Same Gul

I want to start with something that bugged me for months. Everyone kept saying the next Bitcoin supercycle must look like the last one — you know, that parabolic run in 2017 and again in 2020–2021. But something didn’t add up. The rhythm felt wrong. The market isn’t the same animal it was then. And when I started digging under the surface, what I found didn’t just tweak the old story — it suggested a fundamentally different cycle is unfolding.
What struck me first was how easily people fall into pattern‑matching. They see a graph, it looks like a smile, so they assume the next one must be wider, taller, faster. But markets aren’t drawn in Photoshop; they’re driven by incentive structures, participants, technology adoption, regulation, and macro realities. Look at the raw price curves from 2017 and 2021: both soared, sure. But the textures beneath those curves were nothing alike.
In 2017 most of the demand was speculative — retail investors discovering Bitcoin for the first time, easy margin, meme‑driven FOMO. Exchanges were greening up accounts like a wildfire. That era was like lighting kindling; price moved because attention moved. Back then you could buy Bitcoin on a credit card with 0% rates, and people did. Surface level it looked like demand; deeper down it was largely leverage.
Contrast that with today. There’s meaningful staking, custody solutions, institutional participation that actually holds coins for years, not minutes. When big players buy now they tend to keep Bitcoin off exchange. That matters. It changes supply dynamics. In the last cycle, exchange inflows soared in the run‑up — that means potential selling pressure. In the current period, exchange outflows have been steady. That’s not just a number; it’s a texture shift in who holds the asset and how tightly.
Underneath those holding patterns sits a broader macro environment that’s less forgiving than before. Interest rates were rock bottom in 2020; borrowing was cheap. Now rates are higher and real yields matter again. That reworks risk calculus across assets. Bitcoin isn’t an isolated force. It’s competing with bonds, equities, and commodities for scarce capital. That simple fact reshapes market velocity and the pace of inflows.
Understanding that helps explain why the next supercycle won’t be a fever pitch sprint. Instead of a vertical price climb fueled by margin and hype, we may see steadier broadening adoption — slow climbs punctuated by bursts, not single explosive moves. Think of it as a broadening base rather than a sudden skyrocket.
Look deeper at what’s driving demand now. Corporate treasuries are holding Bitcoin as an asset allocation play, not a trade. Some fintech companies offer BTC exposure within retirement plans. That’s not a flash in the pan. It’s structural. When early adopters first piled in, most were under 30, chasing quick gains. Today’s participants include 40‑ and 50‑somethings allocating a slice of capital they’ve managed for decades. That’s a different kind of demand, less reflexive, more measured.
Meanwhile, derivatives markets are more developed. Futures, options, structured products — these allow hedging, liquidity provisioning, and arbitrage. In the last cycle you saw an enormous build‑up of unhedged positions. That’s what made the drawdowns so brutal: when sentiment flipped, margin calls cascaded. Today’s derivatives books are thicker and, crucially, more hedged. That doesn’t mean price won’t fall — it just means a new cycle isn’t as likely to mirror the depth and velocity of 2018’s wipeout.
People counter that Bitcoin’s stock‑to‑flow ratio still points to massive upside. I get it — fewer coins are being mined each year, and scarcity is real. But scarcity alone doesn’t auction price upwards. It’s scarcity plus demand and demand today is qualitatively different. It’s slower, steadier, tied to real use cases like remittances and institutional balance sheets. That steadiness dampens both bubbles and busts. If this holds, the next bull market could feel more like a series of leg‑ups than one big parabolic curve.
Look at regulatory developments too. In 2017 most governments were still figuring out what crypto even was. Now there’s clearer guidance in several jurisdictions. That brings institutional flows but also compliance frictions. Institutions can invest, but they do so slowly and with due diligence. That’s not the frantic, retail‑driven cycle of the past. It’s a snowball rolling uphill, not a firework exploding into the sky.
All of which means the shape of adoption is different. The last cycle was driven by first‑time discovery. The next one is driven by integration into existing financial infrastructure. Integration takes time. It’s less dramatic but more durable if it sticks.
One obvious counterargument is that Bitcoin is still a nascent asset class, so anything can happen. True. Volatility remains high. And there’s always a risk that regulatory clampdowns or tech vulnerabilities could spook the market. But from the patterns I’m watching — participation, custody behavior, derivatives hedging, macro capital flows — the emerging picture is not of another 2017‑like sprint. It’s of layered adoption, each layer slower, deeper, and more anchored to real capital allocation decisions.
