Bit_boy

Development of quantum computing might kill the Bitcoin network
I researched all the data and learn everything about it.
/➮ Recently, BlackRock warned us about potential risks to the Bitcoin network
🕷 All due to the rapid progress in the field of quantum computing.
🕷 I’ll add their report at the end - but for now, let’s break down what this actually means.
/➮ Bitcoin's security relies on cryptographic algorithms, mainly ECDSA
🕷 It safeguards private keys and ensures transaction integrity
🕷 Quantum computers, leveraging algorithms like Shor's algorithm, could potentially break ECDSA
/➮ How? By efficiently solving complex mathematical problems that are currently infeasible for classical computers
🕷 This will would allow malicious actors to derive private keys from public keys
Compromising wallet security and transaction authenticity
/➮ So BlackRock warns that such a development might enable attackers to compromise wallets and transactions
🕷 Which would lead to potential losses for investors
🕷 But when will this happen and how can we protect ourselves?
/➮ Quantum computers capable of breaking Bitcoin's cryptography are not yet operational
🕷 Experts estimate that such capabilities could emerge within 5-7 yeards
🕷 Currently, 25% of BTC is stored in addresses that are vulnerable to quantum attacks
/➮ But it's not all bad - the Bitcoin community and the broader cryptocurrency ecosystem are already exploring several strategies:
- Post-Quantum Cryptography
- Wallet Security Enhancements
- Network Upgrades
/➮ However, if a solution is not found in time, it could seriously undermine trust in digital assets
🕷 Which in turn could reduce demand for BTC and crypto in general
🕷 And the current outlook isn't too optimistic - here's why:
/➮ Google has stated that breaking RSA encryption (tech also used to secure crypto wallets)
🕷 Would require 20x fewer quantum resources than previously expected
🕷 That means we may simply not have enough time to solve the problem before it becomes critical
/➮ For now, I believe the most effective step is encouraging users to transfer funds to addresses with enhanced security,
🕷 Such as Pay-to-Public-Key-Hash (P2PKH) addresses, which do not expose public keys until a transaction is made
🕷 Don’t rush to sell all your BTC or move it off wallets - there is still time
🕷 But it's important to keep an eye on this issue and the progress on solutions
Report: sec.gov/Archives/edgar…
➮ Give some love and support
🕷 Follow for even more excitement!
🕷 Remember to like, retweet, and drop a comment.
#TrumpMediaBitcoinTreasury #Bitcoin2025 $BTC

Candlestick patterns are a powerful tool in technical analysis, offering insights into market sentiment and potential price movements. By recognizing and interpreting these patterns, traders can make informed decisions and increase their chances of success. In this article, we'll explore 20 essential candlestick patterns, providing a comprehensive guide to help you enhance your trading strategy and potentially earn $1000 a month.
Understanding Candlestick Patterns
Before diving into the patterns, it's essential to understand the basics of candlestick charts. Each candle represents a specific time frame, displaying the open, high, low, and close prices. The body of the candle shows the price movement, while the wicks indicate the high and low prices.
The 20 Candlestick Patterns
1. Doji: A candle with a small body and long wicks, indicating indecision and potential reversal.
2. Hammer: A bullish reversal pattern with a small body at the top and a long lower wick.
3. Hanging Man: A bearish reversal pattern with a small body at the bottom and a long upper wick.
4. Engulfing Pattern: A two-candle pattern where the second candle engulfs the first, indicating a potential reversal.
5. Piercing Line: A bullish reversal pattern where the second candle opens below the first and closes above its midpoint.
6. Dark Cloud Cover: A bearish reversal pattern where the second candle opens above the first and closes below its midpoint.
