Crypto-First21

Most blockchains force a trade-off: you either get full transparency, where everyone can see everything, or full privacy, where nobody can verify what's happening. Dusk tries to walk a third path. It tries to make ownership private while keeping rules auditable. That balance explains why it has gained attention in late 2025 and early 2026, but most certainly from financial institutions that need both confidentiality and regulatory clarity.
Having watched markets cycle through privacy hype, regulatory crackdowns, and institutional hesitation, Dusk intrigues me in that it does not pretend the rules aren't there-but builds privacy around them. After nearly six years in development, Dusk flipped the switch on its mainnet in January 2026, touting what's described as "auditable privacy." Simplified: transactions and ownership remain hidden from the public, while regulators and otherwise authorized parties could verify compliance if necessary.
To see why, it's useful to consider how, in regular blockchains like Bitcoin or Ethereum, balances, transactional amount, and wallet history are publicly visible. While visibility can be useful for establishing trust, it also means that anyone and everyone can see sensitive information. When companies have publicly visible shares or publicly traded financial activity, anyone can see exactly what they are doing in real-time. This level of visibility, of course, is not acceptable in regular finance.

Traditionally, the kind of thing we call “privacy coins” has taken the reverse path. Not only do we fail to authenticate some information, we fail to authenticate most. This, of course, protects users, but it causes major issues in regulated markets. Banks, stock exchanges, asset-issuing companies, and the like cannot function on platforms on which they cannot verify their own observance of laws such as KYC, anti-money-laundering laws, and securities laws. And it's here
Dusk leverages zero-knowledge proofs, which are cryptographic means that allow a party to prove the veracity of something without disclosing the underlying data. This would be like proving you are above 18 years old without showing your date of birth. In Dusk, this notion extends to ownership, identity, and transaction rules: you can prove a transfer followed regulatory requirements without disclosing who you are or how much you transferred.
The most tangible example is the work DUSK does in tokenized securities. In cooperation with regulated platforms around Europe, DUSK hosts the actual financial assets directly on its blockchain. By early 2026, over €200 million in tokenized securities were slated for deployment with licensed exchanges. These assets do require strict compliance: investors are required to meet eligibility rules, trades must be in accordance with jurisdictional laws, and regulators must have the ability to audit records. DUSK enables all of this while still keeping individual balances and transaction histories private from the public.
What makes this possible is selective disclosure. Data is encrypted by default. Only authorized parties-regulators or auditors-can decrypt or verify specific parts when this is legally required. Everybody else sees only the cryptographic proofs that the rules were followed. This maintains confidentiality, without breaking trust.
In November 2025, Dusk launched the Hedger Alpha system for confidential transactions on test networks. This let users privately send assets while maintaining cryptographic audit trails. That may sound technical, but the implication is simple: financial activity can finally be private without becoming invisible.
To put things in perspective, let's compare three common blockchain models. On fully transparent chains like Ethereum, ownership is public, compliance is easy, but privacy is almost nonexistent. On full privacy-first chains like Monero, ownership is hidden, privacy strong, but regulatory compliance is extremely hard. Dusk wishes to sit in the middle: ownership is private, compliance rules are executed in code, and audits are possible through cryptographic proofs. This is where real-world finance actually operates.

What makes that suddenly trend so is the regulation. Not only has the MiCA regime in Europe and the DLP been activated, which is requiring financial institutions to seek blockchain-type settlement systems, but the GDPR regarding the proper handling of data cannot have financial information publicly available. You need a solution that meets all the necessary and correct regulation, and Dusk is one of the few blockchains designed for the new world verses an adapted world.
Another reason is the increasing demand for tokenization of real-world assets, wherein investment analysts project that the market for tokenized securities, bonds, and funds could reach $10 trillion by 2030. But this is going to happen only if institutions trust this infrastructure. As of January 2026, the futures open interests on Dusk were at nearly $48 million on a single day, indicating an increasing market focus on this cryptocurrency trading infrastructure. As usual, various price movements are temporary, but the increasing open interests indicate that market players are gradually understanding the underlying tale of this price movement.
From a personal point of view, I see that the most obvious thing is a shift in wording. Just a few years ago, we were all about anonymity and censorship resistance. Now we are all about compliant privacy. That is hard. That is hard cryptographically, hard protocol-wise, and hard-to-achieve. That is well reflected by Dusk’s six-year development.
There’s also the philosophical aspect. Real ownership implies being in control without being exposed. It implies being able to own up, prove your property, operate as you wish, and still operate under rules, without being exposed to the world or informing them of your entire life. And on this, Dusk gets us much nearer than most other systems I’m aware of.
Progress has been steady, not flashy. Mainnet was launched last January 2026, making confidential smart contracts possible. Integrations with data oracles and cross-chain bridges are in the pipeline for the first half of 2026, while regulated exchanges are slowly adding tokenized assets to their lists. There are no instant gratification achievements when it comes to infrastructure, though. The point here is the live building blocks are now out.
Of course, challenges remain. Cryptographic systems are complex, regulatory interpretations change, and adoption takes time. The direction, though, is clear. Financial institutions aren't asking anymore if blockchain can be compliant; rather, they're asking which infrastructure will let them operate privately while staying within the guidelines.
That brings us back to that question of confidential ownership with auditable rules. It sounds very abstract, yet it describes something very, very real. It means holding shares, bonds, or digital assets without public exposure, while proving to regulators that everything is above board. It means businesses operate competitively without spilling their strategic beans. It means individuals can keep their financial privacy without stepping outside the rule of law.
In markets, the biggest changes usually occur quietly, in plumbing and infrastructure. Retail traders chase narratives; institutions chase reliability. Dusk's approach falls squarely into that second category. Whether it becomes dominant or not, it speaks to where blockchain design is going: not toward absolute transparency or absolute opacity, but toward selective, programmatic trust. And in a digitizing, regulating financial world, that may prove to be the most valuable feature of all.
@Dusk #dusk $DUSK