And that’s why the supercycle notion itself needs rethinking. If you define “supercycle” as a dramatic price surge that breaks all prior records in a short time, then yes, conditions today don’t favor that in isolation. But if you define supercycle as a long, multi‑year expansion of economic activity, network growth, and capital engagement, then that’s quietly happening underneath the headlines.
Even the metrics that used to signal euphoric tops — social media mentions, Google search volume spikes — are muted compared to the last cycle’s frenzy. That’s not apathy; it’s maturity. A seasoned investor doesn’t broadcast every position on Reddit. That change in participant behavior means price patterns will also look different.
So what does this reveal about where things are heading? It shows that markets evolve not just in magnitude but in structure. The old model assumed a rapid cycle was tied to speculative FOMO. That model can’t simply replay because the underlying players aren’t the same. Young retail chasing quick wins dominated early Bitcoin cycles. Now you have institutional allocators, corporate treasurers, and long‑term holders. That shifts the demand curve, flattens the peaks, and widens the base.
Which leads to one sharp observation: the next Bitcoin supercycle might not feel like a dramatic sprint at all — it could feel like steady gravitational pull. Not fireworks, but tide rising over years. And if you only expect firework cycles, you’ll miss the real transformation that’s happening underneath. #BTC $BTC #BTC☀️

I kept noticing the same thing in on-chain markets: everyone bragged about throughput, but my trades still felt late. Blocks were fast on paper, validators were “high performance,” and yet slippage kept creeping in at the edges. Something didn’t add up. Either the numbers were misleading, or we were measuring the wrong layer of the stack. When I first looked at how Fogo’s Firedancer-powered architecture is structured, it felt like someone had finally stopped optimizing the brochure and started optimizing the foundation.
On the surface, Fogo is built for one thing: trading. Not general purpose experimentation. Not vague Web3 social promises. Trading. That focus matters because trading punishes latency more than almost any other on-chain activity. If a block takes 400 milliseconds instead of 100, that difference isn’t theoretical — it’s the difference between capturing a spread and donating it.
Underneath that focus sits Firedancer, the independent validator client originally engineered to push the Solana Virtual Machine to its performance ceiling. What struck me is that Firedancer isn’t just “faster code.” It rethinks how a validator processes transactions at the systems level: tighter memory management, aggressive parallelization, and highly optimized networking paths. In plain English, it’s built like a high-frequency trading engine rather than a research prototype.
Surface level, that means more transactions per second and faster block production. But numbers only matter relative to the market they serve. If a network claims 1 million transactions per second yet your trade still waits in a congested queue, the headline figure is noise. What Firedancer changes is the consistency of execution under pressure. It’s not just peak throughput; it’s steady throughput when volatility spikes.
That steady texture matters in trading because volatility is when the system is most stressed. When price swings 5% in minutes, order flow surges. If the validator architecture can’t keep up with packet ingestion, signature verification, and state updates in parallel, the mempool swells and latency balloons. Firedancer’s design reduces that bottleneck by optimizing how packets are handled before they even become transactions in a block. Less wasted CPU. Less serialization. More deterministic flow.
Understanding that helps explain why Fogo leans so heavily into this architecture. If your goal is to host serious on-chain trading — not just retail swaps, but market makers and latency-sensitive strategies — you can’t afford jitter. Jitter is the quiet tax underneath every “fast” chain. It’s the variability between best-case and worst-case confirmation times. Traders don’t just care about averages; they care about the tail.
Fogo’s architecture narrows that tail. Firedancer’s low-level optimizations mean validators can process transactions in parallel without tripping over shared state locks as often. On the surface, that sounds like a small engineering detail. Underneath, it changes how order books behave. If transactions finalize with tighter timing bands, price discovery becomes cleaner. Slippage becomes more predictable. Market makers can quote tighter spreads because the risk of execution lag shrinks.
And that’s the subtle shift. Speed is not about bragging rights; it’s about risk compression.
There’s another layer here. Firedancer reduces reliance on a single dominant client implementation. In many networks, monoculture is the hidden fragility — one bug, one exploit, and consensus stalls. By running a high-performance independent client, Fogo isn’t just chasing speed; it’s diversifying the validator base at the software level. Surface: more codebases. Underneath: reduced systemic risk. What that enables is confidence for larger liquidity providers who think in terms of failure probabilities, not marketing narratives.