7. Morning Star: A three-candle pattern indicating a bullish reversal.
8. Evening Star: A three-candle pattern indicating a bearish reversal.
9. Shooting Star: A bearish reversal pattern with a small body at the bottom and a long upper wick.
10. Inverted Hammer: A bullish reversal pattern with a small body at the top and a long lower wick.
11. Bullish Harami: A two-candle pattern indicating a potential bullish reversal.
12. Bearish Harami: A two-candle pattern indicating a potential bearish reversal.
13. Tweezer Top: A two-candle pattern indicating a potential bearish reversal.
14. Tweezer Bottom: A two-candle pattern indicating a potential bullish reversal.
15. Three White Soldiers: A bullish reversal pattern with three consecutive long-bodied candles.
16. Three Black Crows: A bearish reversal pattern with three consecutive long-bodied candles.
17. Rising Three Methods: A continuation pattern indicating a bullish trend.
18. Falling Three Methods: A continuation pattern indicating a bearish trend.
19. Marubozu: A candle with no wicks and a full-bodied appearance, indicating strong market momentum.
20. Belt Hold Line: A single candle pattern indicating a potential reversal or continuation.
Applying Candlestick Patterns in Trading
To effectively use these patterns, it's essential to:
- Understand the context in which they appear
- Combine them with other technical analysis tools
- Practice and backtest to develop a deep understanding
By mastering these 20 candlestick patterns, you'll be well on your way to enhancing your trading strategy and potentially earning $1000 a month. Remember to stay disciplined, patient, and informed to achieve success in the markets.
#CandleStickPatterns
#tradingStrategy
#TechnicalAnalysis
#DayTradingTips
#tradingforbeginners

I have been looking closely at ROBO and the work behind the Fabric Foundation, and what stands out to me is how different their vision feels compared to most crypto projects. Instead of launching just another token, they’re trying to build the basic infrastructure for what they call a decentralized robot economy. The foundation was initiated by OpenMind, and the idea is simple but ambitious: robots shouldn’t just be tools we control manually, they should be autonomous agents that can earn, pay, verify tasks, and interact safely with people using blockchain rails.
From my perspective, the interesting part is how they combine AI, robotics, and Web3 in a practical way. Each robot has its own on-chain identity, wallet, and staking system, so it can accept tasks, get paid, and be held accountable. If a robot or operator behaves dishonestly, part of their stake can be slashed, which creates real economic consequences. They also reward useful contributions through something called Proof of Robotic Work, where data, compute, or skills are compensated. It feels like they’re trying to treat robots almost like independent workers in a digital marketplace rather than just hardware.
I also like that they aren’t building everything in isolation. They’re working with names like NVIDIA for compute, Circle for stablecoin payments, and Coinbase for ecosystem support. The protocol starts on Base before eventually moving to its own chain, which makes sense to me as a gradual path instead of overengineering from day one.
The $ROBO token is basically the fuel for everything: fees, payments between humans and robots, staking for task priority, and governance. With a fixed supply and planned buybacks from protocol revenue, the design tries to create long-term demand rather than just short-term hype. That said, I’m realistic about the risks. Building both hardware and blockchain infrastructure is incredibly complex, regulation around physical robots is still unclear, and competition from closed systems like Tesla Optimus and Figure is serious.
Personally, I see ROBO as more of a long-term bet on the future of robotics than a quick trade. If they actually execute on the open-source network, mainnet, and real-world adoption, it could become foundational tech. If not, it’s just another ambitious experiment. Either way, I’m treating it as high potential with equally high risk and doing my own research before making any moves.
@Fabric Foundation
$ROBO
#Robo

For years, I watched the AI space obsess over bigger models, higher benchmarks, and faster chips. Every update felt like a race for raw capability. More parameters, more compute, better scores. But the more I followed it, the more I felt something was missing. Performance is impressive, but when AI starts making real decisions that affect money, health, or operations, what I really care about isn’t how smart it sounds. It’s whether I can trust it.
That’s the lens through which I started looking at Mira Network.