In crypto, it can be easy to get lost in all of the roadmaps, all of the whitepapers, or all of the promise. The thing that perhaps is most important for someone who has spent time trading or building is really quite prosaic: who is using this stuff now, and why. Perhaps most interesting is taking a look at how infrastructure development leverages its journey from idea to deployment. Walrus is perhaps an interesting case.
When Walrus finally went mainstream last March 27th, 2025, after announcing the arrival of their mainnet, it indeed faced stiff competition given that numerous decentralized storage-based technologies were already available. Simply put, Walrus promised to store very massive data files in a decentralized manner, which was also affordable, secure, and safe, while also allowing developers to do so without the need to involve centralized cloud providers. Less than a year after, Walrus, just last January 2026, was already assisting more than 120 active projects while also hosting 11 completely decentralized websites. We learn here that surely, something big must be cooking under the surface.

To get a handle on why Walrus is getting attention, it makes sense to take a step back and think about what pain Walrus is helping to relieve. Many blockchains are fantastic at transacting, terrible at storing large files, and most crypto applications will quietly and shamelessly revert to the use of centralized cloud storage like AWS or Google Cloud, which reintroduces the very problems blockchain was meant to help with. Walrus fills this pain point with the ability for applications to use the network as a decentralized data storage system.
From a technical standpoint, Walrus utilizes a technique where files are divided into pieces that, upon being encrypted, can be stored separately in numerous "independent storage nodes. The original files then have the capability to be reconstructed even if some of these "independent storage nodes become unavailable. The present approach does away with replication across numerous copies, which consumes unnecessary storage space. Walrus utilizes advanced erasure coding - that is, only about 4.5 times the original data size needs to be made available for maximum reliability. For context, various decentralized storage systems may need 10 or more copies for maximum safety. This is where cost/storage speed" poses major bottlenecks. This matters because storage costs and speed are the principal barriers to adoption.
One of the most telltale signs of real-world usage is media. In mid-2025, for example, a prominent Web3 media platform called Decrypt began storing its articles and videos on Walrus. In effect, this content is directly served by Decentralized Web technology, not by a traditional web server. For users, this is equivalent to status quo. However, what's underneath changes quite profoundly, in terms of issues like censorship, reliability, and long-term content longevity. At around the same time, TradePort, which is currently the most popular NFT marketplace on Sui, also stored its dynamic NFT data on Walrus. The purpose here was to allow artists and others to evolve NFTs over time without being beholden to a centralized server.
Another segment of Industry that is witnessing increased adoption of Walrus is Artificial Intelligence. At its core, Artificial Intelligence applications rely on big datasets. Controlling access and ownership of this information is fast becoming an economic imperative. In 2025, applications such as Talus began utilizing the power of Walrus for verifiably storing datasets and memory associated with AI agents.
Another domain which Walrus has good traction in, and will continue in the future, is AI. This is primarily due to the fact that current generations of AI systems run on massive amounts of data, and the control that will be had over that data, in the future, will be one of the most questioned economic issues. It has been noted that, starting in 2025, projects such as Talus will commence the use of Walrus for the storage of datasets and AI memory in verifiable and permissioned fashion, such that the integrity and verifiability are derived without the need for a single company to control the data.