Of course, higher throughput introduces its own tensions. If blocks are packed more aggressively and confirmation times shrink, hardware requirements tend to climb. That can centralize validator participation if not managed carefully. It’s the obvious counterargument: does optimizing for performance quietly raise the barrier to entry?
Early signs suggest Fogo is aware of this tradeoff. Firedancer is engineered for efficiency, not brute-force scaling. It squeezes more performance from existing hardware classes rather than simply demanding data-center-grade machines. Whether that balance holds over time remains to be seen. Trading networks naturally attract actors willing to spend heavily for an edge.
But here’s where design intent matters. Fogo isn’t trying to be everything. By narrowing its focus to trading, it can tune network parameters — block times, compute limits, fee mechanics — around one core workload. That specialization changes the economic texture of the chain. Gas pricing becomes less about deterring spam and more about prioritizing economically meaningful flow.
Meanwhile, faster and more predictable finality reshapes trader psychology. If confirmation reliably lands within a narrow window, strategies that were once too risky on-chain start to make sense. Arbitrage loops tighten. Cross-venue strategies compress. Liquidity that once stayed off-chain because of latency fear begins to edge inward. Not all at once. Quietly.
And that momentum creates another effect. As more latency-sensitive actors participate, the demand for deterministic infrastructure increases. Validators are incentivized to optimize networking paths, colocate strategically, and maintain uptime discipline. The culture of the chain shifts. It becomes less about experimentation and more about execution quality. That cultural shift is hard to quantify, but you can feel it in how builders talk about performance — less hype, more benchmarks.
Zooming out, this says something bigger about where on-chain systems are heading. For years, the industry treated decentralization and performance as opposites on a sliding scale. Either you were slow and principled, or fast and fragile. Architectures like Firedancer challenge that framing by attacking inefficiencies at the implementation layer rather than compromising consensus assumptions.
It suggests the next phase of infrastructure competition won’t be about new slogans. It will be about who can engineer the quietest foundation — the least jitter, the tightest execution bands, the most predictable behavior under stress. Trading just happens to be the harshest test case.
When I step back, what stands out isn’t that Fogo is fast. It’s that it treats speed as earned, not advertised. Firedancer isn’t a cosmetic add-on; it’s an architectural commitment to squeezing inefficiency out of every layer between packet arrival and final state update. If this holds, the advantage won’t show up in press releases. It will show up in narrower spreads and fewer missed fills.
And in markets, that’s the only metric that ever really mattered. @Fogo Official $FOGO
#fogo

Every cycle, we promise ourselves we’re building something new, and every cycle we end up porting the old world onto a blockchain and calling it progress. When I first looked at $VANRY , what struck me wasn’t what it claimed to replace. It was what it refused to retrofit.
“Built for Native Intelligence, Not Retrofits” isn’t a slogan you can fake. It’s either embedded in the foundation or it isn’t. And most projects, if we’re honest, are still trying to wedge AI and on-chain systems into architectures that were designed for token transfers, not intelligence.
The quiet tension in crypto right now is this: blockchains were built to verify ownership and state transitions. AI systems were built to process data and generate outputs. One secures truth; the other infers patterns. Trying to glue them together after the fact often creates friction. Latency spikes. Costs climb. Data pipelines leak. The surface story looks fine—“AI-powered NFT marketplace,” “AI-enhanced DeFi”—but underneath, you see APIs duct-taped to smart contracts.
$VANRY , tied to the broader ecosystem of Vanar, is taking a different angle. Instead of asking, “How do we plug AI into our chain?” it starts with, “What does a chain look like if intelligence is native to it?”
That question changes everything.
On the surface, a chain optimized for native intelligence means infrastructure choices: lower latency, scalable throughput, data availability designed for real-time interaction. If you’re processing AI-driven game logic or adaptive digital assets, you can’t afford confirmation times that feel like waiting in line at a bank. A few seconds of delay doesn’t just inconvenience a trader; it breaks immersion in a game or disrupts an AI-driven interaction.
Underneath that surface layer is something more structural. Most blockchains treat computation as expensive and scarce. Gas fees are a tax on complexity. But AI systems are computation-heavy by nature. If every inference or model interaction triggers high on-chain costs, developers quickly retreat to off-chain solutions. That’s how you end up with “AI on blockchain” that is really AI off-chain with a token attached.