To me, they’re not trying to build yet another model or compete with labs on intelligence. They’re going after something more basic and, honestly, more necessary. They’re trying to turn trust into infrastructure. Instead of assuming an AI output is correct because a company says so, the idea is to verify it through a decentralized network that’s economically accountable.
When I think about AI moving into finance, healthcare, or logistics, the risks feel obvious. If one AI agent triggers a trade or approves a transaction based on another model’s output, who takes responsibility if it’s wrong? Where’s the proof that the result wasn’t tampered with? Right now, most of that trust is internal and opaque. Companies audit themselves and publish reports, and we just accept it.
That doesn’t feel strong enough for systems that might be moving billions of dollars or handling sensitive decisions.
What Mira proposes makes intuitive sense to me. Validators, incentivized by the $MIRA token, check and attest to outputs or integrity signals. Instead of trust being a promise, it becomes something backed by stake and penalties. If you lie or act carelessly, you lose money. That simple economic pressure is often more reliable than policy documents.
But I’m not blindly optimistic either. I can see how this kind of system could go wrong. If validators just chase rewards without doing real work, verification becomes theater. If only a few players dominate staking, decentralization becomes cosmetic. If using the network slows everything down, developers simply won’t bother. Trust that adds friction isn’t trust people will adopt.
Still, I keep coming back to the same thought: as AI becomes more autonomous, some neutral trust layer feels inevitable. We’ve seen this before on the internet. Secure commerce eventually needed independent authorities. DeFi needed oracles once real money was on the line. It’s hard for me to imagine AI scaling globally without something similar.
In that scenario, $MIRA isn’t just another token to trade. I see it more like collateral for credibility. Its value would come from securing the system, not just speculation. If more applications depend on verified outputs, the network becomes harder to ignore.
So when I look at Mira, I don’t see hype. I see a bet on accountability. It feels less like chasing the next flashy model and more like building the plumbing that everything else might quietly rely on.
Capability got us excited about AI. For me, reliability is what will actually make it usable. And if a project can make trust measurable and verifiable, that’s the kind of foundation I’d rather back for the long term.
@Mira - Trust Layer of AI
$MIRA
#Mira

When I first got into DeFi, I thought speed was everything. Faster blocks, higher TPS, lower latency. But after actually trading on different chains, I realized something: even the fastest network still feels bad if the experience is clunky. Constant wallet pop-ups, random gas spikes, signing every tiny action — it breaks your flow. That’s why Fogo Official started to stand out to me, because they seem to care as much about how trading feels as how fast it is.
What really changed my perspective is their idea of Sessions. Instead of approving and signing every single transaction, I can open one session and let a dApp act within limits I set. I choose which tokens it can use, how much it can spend, and when it expires. After that, trades, cancellations, and rewards just happen in the background. For me, that feels closer to using a centralized exchange account, but I still keep control of my keys. It removes a lot of the small frictions that usually slow me down.
I also like that it’s not blind trust. Sessions aren’t unlimited approvals. There are caps and expiry times, and I can revoke access anytime. That balance between convenience and control feels practical rather than risky.
Beyond the wallet side, the network itself seems built for performance. Fogo runs on the Solana Virtual Machine and uses the Firedancer client, which is optimized for speed. On top of that, their FluxRPC layer keeps requests fast and stable, so apps can react in real time. As a trader, that consistency matters more to me than just flashy TPS numbers.
Then there’s their Dual-Flow Batch Auctions. This part honestly surprised me. Instead of pure first-come-first-serve trading where bots win every race, orders are grouped into short batches. Prices are set based on overall supply and demand, not who paid the highest gas. That means less front-running, fewer sandwich attacks, and fairer execution. For once, it feels like the system isn’t stacked against regular users.
What makes it click for me is how all these pieces connect. Sessions remove signing friction. FluxRPC keeps everything responsive. Batch auctions reduce MEV and spam. Together, it feels less like “typical DeFi” and more like a smooth trading platform that just happens to be decentralized.