A good real-world example for this problem is the field of healthcare. There is a project which utilizes the benefits provided by building on top of the Walrus, the CUDIS system, which gives users the right to store their personal health data and specify precisely who is allowed to access it. Instead of the hospital or the provider being the owner of the data, the end user in the health field is the true owner and has the right to share the data anonymously to benefit from the provided revenue. This type of system is hard to effectively implement for conventional systems because of the difficulties of access controls, privacy, and accountability. Walrus aims to alleviate these difficulties by embedding these permissions within its own data layer.
Another area that has been quietly growing is the use case for what are known as decentralized websites. Walrus was, at the last update in December 2025, host to 11 live websites, which may not seem like a large number, but what this essentially means is that with websites, the infrastructure costs for developers can be cut down, and there will not be any single entity that has the control to shut down the website.
From the point of view of the markets, the volume of the investments may also imply the extent of the long-term beliefs. Walrus raised $140 million in a private token sale proposed by Standard Crypto in the domestic market in the early months of the year 2025. On top of the investment and venture capital ventures, Andreessen Horowitz, Electric Capital, and Franklin Templeton Digital Assets all invested in the venture. Generally, big funds avoid pure speculation, focusing on infrastructure that can hold up an entire ecosystem. The funding implies that decentralized storage should be considered as an infrastructure layer, much like how cloud computing changed the Web2 landscape.
What ultimately makes Walrus interesting or different from traditional or older forms of decentralized storage isn’t just the economics; it’s programmability. For example, with older solutions like IPFS or Filecoin, the focus has traditionally been on the storage of the file itself. Walrus has much deeper interaction with the blockchain. For example, with Walrus, a team can essentially store a piece of information and allow only that information to be accessible for six months. At the same time, they can automatically charge users for that information.
Looking at the similarities and differences with a centralized cloud storage solution like Walrus makes the former a little clearer. While a centralized solution provides speed and convenience, the price is control, privacy, and lack of access to censors. For our decentralized solution, users are willing to lose a little speed for the advantages of decentralized solutions. Compared to old decentralized storage systems, Walrus reduces storage overheads considerably and the recovery is also considerably faster, making it usable for production environments and not just experimentation, which is the middle ground where adoption is often reported to happen.
While it may be true that fast-paced narratives around trader sentiment have the most influence on prices, as a trader myself, I think these infrastructure narratives have a lot more going for them. As has been noted, the investment in memes, trends, and hype certainly has a high turnover rate, while the compounding rate at which it all gets used takes a much slower pace. The fact that over 120 active projects have popped up on the Walrus blockchain within nine months of its mainnet release hardly constitutes explosive growth, and it doesn’t quite have the same importance as it's described.
Why it’s trending now: The first reason for Walrus trending now has to do with its timing. The need for data storage in AI, especially at such a colossal level, is exploding. The need to lend a regulatory edge to data’s owners, i.e., users, is also rising. And finally, the crypto infrastructure is moving away from purely financial speculation. Walrus is at the crossroads of all three. In late 2025, there were some announcements made around partnerships for AI and enterprises. Walrus was again put back into the public eye. But what is really occurring beneath the surface is developer traction.
Looking ahead to 2026, some exciting innovations are perhaps being developed in places outside the crypto space. Notably, healthcare data, autonomous AI entities, decentralized publishing, and enterprise compliance tools are some spaces where decentralized storage solutions are perhaps being developed behind the scenes to eventually replace existing centralized infrastructure. That is what Walrus is building towards, the plumbing for all this.
Rather, the world always ends up adopting the real thing, albeit at its own pace and without any great fanfare. Walrus today is no fantasy; Walrus today is living its best life deploying media assets, NFTs, AI sets, and health information. If you’re paying attention to the world’s infrastructure trends, you know where the real value is at the end of the day.

@Walrus 🦭/acc #walrus $WAL

Most crypto infrastructure stories sound exciting in theory and disappointing in reality. Storage networks promise scale but struggle with speed. Execution layers promise speed but collapse under real data loads. For once, Walrus and Sui feel like two pieces that actually fit together. And when you zoom out, the decision starts to make a lot of sense.

If you’ve been in this market for a while, you’ve probably noticed how storage quietly became one of crypto’s biggest bottlenecks. In early blockchains, data was tiny. Transactions were simple. State updates were small. But by 2024, and in 2025, blockchains are hosting NFTs, gaming, AI, social media, and real-world files. End of story. But wait – it turns out storage wasn't an afterthought. It was the actual problem.

However, this is where Walrus comes in to save the day, as it was created by Mysten Labs, which developed Sui, with its official public mainnet launch happening on March 27, 2025. By that point, Sui had already demonstrated that, when employing their method of parallel execution, they could process transactions at an enormous scale, with sustained throughput of over 100,000 transactions per second on their production benchmarks. Of course, speed is not the only concern when dealing with data-intensive workloads, especially when one needs somewhere to store these large blobs of data affordably, quickly, and safely.
This, in essence, explains Walrus’ decision not to simply build yet another decentralized Dropbox. Walrus chose to build programmable storage. Essentially, programmable storage allows data to not only be stored but also be interacted with. Simply put, apps can, in fact, read, write, authenticate, change, etc. large data sets directly inside onchain transactions. While perhaps not as exciting as it sounds, it's much, much more significant than it could initially be interpreted to be.

