem. The first trade was compliant, and the second trade was also compliant using the same authorization. But the market changes between the two trades caused the second trade’s actual outcome to completely deviate from what it should have been. Once that authorization was issued, during the gap between trades, there was nothing overseeing or managing anything.
Originally, I only wanted to understand what the point of splitting Intent and Policy in @NewtonProtocol is. I flipped through the developer documentation several times before I realized my previous understanding was too shallow.
When I used to write contracts, I was used to stuffing the decision logic directly into the business flow—authorization, conditions, and execution all tightly bundled together. If the code ran, that was considered good enough. Newton’s design is completely the opposite: Intent describes “what I want to do,” Policy decides “whether it can be done,” and the execution layer only has to run the validation results. At first I thought it was just another layer of abstraction. The more I looked, the more I felt that what it really wants to separate is the responsibility boundaries that developers normally mix together by default.
But this architecture also makes it impossible for me to be fully confident. Following the technology stack down: TEE depends on Intel SGX. Vulnerabilities like Foreshadow and Plundervolt—each round of side-channel attacks is a slap in the face to the word “trusted.” The computational overhead of generating proofs with ZKP is several times higher than that of ordinary transactions. The cross-chain bridge of Newton’s own Rollup is itself an additional attack surface. HTX’s report says the mainnet launch is scheduled for Q3 2025, developer tools in Q4, and global multi-chain coverage by 2026. With four layers—TEE + ZK + Rollup + AI—stacked together, each layer by itself is already a tough nut to crack, so the development iteration difficulty rises exponentially.
What concerns me even more is Newton’s dependence on EigenLayer. Policy execution relies on EigenLayer’s restaking nodes to perform consensus validation—this is a shortcut and avoids building validator verification from scratch. But if the underlying restaking contracts have vulnerabilities, or if a large-scale operator gets slashed, the impact will propagate along the dependency chain to Newton. $NEWT has a total supply of 1 billion tokens, with only about 287 million currently circulating, and 94% has not been released yet. The TGE has only been around for a little over a year, and most of the complicated functionality that supports the valuation is still in the roadmap.
Of course, I won’t dismiss it entirely because of this. If the community project really starts reusing the same set of Policy instead of writing critical decisions back into its own business logic, I would be more supportive of what NewtonProtocol wants to change—the underlying mindset for developing on-chain applications. #newt
I翻到了@grvt_io 的官方文档,翻到“Hybrid Architecture”那节时我停下。FAQ里写得很清楚:“GRVT has a hybrid architecture that is made up of both on-chain and off-chain systems for scalability, security, and privacy.”链下撮合、链上结算。再看数据:600,000笔/秒、亚毫秒级延迟。CEX级速度再加ZK自托管——这组合拳确实漂亮。
但我翻到另一段时愣住了。文档说:“A subset of the off chain actions are pushed to the GRVT chain. These actions are then published as zero-knowledge proofs to verify off-chain transactions on Ethereum.”链下撮合后打包成ZK证明并提交到以太坊。听起来顺,可L2BEAT的风险评估专门点了一句:“Each update to the system state must be accompanied by a ZK proof”。问题就出在这个“must(必须)”上。
ZK证明的生成依赖Boojum虚拟机的特定版本。底层迭代、版本升级,兼容性漏洞也就跟着来了。一旦批量证明验证失效,所有用户的提现、结算都得被堵死。L2BEAT的ZK Catalog还专门追踪各项目的verifier合约,流程是“regenerating Solidity files directly from source code to confirm deployed contracts are legitimate”。他们为什么这么做?因为验证密钥的生成依赖trusted setup,而“SNARKs require a trusted setup”——这就是信任假设。
If Binance is “the player” wearing the No. 9 jersey, then I’m willing to be that “teammate” who has always stood by your side.
Come to think of it, I’m also something of an “old teammate.” Over the years, we’ve gone through so much together—charging forward in bull markets, holding strong during periods of volatility, and never even thinking about walking away in the lows. Watching Binance grow from that youthful “rookie” into the “superstar” it is today, with more than 300 million users worldwide, there’s really no way to put into words how I feel. In these nine years, Binance has turned community voices into tangible product updates, with 198 improvements and 2,354 pieces of user feedback.
What moves me most is the “customer service Xiao He” who always keeps users in mind. For a co-founder to personally reply to users’ DMs and help everyone recover mistakenly transferred assets year after year—this kind of warmth as a teammate is something no candlestick chart can ever capture.