From my own experience testing different chains, most focus on raw performance and forget usability. Fogo feels like it starts with the question, “How do traders actually want this to work?” That human-first design is rare in crypto.
It’s not perfect, and there are always trade-offs between speed, trust, and fairness. But if DeFi really wants to compete with centralized exchanges, I think this is the direction it has to go. For me, Fogo Official feels less like another chain and more like an attempt to make on-chain trading actually usable day to day.
@Fogo Official
$FOGO
#fogo

After sliding 35% between Jan. 14 and Feb. 5, Bitcoin has moved sideways, holding between $60,000 and $70,000 for the past three weeks. Meanwhile, key adoption indicators across ETFs, whales, miners, and corporate treasuries are trending in different directions.
These mixed signals suggest quiet but persistent capital accumulation beneath the calm price range, offering a broader view of underlying market strength.
Bitcoin ETF flows remain negative
The 90-day rolling average of US spot Bitcoin ETF net flows has dropped to -$2.18 billion. Over the past two years, the metric has turned negative only twice: from March to May 2025, and in the current stretch that began on December 11, 2025. In both instances, Bitcoin followed with a corrective phase.
When the rolling average turns negative, it means more money is leaving ETFs than coming in over a longer period. That reduces buying pressure, weakens overall demand, and can make it harder for prices to move higher.
A move back above zero, followed by steady inflows, may mark the return of institutional participation. Sustained positive readings tend to align with stronger price action from BTC, alongside improving liquidity conditions.
BTC whale accumulation versus dominant trend
CryptoQuant data tracks the one-year change in total whale holdings and its 365-day moving average. Addresses holding 1,000 to 10,000 BTC added more than 200,000 BTC from June to November 2023, while the price ranged from $25,000 to $30,000.
When the raw one-year change crosses above its 365-day average, whales are accumulating faster than their longer-term trend. That crossover in 2023 coincided with supply absorption during sideways trade, which eventually led to BTC’s bullish rally.
Thus, a bullish trend may unfold for BTC once the one-year change sustainably moves above its moving average (365-SMA), signaling renewed large-scale absorption.
Hash rate and infrastructure signal
Bitcoin’s 30-day mean hash rate stands near 0.99 ZH/s after peaking at 1.10 ZH/s in November 2025. Both hash rate and price have moved lower in recent weeks.
Hash rate measures the computational power securing the network and reflects miner investment in hardware and energy capacity. Rising hash rate during price consolidation points to infrastructure expansion independent of short-term price gains.
If the hash rate trends higher while the price trades sideways, it points to a stronger long-term commitment from miners. A sustained divergence, where hash rate rises ahead of price, can signal growing confidence within the mining sector.
Likewise, miner economics must also improve. Stabilizing the hash price and lower miner sell pressure confirms that rising computational power is backed by healthier revenue conditions rather than tightening margins.
Corporate Bitcoin treasury growth slows
According to a recent bitcointreasuries.net report, companies added roughly 43,200 BTC in January, with Strategy contributing about 40,150 BTC.
Looking at the bigger picture, Strategy’s corporate accumulation has decelerated noticeably since late 2024. Monthly additions hit highs of around 148,000 BTC in November 2024 and 87,000 BTC in July 2025.
Recent monthly increases are much smaller, and the past 30 days added only a slight uptick to the 1.13 million BTC currently held by public firms.
The latest monthly net increase equates to roughly 0.1% growth relative to total public company holdings. That pace signals stability rather than acceleration in treasury expansion.
For BTC price, broader and accelerating treasury inflows help absorb available supply more effectively. Slower increases, by contrast, signal companies are largely maintaining positions rather than driving new demand.
$BTC

For a long time, I bought into the idea that AI was “good enough.”
It writes our emails, helps doctors analyze scans, flags fraud, routes deliveries, even helps people create art and code. Everywhere I looked, AI was being treated like this unstoppable, reliable layer quietly running the world.