Native intelligence implies a different cost model and execution environment. It suggests that smart contracts, or their equivalent, are designed to work alongside AI processes rather than merely record their outputs. That might mean tighter integration between on-chain logic and off-chain compute layers, but orchestrated in a way that keeps trust assumptions transparent. The point isn’t to put a neural network fully on-chain; it’s to design the system so that intelligence and verification grow together, not apart.
Understanding that helps explain why $VANRY positions itself less as a speculative token and more as an infrastructure layer for immersive ecosystems—especially gaming and interactive media. Games are the clearest stress test for this thesis. They demand low latency, high throughput, and dynamic assets that evolve in response to player behavior. Static NFTs minted once and traded forever don’t cut it anymore. Players expect living worlds.
If you’re building a game where in-game characters adapt using AI—learning from player actions, generating new dialogue, altering strategies—those changes need to interact with ownership systems. Who owns that evolving character? How is its state validated? How are upgrades tracked without breaking the experience? A retrofit approach would store most intelligence off-chain and just checkpoint results. A native approach asks how the chain itself can anchor those evolving states in near real time.
That’s where the texture of $VANRY ’s design philosophy matters. Early signs suggest the focus is on performance metrics that actually support interactive workloads. High transaction capacity isn’t just a vanity number. If a network can handle thousands of transactions per second, what that reveals is headroom. It means a spike in user activity during a game event doesn’t immediately price out participants or slow everything to a crawl.
Every number needs context. Throughput in the thousands per second sounds impressive until you compare it to a popular online game, which can generate tens of thousands of state changes per minute across its player base. So the real question isn’t whether the chain can spike to a high TPS for a benchmark test. It’s whether it can sustain steady activity without unpredictable fees. Stability is what developers build around.
There’s another layer underneath: developer experience. Retrofits often require devs to juggle multiple toolkits—one for AI frameworks, another for smart contracts, another for bridging. Each boundary adds cognitive load and security risk. If $VANRY ’s ecosystem reduces that fragmentation—offering SDKs or tooling that align AI logic with on-chain execution—that lowers the barrier for serious builders. And serious builders are what create durable value, not token incentives alone.
Of course, the counterargument is obvious. AI models are evolving fast. Today’s state-of-the-art may look outdated in 18 months. So why hardwire intelligence assumptions into a blockchain at all? Wouldn’t flexibility favor modular systems where AI can change independently of the chain?
That’s a fair concern. But “built for native intelligence” doesn’t have to mean locking in specific models. It can mean designing primitives—data structures, verification mechanisms, identity layers—that assume intelligence will be a first-class actor in the system. Think of it as building roads wide enough for heavier traffic, even if you don’t know exactly which vehicles will dominate.
Meanwhile, token economics can’t be ignored. A token like $V$VANRY n’t just a utility chip; it’s an incentive mechanism. If developers and users pay fees in $VANRY , stake it for network security, or use it within gaming ecosystems, demand becomes tied to actual activity. The risk, as always, is speculative inflation outrunning usage. If token price surges without matching ecosystem growth, it creates instability. Builders hesitate. Users feel priced out.
But if activity grows steadily—if games launch, if AI-driven experiences attract real engagement—then the token’s value becomes earned rather than hyped. That’s the difference between a short-lived narrative and a durable foundation.
Zooming out, the deeper pattern is clear. We are moving from static digital ownership to adaptive digital systems. Assets are no longer just pictures or entries in a ledger. They’re behaviors. They respond. They learn. That shift demands infrastructure that treats intelligence not as an add-on but as a core component.
We’ve seen this movie before in other industries. The internet wasn’t built by bolting connectivity onto typewriters. Smartphones weren’t just landlines with touchscreens. Each wave required systems designed for the new dominant behavior. If AI becomes embedded in everyday digital interaction, then blockchains that merely accommodate it at the edges may struggle.
$VANRY ’s bet is that the next phase of Web3 belongs to environments where intelligence is woven into the base layer. Not as marketing. Not as a plugin. As an assumption.
Whether that bet pays off remains to be seen. Execution matters. Adoption matters. Market cycles matter. But the philosophical shift—from retrofitting intelligence to designing around it—feels aligned with where things are heading.