It’s our ninth anniversary, and the new season has already begun. As a teammate, I want to say: thank you for the companionship and trust over these nine years. For the next nine years, no matter how the market changes, we’ll keep standing shoulder to shoulder and together earn our ranks!
The No. 9 player is the Binance of its 9th anniversary—new matches are underway!
Thank you to each and every one of you who has journeyed with Binance to today—players are now on the field. This time, which seat are you in?
Choose your identity: coach, teammate, supporter, host… Share stories, videos, and images related to Binance from the perspective of your role.
💛 Use your story, blessings, or creativity to send an assist to the No. 9 player
Follow the account, and submit your work—forward with #币安九周年 to participate in the event. 🎁 Win a prize as 10 lucky creators are selected; each will receive 99U 🏆 Plus, one additional best work will be chosen for the ultimate prize of 199U
The Cost of Trust Migration: Design and Risks of a Verifiable Automation Layer by Newton Protocol
Last month I asked a friend to manage a small amount of my crypto assets for me, saying it was for grid trading. After half a month, when I checked the account, he not only used 3x leverage, but also lost 40% of the principal in a liquidity pool I didn’t understand at all. My friend feels very wronged. He said, "I think that opportunity was pretty good." But the real issue isn’t whether his judgment was right or wrong—it’s that when I handed over the permissions in the first place, there was simply no way to specify, "Which things you can’t do." I can only choose to trust him, or not trust him. Either I give it all, or I give nothing. That sense of frustration is the same as what I’ve been thinking about recently while paging through @NewtonProtocol materials.
When I was reading the mainnet announcements on @NewtonProtocol , I noticed that the first batch of data partners were RedStone and Credora—one provides oracles and the other provides credit ratings. At first I found it strange. With an on-chain authorization agreement, why weren’t the partners security audit firms?
After thinking it through, I understood. Newton’s Policy Engine is essentially a judge. No matter how strict you write the rules, whether the judgment is correct ultimately depends on the data fed into it. For example, if the price drops below a threshold, liquidation is triggered. If the data source is manipulated or delayed, the rules being written perfectly won’t help. Its credibility is actually two layers stacked together: the operator network on EigenLayer together with zero-knowledge proofs ensures the computation process isn’t tampered with; but whether the data used as the basis for the judgment is correct is a separate, independent issue.
What concerns me even more is TEE. Newton runs its agent on Phala Cloud, with Intel SGX providing hardware isolation, and remote attestation can verify that the agent executed in a trusted environment. But TEE verifies that the environment is trusted—not that the code is free of flaws. If the agent’s code contains malicious logic, TEE will obediently execute it, and remote attestation will still pass. In that sense, TEE may actually stamp a layer of “trusted” approval on malicious code.
There’s also a practical issue. Newton’s core contracts reserve admin upgrade privileges, controlled by the foundation’s multisig wallet. If any multisig member leaks information or colludes, theoretically they can directly change the contract rules. As for the third-party audit status of the contract, it is currently still “none.”
I agree with Newton’s direction of embedding compliance and risk control into the execution process rather than relying on a post-incident pursuit model. But with these three layers of risk stacked together—dependence on external data providers, TEE not auditing code intent, and the core contract retaining admin privileges—I will wait until third-party audits are in place and the agent reputation scoring goes live before considering entrusting it with my assets. #newt $NEWT
A friend of mine who’s into quant trading complained to me the other day: running strategies on a DEX is just too hard—speed can’t keep up, and the slippage hurts badly. He sent me a link and said, “Take a look at GRVT. They claim they’re solving this.”
I went through the official documentation for @grvt_io . GRVT uses a hybrid architecture: “off-chain matching with on-chain stored data, and providing contract-level guarantees for on-chain execution.” The matching runs off-chain to maximize speed; settlement and verification are sent back on-chain for security via ZKsync’s Validium technology. The official numbers are very persuasive: peak throughput of 600,000 transactions per second, with sub-millisecond latency.
But then issues show up. Since GRVT uses a Validium approach, data availability is maintained off-chain by a DAC committee. Unlike a standard rollup that publishes full batches to the Ethereum mainnet, transaction data isn’t put on a public ledger. That does indeed prevent front-running and sandwich attacks. But what’s the trade-off? The underlying granularity of the order book is limited for retail users—quant teams want to capture real-time order flow? They’re out of luck.
Now, the account system is another story. GRVT splits accounts into “funding accounts” and “trading accounts.” The funding account handles deposits and withdrawals with extremely strict permissions; the trading account is what you use to trade. The API only lets you access the trading account—private keys aren’t stored. Security is maximized, but for retail users it’s also too heavy: registering requires binding an email, setting up SecureKey, and if you accidentally clear cached data, you might be locked out.