That's where Walrus steps into the picture. Walrus is a creation of the same team that built Sui. Walrus has officially announced the mainnet. As the team behind Walrus suggests, the mainnet became publicly accessible on the 27th of March, 2025. This has been a carefully timed unveiling. As can be anticipated following the success and large-scale transactions that Sui has successfully processed with the ability to achieve a continuous transaction rate greater than 100,000 transactions per second, speed without a proper storage facility would only be half the job.

This is why Walrus didn’t just build another decentralized Dropbox. It focused on programmable storage, meaning data is not just stored, but can be interacted with by smart contracts. In simple terms, apps can read, write, verify, modify, and manage large data files directly inside onchain workflows. This matters far more than it sounds. It turns storage into an active part of execution, instead of a passive archive.

Why does this require Sui specifically? The main reason is that most blockchains execute these types of transactions sequentially. When storage is rapid, execution becomes a limiting factor. With Sui, however, independence and parallel execution allow many storage actions, payments, and contract calls to actually happen in parallel, rather than having to wait for a sequence. With Walrus, storage and execution scale without competing or conflicting.
That alignment explains why Walrus was built as part of the Sui stack instead of as a generic multi-chain service. Storage and execution needed to co-evolve.

The technical innovation inside Walrus also deserves attention. Its core encoding engine, called Red Stuff, uses a two-dimensional erasure coding model. In simple language, it splits data into fragments in a way that lets the system recover files even if large portions of the network go offline. According to research published in mid-2025, Walrus achieves strong security with only about 4.5x replication overhead, compared to 10x or more in many decentralized storage systems. This implies that storage costs remain low, while at the same time, data access speeds increase.
Walrus had crossed 120 live projects by December 2025, had 11 decentralized websites, and was storing large-scale NFT metadata, AI data, and content for platforms like TradePort and Decrypt. All this may not seem like a big achievement compared to Web 2.0 giants, but for decentralized platforms, this kind of usage in just under a year after mainnet deployment was a big achievement.
This traction is what also enabled the institutional funds that followed suit. In fact, in March 2025, Walrus invested $140 million alongside major funds like Franklin Templeton and others, led by Standard Crypto. That $140 million was not invested in hype alone. It was invested in infrastructure for data workloads to cater to AI for the next decade.
That is where timing becomes critical, and that is exactly where on-chain AI agents, autonomous workflows, and machine learning models have defined the significance of storage.
@Walrus 🦭/acc #walrus $WAL

Most people know blockchains as a place where money flows and tokens change hands. Yet, over the past two years, something more profound and important has also been emerging: a place where rules around data, storage, and long-term trustworthiness are defined and enforced by code rather than trust. Walrus is perhaps the most demonstrable example of such a development, and its underlying approach is also one of the more evident examples around storage itself.
In early 2025, a significant milestone was passed by decentralized storage systems. Using data from Messari and Nansen, web3 application storage demand exceeded 30 petabytes, consisting mainly of data from artificial intelligence datasets, non-fungible token media files, gaming assets, and blockchain histories. The approach traditionally taken by decentralized storage systems, including Filecoin and Arweave, had difficulty scaling in an cost-effective manner and thus depended largely on brute force replication techniques, which caused storage costs to skyrocket in a short time. Walrus had entered a space in which storage providers and replication techniques are not leveraged, and instead, storage laws are enforced cryptographically.
Fundamentally speaking, Walrus is a storage system that is built to store large amounts of unstructured data types also termed as "blobs." Blobs are types of files that are not best stored in a blockchain because they are large files which can vary in type and can include items like video and image files. Rather than having nodes store a copy of a file of a particular type, Walrus makes uses of a custom coding style termed "Red Stuff," and what is so unique about "Red Stuff" is that nodes are constantly forced to prove that they are holding their assigned pieces; if they are not able to do so, they are heavily penalized for their activities.

This is where the code for the storage policy begins. Again, unlike with traditional cloud storage, where the enforcement of the policy is through contract, audit, and law, with Walrus, the enforcement happens with the algorithm and contract. When the user sends the data to the cloud, the network generates a proof that the sending of the information happened correctly. This proof is stored in the contract. After that, the storage nodes are periodically expected to answer random challenges that check the storage of the information. If the nodes fail to answer too many of these, they are slashed, meaning the nodes are automatically and mechanically forfeited.
To put it simply, Walrus does not ask nodes to behave truthfully. It forces them through mathematics and economics!
To make sense of the above assertion, it helps to think about the conventional nature of storing information. Usually, a conventional blockchain involves the replication of all data. This is secure but also inefficient. For example, the need for storing a terabyte of information could necessitate the allocation of more than twenty terabytes of space. Filecoin innovates beyond the conventional through the application of proof-of-storage. However, the application of replication is basically central.Walrus, however, approaches things a bit differently. Where its Red Stuff encoding reduces replication down to 4.5x, storing a single terabyte of data only necessitates 4.5 total network storage, a small fraction of what other systems have to recover. Furthermore, when tested and announced publicly around mid-2025, its recovery speeds are 5x greater, utilizing fewer bandwidths during repair.
This is what it ultimately comes down to for storing the rules.
A reduction in replication equates to a reduction in costs but increases risk because if many fail, data could be lost. This issue is addressed in Walrus in the sense that storage guarantees are baked into the protocol. The storage nodes must stake their WAL tokens in order to play a part in this. Their reward comes from their uptime performance, and honesty; their losses are direct and instantaneous if they perform badly.
The reduction of replication also leads to lower costs; however, there will also be a greater chance of jeopardizing the information. Walrus is able to avoid such an issue due to its guaranteed storage protocol. For the nodes that store information to be able to participate and earn money justly, the nodes will be required to stake the WAL tokens.
The WAL token plays a critical role in this model as users pay for data storage for a specified time using WAL, which then accrues on nodes gradually, thus providing them with compensation for storing data as opposed to just holding it. Should nodes vanish prematurely, they stand to forfeit funds as well as part of their stake. Thus, there develops a huge link between economic gain and data reliability through this model.