And if this holds, the real dividing line in the next cycle won’t be between chains with higher TPS or lower fees. It will be between systems that treat intelligence as external noise and those that quietly made it part of their foundation from the start. @Vanarchain $VANRY #vanar

That strange familiarity in the tape. The way Bitcoin starts moving before anyone agrees on why. The way confidence builds quietly underneath the headlines, long before the front pages catch up. When I first looked at this cycle’s structure, something didn’t add up — or rather, it added up too neatly. The rhythm felt familiar. Not random. Not new. Familiar.
Bitcoin is repeating the 2017 and 2021 pattern.
Not in price alone. In structure. In tempo. In psychology.
In 2017, Bitcoin spent months grinding upward after its 2016 halving. It didn’t explode immediately. It built a foundation. By early 2017, it had broken its previous all-time high near $1,150 — a level set in late 2013. That breakout mattered because it marked the first clean air above prior resistance in years. Once price clears a major historical ceiling, there’s no one left holding bags at that level. There’s no natural seller overhead. That creates space. And space changes behavior.
The same thing happened in 2020 heading into 2021. After the May 2020 halving, Bitcoin consolidated for months. It wasn’t dramatic. It was steady. Then in December 2020, it broke above $20,000 — the 2017 high. Again, clean air. Again, no trapped supply. That breakout wasn’t just technical. It was psychological. It signaled that the previous cycle’s pain had been fully absorbed.
Now look at the present cycle. After the 2024 halving, Bitcoin reclaimed and broke above its prior high around $69,000, first set in 2021. And just like before, the breakout didn’t immediately trigger a straight vertical move. It stalled. It consolidated. It made people doubt. That hesitation is part of the pattern.
Here’s what’s happening on the surface: price breaks out, pulls back, chops sideways, and frustrates both bulls and bears.
Underneath, something more important is happening: long-term holders are absorbing supply while weaker hands rotate out. You can see this in on-chain data. In both 2017 and 2021, the percentage of Bitcoin held by long-term wallets — coins unmoved for 155 days or more — steadily climbed during consolidation phases. That metric matters because it measures conviction. When coins go dormant, it suggests owners are not interested in short-term volatility.
Right now, long-term holder supply is again climbing after an initial distribution near the highs. That’s the same pattern we saw before the final acceleration phases in prior cycles. The surface looks uncertain. The foundation looks steady.
Understanding that helps explain why volatility compresses before expansion. When coins cluster in strong hands, there’s less supply available to meet new demand. It doesn’t take much incremental buying to move price sharply upward. That’s how parabolic phases begin — not because of hype, but because of imbalance.
In 2017, once Bitcoin cleared $3,000 — roughly triple its previous high — momentum fed on itself. Retail participation surged. Google search trends spiked. By December, price touched nearly $20,000, a 17x move from the breakout year’s start.
In 2021, the move was more muted but structurally similar. Bitcoin broke $20,000 in December 2020 and ran to $64,000 by April 2021. That’s a little over 3x in four months. After a mid-cycle reset, it pushed again to $69,000 in November.
Notice something. Each cycle’s multiplier compresses. Early cycles produced 50x or 100x gains. Later cycles produce 10x, then 3x. That’s what happens as an asset matures and liquidity deepens. It takes more capital to move the market. But the pattern — breakout, consolidation, acceleration — remains intact.
This time, there’s an additional layer. Spot Bitcoin ETFs. In early 2024, institutional access changed. Billions of dollars in inflows came through regulated vehicles. That matters because ETF flows create steady, mechanical demand. When investors buy shares, the fund must acquire Bitcoin. That’s not speculative leverage. That’s structural buying pressure.
Surface effect: price rallies on ETF inflows.
Underneath: circulating supply tightens further because ETF-held coins are effectively removed from liquid markets.
What that enables is slower, more sustained moves rather than purely retail-driven spikes. What risk it creates is concentration — large custodians holding significant supply introduces systemic dependencies that didn’t exist in 2017.
Meanwhile, derivatives markets tell a familiar story. Funding rates — the payments traders make to hold leveraged long or short positions — tend to flip positive during euphoric phases. In both 2017 and early 2021, funding became persistently elevated before major corrections. That was leverage overheating.
Currently, funding periodically spikes but resets quickly. That suggests speculation is present but not yet extreme. If this holds, it implies we’re not in the terminal phase. Parabolic blow-offs usually coincide with sustained leverage excess.
Skeptics will say this time is different. And they’re right in one sense. Macro conditions aren’t identical. Interest rates are higher than they were in 2020. Liquidity is tighter. Global risk appetite fluctuates with every central bank meeting.