Even the regulatory angle is interesting. GRVT claims it’s the “first licensed DEX globally.” By end of 2024, it obtained a Bermuda M-class license. But the M-class license is essentially a “modified” license with sandbox-style constraints—its audit transparency and depth aren’t on the same level as the EU’s MiCA or the U.S. CFTC.
My take: GRVT’s technical compromises are genuinely smart, and the front-end experience does feel more like CEX. However, the Validium data transparency issues and the controversy over the real value of the license are hurdles you can’t bypass. I plan to wait and observe the actual liquidity depth after TGE before deciding whether to get in. In DeFi, it’s better to trust the code than the slides. #grvt
Technical Validation and Token Economic Risk Analysis After the Newton Protocol Mainnet Beta Launch
Last month, in a coffee shop in Nanshan, Shenzhen, I was working on a report on my laptop. Two young guys in plaid shirts sat at the next table. One of them stared at his phone and said something that almost made me spray my Americano out: “Once Newton’s PoRW goes live, my mining rig can pay for its electricity by itself—I won’t have to worry about it anymore.” I turned my head and glanced at the screen—there it was, a candlestick chart of $NEWT . The curve that slid from $0.7 all the way down to $0.047 looked like a wound stitched onto the June market chart. To be honest, I initially noticed Newton Protocol out of sheer curiosity: a project whose token issuance in June 2025 saw its market cap climb to $118 million—how did it lose 93% a year later? But after I went home and spent three days reading the whitepaper and technical documentation, I realized what truly mattered to me wasn’t the price at all.
I’ve been working on on-chain automation for almost two years, and I’m increasingly convinced that this space is stuck in a deadlock: if you let an AI Agent manage your money, you have to give it permissions; but once you hand over permissions, it’s basically handing over the keys to someone else. Market solutions either turn the bot into a centralized system, with security relying on nothing more than “good conscience,” or they move computation onto the chain—where the Gas fees are so high that ordinary users can’t afford it.
What impressed me about Newton Protocol is that it breaks the “trust problem” into an executable technical design. Its three core principles—Scoped Autonomy (limited autonomy), Verifiable Integrity (verifiable integrity), and Earned Reputation (reputation accumulation)—connect pre-constraints, in-process verification, and post-penalties into a closed loop. The AI computation runs inside a TEE; ZKPs are used to generate verifiable proofs; then EigenLayer’s AVS network samples and rechecks. Operators must stake NEWT tokens—if they act maliciously, they’re directly slashed and their assets are forfeited. This mechanism doesn’t depend on “team goodwill,” but instead hardens the game rules through adversarial constraints. I think the direction is right.@NewtonProtocol
But after going through the docs, I also found some issues. ZK verification Gas costs around 230k, which is more than ten times that of a normal transfer. The cost of complex strategies doubles as well, and ordinary users simply can’t use it. What worries me even more is the permission expiration problem: session keys have an expiration time, but the documentation doesn’t mention any “automatic revocation on expiry.” An attacker can capture a ZK proof near expiration and submit it repeatedly, enabling unlimited calls to the user’s authorization. Once a ZK proof is generated, it’s verifiable; the system doesn’t check whether the proof has been used.
Also, although the mainnet Beta has launched, there are still very few advanced models that can generate large amounts of native Gas consumption on-chain. The ecosystem hasn’t truly taken off yet, so it’s still an unknown how much real business activity could burn circulating supply to offset token release pressure.$NEWT With total supply of 1 billion tokens and initial circulating supply of 215 million, there is objectively a long-term selling/pressure effect.
I won’t blindly go all-in just because I like the direction. Verifiable automation is the inevitable path for the industry, but ZK costs, permission risks, and ecosystem deployment data—all of these need continuous tracking. Let’s wait until real usage volume comes in.#newt
I stumbled upon project @grvt_io by chance. It claims it wants to build “the top financial institution on the blockchain,” and even obtained a Bermuda license. Honestly, my first reaction was disbelief. But when I looked through its official documentation, the more I read, the more interesting it seemed.
What attracts me most is its hybrid architecture. The official help docs put it clearly: “GRVT has a hybrid architecture that is made up of both on-chain and off-chain systems for scalability, security, and privacy.” Off-chain matching and on-chain settlement, with a claimed order-matching speed of 600,000 TPS and sub-millisecond latency. The official blog further explains that this architecture is “built as a ZK Stack validium,” using zero-knowledge proofs to protect transaction privacy, with Ethereum handling final settlement. Some people in the community say the experience is “almost CEX-level”—I agree with that assessment, but the real performance on the mainnet still remains to be seen.