August of 2025, in one of the reports published by Walrus, it was noted that the number of storage nodes that are currently participating in the mainnet of the network exceeded 1,800, while the nodes had an uptime of higher than 99.3 percent. Perhaps more important is the fact that the network is able to accommodate upload speeds higher than 2 gigabytes/second.
What’s interesting about Walrus is its approach to treating storage as a malleable resource. The stored blob can be considered an object that’s placed directly onto the Sui blockchain. You can create smart contracts that can test if the stored information exists, make it last longer, or even eliminate it under certain instances. This provides plenty of possibilities. Consider NFT platforms that can see royalties based upon certain longevity guarantees, AIs that can test if training information exists, or games that can delete assets if they’re no longer being utilized. It’s no longer static.
What’s significant is that infrastructure narratives tend to last longer than hype narratives. For example, in 2021, tokens focused on fast transactions and low fees were widely talked about. Yet in 2024 and 2025, data availability and storage seem to creep up and gain attention because of their connection to AI and related developments in on-chain media. In 2025, spending in decentralized storage exceeded a rise of over 160 percent year-over-year according to CoinMetrics data, compared to an 18 percent increase in volume in DeFi trading.
The most interesting thing for me in Walrus is the enforcement model. Conventional blockchain systems use social consensus and governance elections for dealing with any misbehavior in the network. Walrus uses math, randomness, and economics for this purpose. Walrus does not debate whether a node has behaved correctly or not. It just measures the behavior cryptographically and acts accordingly. So, fairness is mechanical, and this is very rare in distributed systems.
Of course, there remain some challenges that must be addressed. For example, running reliable storage nodes demands strong hardware, bandwidth, and operational discipline. And the system must resist issues such as long-term "data decay," legal requirements, and regional network volatility. However, initial statistics point to steady improvements. Walrus has released several protocol upgrades since its public debut in mid-2024, its nodes have seen performance improvements of close to 40 percent, and the network has developed its layers of encrypting the data through its 'Seal' initiative.
Narratives are a feature of markets; they rise and fall. Infrastructure may not grow or fall so dramatically but accumulates steadily over time, a relentless tide of change. Storage is not a glamorous space in tech terms. It’s unlikely to ever trend in social media or elsewhere. Nevertheless, all digital activity depends ultimately on storage.
Walrus is creating something akin to a decentralized operating system in which rules governing storage are built-in and pricing and availability are predictable and measurable.
If the last decade has been about making money without banks, then perhaps the next decade or two will be about safe storage of data without trust in anybody. Walrus, by enforcing storage policies using code, presents a glimpse of the future of that process.
@Walrus 🦭/acc #walrus $WAL

Most people still think that blockchain competes on scalability. In 2026, that seems quaint. It’s not innovation or scalability that’s important anymore—it’s execution: How well does a network move actual value? How well does a network handle a high volume split? XPL is right in the middle of this upheaval, and what’s been happening in its prices is only a small part of this larger narrative.
The concept of an execution layer is simple. It is the part of the blockchain that actually gets the transactions done, the smart contracts, and then gets the results back. In the old systems, this was an integrated network, where the execution, the settlement, the storage, and the consensus were layered one on top of the other. This was fine when the blockchains were small in number.
Ethereum illustrated this problem in 2021 and 2022. Behind every spike in NFT minting and DeFi liquidations, fees busted through the $50 barrier on a per-transaction basis. Solana moved in the other direction, prioritizing raw transactions, and its frequent crashes in the first year encouraged us to understand the trade-off between raw performance and sufficient fault tolerance, especially in a safety-critical area such as our code runs in.