But Bitcoin has never required identical macro backdrops to follow its internal cycle structure. The halving reduces new supply issuance by 50% roughly every four years. In 2016, daily issuance dropped from 3,600 BTC to 1,800. In 2020, from 1,800 to 900. In 2024, from 900 to 450. Each reduction seems small relative to total supply — 450 BTC per day is tiny against 19+ million already mined — but markets trade on marginal flows, not totals. If daily new supply shrinks while demand stays steady or grows, price must adjust upward to ration access.
That supply shock doesn’t hit instantly. It works quietly. Miners sell fewer coins. Exchanges see lower inflows. The texture of order books changes. Liquidity thins at the edges. Then when demand returns — often triggered by narrative or momentum — price moves faster than expected.
This layering explains why cycles feel slow until they feel sudden.
Another repeated pattern: disbelief. In 2017, analysts called $5,000 unsustainable. In 2021, $30,000 was labeled absurd. Today, even after breaking prior highs, large segments of the market remain cautious. Sentiment surveys are elevated but not euphoric. Retail participation, measured by app downloads and small transaction counts, hasn’t reached prior extremes. That gap between price strength and public excitement is telling.
That momentum creates another effect. Institutions accumulate while retail hesitates. In prior cycles, the final phase began only after mainstream participation surged — when price appreciation became dinner-table conversation.
Early signs suggest we’re not fully there yet.
Zooming out, what we’re seeing may not just be a repetition but a refinement. Each cycle becomes less explosive but more structurally integrated into the broader financial system. Bitcoin is changing how capital allocates to non-sovereign assets. It’s moving from outsider speculation toward portfolio allocation.
If this pattern continues, future cycles may compress further — smaller percentage gains, longer consolidation phases, deeper integration with global liquidity cycles. The raw volatility of 2017 may never return. But the core mechanism — supply contraction meeting episodic demand — remains intact.
And that’s the real pattern.
Not hype. Not headlines. A steady four-year heartbeat driven by programmed scarcity and human behavior layered on top of it.
We can argue about exact targets. We can debate macro headwinds. That’s healthy. What’s harder to ignore is the rhythm — breakout above prior highs, hesitation, absorption, expansion.
When markets repeat themselves, it’s rarely because history is lazy. It’s because incentives haven’t changed. Bitcoin’s supply schedule hasn’t changed. Human psychology hasn’t changed either.
If this cycle truly mirrors 2017 and 2021, the quiet consolidation we’re seeing now isn’t weakness.
It’s pressure building underneath. #BTC $BTC #CPIWatch

Mỗi dự án khác đột nhiên trở thành “được hỗ trợ bởi AI.” Mỗi lộ trình đều có cùng một ánh sáng. Mỗi bộ pitch deck đều đưa các chữ cái A và I vào những chỗ mà, một năm trước, chúng không tồn tại. Khi tôi lần đầu nhìn vào làn sóng này, có điều gì đó không đúng. Nếu AI thực sự là cốt lõi, tại sao lại có quá nhiều điều cảm giác như một tùy chọn tính năng thay vì một nền tảng?
Sự căng thẳng đó — AI-đầu tiên hay AI-thêm vào — không phải là một cuộc tranh luận về thương hiệu. Đó là một câu hỏi về cơ sở hạ tầng. Và thiết kế cơ sở hạ tầng quan trọng hơn bất kỳ câu chuyện nào ngồi ở trên.

Những buổi ra mắt ồn ào. Những chủ đề được trả tiền. Những dòng thời gian cảm thấy được phối hợp đến từng phút. Mọi người nhìn về phía bên trái vào kích thước ngân sách tiếp thị, danh sách người ảnh hưởng, hashtag thịnh hành.
Trong khi đó, một điều gì đó yên tĩnh đang xảy ra ở phía bên phải.
Các nhà xây dựng chỉ đang... xuất hiện.
Khi tôi lần đầu nhìn vào Plasma, nó không nổi bật vì một tiêu đề hay một sự ủng hộ của người nổi tiếng. Nó xuất hiện theo một cách khác. Trong các phản hồi. Trong các cam kết trên GitHub. Trong những chủ đề Discord kéo dài lâu sau chu kỳ thông báo. Không có sự phấn khích được trả tiền. Không có những câu chuyện bị ép buộc. Chỉ có các nhà xây dựng nói chuyện với nhau về cách làm cho một thứ gì đó hoạt động. $XPL #plasma

Một mã thông báo mới ra mắt, dòng thời gian đầy những chủ đề về quan hệ đối tác và câu chuyện, giá cả di chuyển nhanh chóng, và sau đó sáu tháng sau sự phấn khích mờ nhạt đi. Mọi người đều nhìn về bên trái câu chuyện. Tôi bắt đầu nhìn về bên phải hệ thống.