Let’s talk about the 2026 roadmap. The official goal is “unifying the entire capital lifecycle around a single programmable balance,” where one balance serves as both margin, yield, and trading. It plans four major layers: earnings, investment, trading, and payments, and also intends to integrate L1 liquidity such as Aave through ZKsync Atlas. The blueprint sounds sexy, but the implementation difficulty is certainly not small.
GRVT’s compliance path is definitely a plus. It secured a Bermuda Class M license by the end of 2024, and already obtained a VASP authorization in Lithuania in 2023. The founders come from top-tier investment banking, and the team’s background is solid.
But I also have some reservations. TVL currently is only around $7–8 million, and some analysis suggests that “the lack of trading activity and on-chain data is not short-term noise, but a structural issue.” Although the tokenomics model has been published—total supply of 1 billion tokens and a 28% community airdrop—its specific distribution mechanism hasn’t been fully implemented yet. Adjustments to the airdrop rules have also sparked some community discussion.
The direction is right—the road ahead is long. The hybrid architecture sounds great: the coordination between off-chain matching and on-chain settlement, the performance overhead of zero-knowledge proofs, and the balance between regulation and decentralization are all tough challenges. Once the mainnet is truly running and the data is out, then we can judge whether it’s a real transformation or just a good story—not too late. #grvt
Newton Protocol’s Verifiable Automation Narrative and the Hardware-Trust Dilemma
Honestly, the first time I came across @NewtonProtocol , I just swiped past it. “On-chain AI agents” and a “verifiable automation layer”—these narratives are things I’ve seen way too often in the crypto space. In ten projects, eight tell roughly the same story. It wasn’t until one night when I couldn’t sleep and ended up reading the whitepaper that I noticed its underlying system uses a double safeguard: TEE plus ZKP. It also introduced a mechanism called zkPermissions, so users don’t have to hand over their private keys to the agent, while each step can still be verified. Only then did my finger stop and I started reading seriously. Let me start by saying what I think is worth appreciating. Newton Protocol’s positioning is very clear: it builds a verifiable automation layer for on-chain economics. Users can define the behavioral boundaries of AI agents via zkPermissions—for example, limiting spending, approving specific DEXes, or setting transaction time windows. The agent executes tasks inside a TEE “encrypted little black box,” and every step of operation generates a ZKP to prove to the chain that “I didn’t touch your assets recklessly.”
I’ve been researching derivatives trading on-chain recently, and I found project @grvt_io quite interesting. To be honest, the Perp DEX space is already crowded—old players are firmly entrenched, so what kind of “new magic” could a fresh project actually bring? But after digging through the documentation for a few days, my view changed.
What really impressed me about GRVT is its hybrid architecture. The official technical docs explain it clearly: “GRVT adopts an architecture that matches and stores data off chain and provides smart contract level guarantees of their execution on chain.” In other words, order matching runs off-chain, with speed comparable to centralized exchanges, while settlement and verification happen on-chain, with smart contracts acting as a backstop. The official claims it can reach 600,000 TPS with sub-millisecond latency. I think this approach is genuinely pragmatic—more reliable than pure AMMs, which can be big slippage culprits.
But technology alone isn’t enough. GRVT also introduces a “single balance” design, aiming to let the same pot of funds both earn yield and serve as margin. The official blog puts it this way: “The same deposit can simultaneously earn yield, back a margin position, and even stay exposed to spot price appreciation.” That sounds great and addresses the problem of fragmented capital. Still, I’m a bit uneasy—if this complex mechanism runs in practice, can risk management and liquidation really keep up? Hard to say.
GRVT reportedly holds a Class M license from the Bermuda Monetary Authority, claiming to be the first DEX to obtain a license. Compliance is a double-edged sword: institutional capital may be willing to enter, but KYC blocks anonymous users— and in places like Hong Kong, it’s even inaccessible directly.
I also skimmed through the roadmap. In 2026, it plans to integrate Aave and other L1 liquidity via ZKsync Atlas, and it also wants to launch perpetual contracts for stocks and forex. The ambition is big, but the TGE has been pushed from late June to July, and some people in the community are already questioning delivery capability.
Overall, I think GRVT is worth keeping an eye on. The technical foundation looks solid, and the compliance path is fairly clear. But don’t rush in—after the TGE, let real data and community feedback speak for themselves. A whitepaper can be beautiful, but only the real-world rollout counts. #grvt
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