To the best of history in the BlockChain industry, when the mainnet of XPL was launched in September of the year 2025, the initial one-hour stablecoin deposit was $250 million. The one data point speaks more than any slogan can speak in terms of checking the capability of the Execution Layer for a large-scale money transfer, which was successfully tested by the end-users of the first kind of mainnet in the world.
Why is this execution a problem? In other words, what makes it so difficult to move value reliably in a decentralized network? The standard blockchain model is a batch processor, and their transactions are done in batches, or “blocks” that must be propagated and validated on dozens or hundreds of machines. Each additional step increases latencies, and each and every detour brings with it a whole line of potential hazards. Layer one execution protocols attempt a refactoring of this whole process in order to facilitate smooth and trust-free execution..
One of the main focuses of XPL is the execution of stablecoins. This may seem like a very specific task for a blockchain network. However, the reality is that right now, stablecoins are the dominant players when it comes to actual blockchain transactions. It is no secret that more than 70 percent of all transactions that were processed through the blockchain network in 2025 were stablecoin transactions. This matters, because the numbers mentioned above are actual economy values. A layer of execution only actually matters if the people using the layer trust it
One such example is the integration of the cross-chain liquidity system called USDT0 that belongs to the company called Tether. USDT0, as of January 15, 2026, processed more than $63 billion in transaction volume across 18 interconnected blockchain networks, and XPL was identified as one of the main execution paths. What this means is XPL is more than just theory – it’s actually facilitating the flow of substantial amounts of capital throughout the crypto space.
As of January 22, 2026, XPL processes over $100 million in daily trading volume, with roughly 1.8 billion tokens circulating out of a total 10 billion supply. That gives it a real-time market capitalization near $230 million. These numbers are important because they show real economic activity. Execution layers only matter if people trust them with money.
What makes execution layers different today compared to a few years ago is specialization. Instead of trying to serve every possible use case, newer networks design their execution engines around specific workloads. XPL does this for stablecoins and payments. Other chains may target gaming, NFTs, or AI computation. This division of labor is starting to look more like traditional financial infrastructure, where different systems handle clearing, settlement, custody, and compliance separately.
In understanding the positioning of XPL, a brief discussion of Ethereum and Solana, two other familiar blockchain networks, is in order. While Ethereum is committed to achieving the highest level of decentralization and an unshakeable level of security, the underlying transaction processing layer is only able to process 15-20 transactions in a second. Solana focuses purely on achieving the highest transaction processing speeds, claiming a processing rate of thousands of transactions in a second, but functioning only with the most specialized equipment and in highly optimized ways.
So, Ethereum is basically a global courts system: slow, costly, but incredibly secure. Solana is more like a high-frequency trader: fast but tough to work with. XPL is more like a global payment switch: built for constant throughput, rather than to enable all possible smart contract experiments.
The reason why there is a recent interest in XPL is not because of hype but because progress is being made. In October 2025, mainstream DeFi protocols started incorporating their work right into its execution layer and implemented fixed-yield tactics and stablecoin routing in an auto-router. Then in January 2026, a multi-week XPL creator competition was started by Binance, handing out 3.5 million tokens and bringing in a whole new level of users and transaction activity.
Another, even more subtle, reason that traders care is related to unlock schedules of tokens. About 88.8 million XPL tokens, or 0.9 percent of total supply, will unlock on January 25, 2026. Such events in regular markets are known to cause market volatility. However, in execution value projects, unlock events further validate demand for the underlying network. This helps execution value accrue if transaction volumes increase at a faster rate.

Personally, it has been a humbling experience to observe how execution layers have developed during the last ten years. There was a promise of payments happening in an instant and happening worldwide. In truth, payments took minutes, and the cost was high. Today, for the first time, we find ourselves on the cusp of a new era, with the possibility of transactions becoming almost invisible, like in traditional finance but without its middlemen, and XPL is a step in that direction.
One question keeps coming up: does execution alone create long-term value? The answer depends on whether usage becomes habitual. Payments networks succeed when people stop thinking about them. Visa did not win because it was exciting. It won because it worked every time. Execution layers in crypto must reach that same level of boring reliability.
As someone who has been following execution layers, it has been an eye-opening process the last ten years. Bitcoin's initial vision was for zero-conf, global payments. In practice, there were minute waits and considerable charges. Now, for the first time, we're able to look at a system that provides transfers almost inconceivably close to instantaneous, as if it's traditional finance, but without an intermediary system; systems like XPL, which is a result of learning from the school of hard knocks.
Execution layers are where crypto meets reality. They turn ideas into transactions, and transactions into trust. XPL is not redefining what blockchains are. It is refining how they work.
@Plasma #Plasma $XPL

The metaverse promises real-time digital worlds where millions of users move, trade, create, and socialize at the same time. That sounds exciting, but it also creates a technical reality most blockchains were never built for. As someone who has watched blockchain infrastructure evolve since the early days of Bitcoin, I’ve seen the same pattern repeat: new use cases arrive, and old systems start to show their limits.
The metaverse is not just about tokens and NFTs. It is about persistent environments. These are worlds that need to stay alive every second, process constant updates, store large files, and react instantly to user actions. In 2025, global metaverse activity crossed an estimated 400 million monthly active users across gaming, virtual worlds, and enterprise simulations. Real-time platforms now generate terabytes of interaction data daily. That scale changes everything.
Traditional blockchains were designed to record financial transactions, not to manage living digital environments. Bitcoin processes around 7 transactions per second. Ethereum, after years of upgrades, averages between 15 and 30. Even fast chains like Solana typically handle between 3,000 and 5,000 in real-world conditions. In contrast, a single popular metaverse game can generate tens of thousands of micro-events per second, from avatar movements to asset interactions and environmental updates.