Đó là nơi mà VANRY nổi bật. Không phải vì nó có câu chuyện ồn ào nhất, mà vì nó được định vị xung quanh sự sẵn sàng. Và sự sẵn sàng thì yên tĩnh hơn. Nó không tăng vọt trên các tiêu đề. Nó tích lũy bên dưới.
Khi tôi lần đầu nhìn vào $VANRY , điều làm tôi ấn tượng không phải là một thông báo duy nhất. Đó là định hướng. Ngôn ngữ không nói về việc “trở thành tương lai của AI” theo những thuật ngữ trừu tượng. Nó nói về cơ sở hạ tầng được xây dựng cho các tác nhân bản địa AI, quy trình làm việc doanh nghiệp, và triển khai trong thế giới thực. Sự khác biệt đó nghe có vẻ tinh tế. Nó không phải như vậy.

Mỗi chu kỳ, những dự án ồn ào nhất hứa hẹn sẽ xây dựng lại internet, sửa chữa tài chính và đưa vào sử dụng tỷ lệ người dùng tiếp theo — tất cả trước khi họ gửi đi một thứ gì đó ổn định. Thời gian kéo dài. Lộ trình mở rộng. Biểu đồ token di chuyển nhanh hơn mã. Và đâu đó dưới tất cả những tiếng ồn đó, một nhóm nhỏ hơn chỉ tiếp tục xây dựng.
Khi tôi lần đầu nhìn vào Plasma, điều khiến tôi ấn tượng không phải là những gì nó tuyên bố. Đó là những gì nó không tuyên bố.
Plasma không hứa hẹn thế giới. Nó không định vị mình như là lớp cuối cùng, trung tâm vũ trụ, chuỗi mọi thứ. Nó không treo lơ lửng những tích hợp tương lai phụ thuộc vào ba giao thức khác được gửi trước. Nó không chạy một chu trình tiếp thị ngụy trang dưới dạng phát triển sản phẩm.

Mỗi chu kỳ crypto, ánh đèn sân khấu truy đuổi các layer-1 hào nhoáng, các đợt phát hành token, sự phấn khích do meme thúc đẩy. Trong khi đó, một cái gì đó yên tĩnh hơn đang được xây dựng bên dưới. Tôi lần đầu tiên thấy điều này khi tôi theo dõi thông lượng giao dịch so với sự chấp nhận thực tế. Các con số không nói dối: các mạng lưới có nhiều trò chuyện nhất thường gặp khó khăn dưới sự sử dụng thực tế. Đó là lúc tôi nhìn về Plasma, không phải vì nó ồn ào, mà vì nó đang giải quyết một vấn đề mà chu kỳ cứ tiếp tục phớt lờ.
Plasma không cố gắng để được chú ý bởi các dòng Twitter. Tầm nhìn của nó sống trong những gì mà hầu hết mọi người thường bỏ qua: cơ sở hạ tầng thực sự có thể mở rộng. Trên bề mặt, đó là một giải pháp mở rộng cho Ethereum, một “layer-2” trong một thị trường đông đúc. Nhưng bên dưới, nó còn hơn thế nữa. Nó liên quan đến việc tạo ra một nền tảng nơi các ứng dụng phi tập trung có thể hoạt động mà không bị thỏa hiệp, nơi người dùng không phải lựa chọn giữa bảo mật, tốc độ hay chi phí. Sự đánh đổi đó, được gắn vào cốt lõi của Ethereum, vẫn chưa biến mất. Plasma một cách yên lặng giải quyết nó, cho phép thông lượng tăng trưởng trong khi giữ nguyên sự bảo mật của Ethereum. Khi tôi lần đầu tiên mô hình hóa dữ liệu giao dịch, tôi đã nhận ra: các mạng lưới tuyên bố tốc độ “ngay lập tức” thường để bảo mật bị treo lơ lửng. Plasma giữ cho nó ổn định bên dưới, ngay cả khi sự ổn định đó cảm thấy vô hình.