Latency becomes the first major barrier. In gaming or immersive environments, anything above 100 milliseconds feels sluggish. Many blockchains finalize transactions in seconds, sometimes minutes during congestion. That delay might be acceptable for payments, but it breaks immersion. Imagine swinging a sword, opening a door, or placing an object and waiting five seconds for confirmation. Users simply won’t tolerate it.
Then comes data storage. Metaverse environments rely on massive volumes of dynamic data: 3D assets, environment states, identity records, social interactions, and ownership proofs. Most blockchains were never built to store large files. They only store transaction records and tiny pieces of metadata. All actual content typically exists in an off-chain manner on centralized servers or in a Decentralized system such as IPFS. This creates a tenuous connection between on-chain ownership and what exists in reality. Once a node goes down or a connection fails, assets will “exist” on a blockchain network yet not be accessible in reality in any functional manner.
Another limitation is the cost. On the Ethereum network, the average cost of a transaction, peaking in 2024, stood between $2 and $20, occasionally going as high as much higher amounts. When this is multiplied in the thousands for in-game interactions per user, the viability of the economy fails. Even the most inexpensive blockchain platforms fail when transactions rise in unpredictable ways.

Security and consistency also become harder. Metaverse worlds require constant state updates. When thousands of transactions arrive simultaneously, block reordering, mempool congestion, and temporary forks can introduce inconsistencies. That may not matter much for token transfers, but in persistent worlds, inconsistent states can break game logic, ownership history, and environmental continuity.
Classical blockchains have always been optimized for correctness and decentralization, not speed, storage, and maintaining a state. They perform amazingly in financial settlement systems but not in virtual reality worlds.
This gap is exactly why new infrastructure designs are emerging. One interesting response is Vanar, which started from the assumption that future digital environments would require constant interaction, large-scale storage, and real-time processing.
Instead of treating data as something that must live off-chain, Vanar integrates native on-chain storage optimized for compressed files. At launch, internal benchmarks showed up to 80 percent reduction in file size for typical game and media assets, while preserving verification capability. Instead of storing pointers, the chain itself becomes the data layer.
A latency issue is addressed by employing a high-throughput, parallel-processing-friendly Layer 1 architecture. While exact production figures fluctuate, Vanar’s architecture targets sub-second finality and sustained throughput above 10,000 transactions per second. That moves blockchain responsiveness closer to traditional cloud gaming servers, which typically operate at 20 to 60 millisecond response windows.
For easier comparison, consider an example to understand their functionality. A traditional blockchain network can support 30 transactions in one second with 2 to 15 seconds of confirmation time. It can store metadata of transactions and use external storage for storing files. A high-performance chain like Solana might process thousands of transactions per second with sub-second latency but still offloads most data storage. Vanar’s design pushes toward high throughput combined with native data compression and persistent storage, enabling the chain to directly manage digital environments instead of outsourcing them.

This is important since the metaverse is getting more complex rather than being simple. Enterprise metaverse applications such as training simulation, manufacturing simulation, and healthcare continued to grow significantly in 2025.Siemens and Hyundai showed double-digit increases in their productivity through immersive simulates, although they also indicated that the data consistency/latency environment is a limitation in their infrastructure. Such use cases require digital continuity beyond quick payments. From a trader’s point of view, I am reminded of the early days of the boom in DeFi in 2020.
Why is this trend accelerating now? Part of the answer lies in hardware maturity. Affordable VR headsets, AI-driven content creation, and real-time rendering engines have finally reached consumer and enterprise readiness. Once users can enter immersive spaces easily, expectations change. Lag, missing assets, and broken state transitions become unacceptable.
In Early DeFi boom in 2020, chains struggled, fees exploded, and networks froze. Over time, new architectures emerged that matched new workloads. The metaverse is entering a similar phase. Infrastructure is being stress-tested by real users, not just speculative activity.
One thing I’ve learned over the years is that narratives fade, but engineering problems persist. The core challenge here is not hype. It is math, physics, and bandwidth. Moving massive amounts of state data in real time is simply hard. Chains that adapt at the architectural level stand a better chance of surviving long-term.
Vanar’s response focuses less on marketing promises and more on solving structural constraints: storage, latency, data persistence, and execution efficiency. Whether this approach becomes dominant remains to be seen, but the direction aligns closely with where workloads are clearly heading.
Something that I have learned over the years is that stories have a shelf life, whereas engineering challenges do not. Here, the problem is not hype. It is math, physics, and bandwidth. It is hard to move a lot of state in real-time. Those who are able to adapt in terms of architectures will fare better in this space.
Vanar's answer is less focused on the marketing kind of promise and more on how the structural limitations can be alleviated, such as the need for storing, latency issues, data persistence, and executing efficiently. Only time will tell whether this will be the way the industry leans, but definitely a good trajectory for where the workloads appear to be trending.
Siemens and Hyundai reported double-digit growth for productivity based on immersive simulates, yet they also stated that the consistency/latency data environment is a challenge for them concerning the underlying infrastructure. These are the kinds of applications that need more than just fast money transfers and therefore digital continuity. As far as a trader is concerned, I am reminded of the beginning of the explosion in the world of DeFi last year, 2020.
@Vanarchain #vanar $VANRY

Selective disclosure is the idea that you can prove or share only the piece of information someone needs — and nothing more. Think of it as handing over a redacted page that still proves the point. In blockchains, which were built on radical openness, selective disclosure introduces a more mature idea of trust: verifiable truth without full exposure.
For years, transparency was treated as a virtue in itself. Every transaction visible, every balance traceable, every action permanent. That worked well for simple value transfer, but it breaks down when blockchains touch the real world. Identity, compliance, salaries, trading strategies, corporate balance sheets — these are not things people or institutions want permanently exposed. Selective disclosure emerged to solve that tension by allowing users to prove a fact without revealing the underlying data. You can show you meet a requirement without showing who you are or everything you own.
"Zero-knowledge proofs go further. They enable one to prove the truth of something, like that their balance meets a certain level or that they successfully completed a regulatory check, without showing the actual number or the paperwork," explains computer scientist Cynthia Breul. "In other words, mathematics confirms their honesty without spilling the beans."

This area developed traction over the past two years because regulation and infrastructure finally aligned. Between the years 2023 and 2025, it became evident from government and business statements that public blockchain must enable privacy-preserving verification instead of nothing or something. Simultaneously, the development infrastructure evolved too. Proof systems optimized their performance, storage of credentials in wallets developed further, and standardization allowed varying proofs to interoperate. In the market research study published in 2024, just the market for zk-proofs transcended $1.2 billion, anticipating billions for the earlier 2030s. Markets typically won't commit so much unless something existing is really there.
The progress is palpable. Pilot projects began scaling use cases for selective disclosure for on-chain KYC verification in 2024, where a determination of eligibility was made without keeping personally identifying information on file by either an exchange or a protocol. Proof-of-reserves protocols also developed as a function of time. Rather than revealing a full wallet, some custodians decided to test a cryptographic proof of solvency without revealing addresses as a way to maintain trust with a level of privacy that proved necessary following hot failures earlier in the decade.
However, there are trade-offs that are not considered in shallow discussions. Adding data to the chain enhances auditability and provides immutable proof that violates the right to erasure. Using credentials off-chain provides users with more control and lowers cost, but there is dependency on wallet trust and issuer trust. Use of zero-knowledge-proof-based platforms provides better privacy, but it is computationally intensive and requires infrastructure. In 2025, there would be latency in generating a complex proof that takes seconds to minutes along with expenses.
Let’s use an example to put this in perspective. Full and verifiable disclosure on-chain provides excellent public verifiability and lags only in terms of privacy and integrity risk. Selective and off-chain disclosure enables better cost-effectiveness and user experience, moving the risk to wallets and parties issuing those disclosures. The zero-knowledge method provides data exposure close to zero, taking a hit on complexity and ease of use. There is no straightforward best practice among these. This greatly depends on the verification frequency, data type, and cost that the system is willing to and can afford to absorb.

What’s more relevant for traders, then, is the fact that disclosure is less about ideology than market structure. Those infrastructures that can’t handle privacy-for-compliance awareness will have a hard time bringing in institutions. Those infrastructures that prioritize enhancing privacy but can’t be used will have a hard time bringing in users. What works is the middle. Over the past year, this has been manifest in funding, not price or headlines.
What’s often underestimated is revocation. If a credential has been compromised or invalidated, this information needs to be reflected in the system in a timely and verifiable manner. This is precisely why some credenzias make revocation lists or hashes on-chain and the credenzias themselves off-chain. This is just a good compromise that takes into account reality rather than assuming good key management.
A Selective Disclosure system is only good if it incorporates within the existing work flow. I have observed people take months in developing a good cryptography mechanism, neglecting the way credentials are issued, renewed, or recovered. Some systems that were less complex, emphasizing the issuer, revocation, and simplified interfaces, went live much faster.
Selective disclosure does not eliminate transparency. It refines it. It allows blockchains to express truth with precision instead of brute force visibility. As we move through 2025, expect fewer theoretical debates and more quiet integrations into identity systems, compliance tools, and financial infrastructure. The real signal will not be flashy announcements, but how often users prove something without revealing everything. That’s where this shift becomes real.

@Dusk #dusk $DUSK