But the more I used it seriously, the more cracks I started noticing.
Not small mistakes — fundamental ones.
I’ve seen AI answer questions with total confidence and be completely wrong. I’ve seen it invent facts, misread context, and sometimes produce advice that could actually hurt someone if they followed it blindly. The hallucinations, the bias, the weird edge cases — they’re not rare bugs. They’re baked into how these systems work.
At some point it hit me: we’re deploying AI into healthcare, finance, and other high-stakes areas without ever solving the trust problem first.
We just assume it’s reliable because it sounds smart.
That feels reckless.
I really understood this when I watched someone ask an AI about medical symptoms and get a very convincing but totally incorrect answer. They almost acted on it before double-checking with a real doctor. That moment stuck with me. If they hadn’t verified it, the outcome could’ve been serious.
That’s when I started thinking: AI doesn’t just need to be powerful. It needs to be verifiable.
And that’s why what Mira Network is building caught my attention.
What they’re doing isn’t another “better model” or “smarter chatbot.” They’re not trying to make AI magically perfect. Instead, they’re tackling the trust issue directly.
Their idea is simple in a way that makes you wonder why nobody pushed it harder before: don’t trust a single AI’s output. Verify it.
Instead of treating an answer as one big block of truth, they break it into smaller claims and have multiple independent systems check those claims. Different models, different verifiers, all cross-examining the same output.
It reminds me a lot of how blockchains work.
You don’t trust one party to say a transaction is valid. You rely on consensus.
Mira applies that same thinking to AI. Multiple verifiers check the result, and the validation gets recorded on-chain so it can’t be quietly changed later. So you’re not just hoping the answer is right — you can actually see whether it’s been verified and how.
That shift feels huge to me.
It turns AI from “trust me bro” into something measurable.
And the incentives matter too. Validators are rewarded for being accurate, not for rushing or rubber-stamping results. So honesty and careful checking become economically rational, not just idealistic.
What I like most is that it’s not trying to replace existing AI systems. It acts more like a verification layer you can plug in. So teams don’t have to rebuild everything from scratch — they just add a trust layer on top.
I talked to a developer working on healthcare tools who said the biggest barrier for them wasn’t the model quality. It was liability. What happens if the AI is wrong?
That’s the real fear most teams don’t talk about.
If you can’t prove outputs are reliable, you can’t safely deploy in sensitive environments. Hospitals, autonomous vehicles, finance — the cost of being wrong is too high.
Verification changes that equation.
There’s also an ethical side to this that I appreciate. When outputs are transparent and independently checked, bias and errors get exposed instead of buried. It forces accountability. You can’t just say “the AI decided” and move on.
To me, that feels healthier than the current system where a few big companies control everything and everyone else just has to trust them.
What Mira seems to be saying is: don’t trust blindly — verify collectively.
The more I think about it, the more obvious it feels. AI isn’t going away. It’s only going to get embedded deeper into critical systems. So the question isn’t whether we’ll use it.
It’s whether we’ll put safeguards in place before something breaks badly.
For me, this kind of decentralized verification feels like the missing piece. Not hype, not smarter prompts, not bigger models — just accountability and proof.
Honestly, after seeing how often AI can be confidently wrong, I don’t think we should trust it without something like this ever again.
@Mira - Trust Layer of AI
#Mira
$MIRA

Most people I talk to about Fogo Official immediately focus on one thing: speed. Faster blocks, lower latency, smoother execution. And yes, that part is impressive. But the more time I spend reading its docs and thinking through the design, the more I feel like speed isn’t actually the point.
What really stands out to me is that FOGO feels like it’s experimenting with something deeper — almost like a different political model for how blockchains should work.
As I went through the whitepapers and specs, I kept coming back to one uncomfortable question that most chains seem to avoid: where does the protocol’s responsibility end and mine begin as a user? FOGO doesn’t dodge that. It answers it directly, sometimes bluntly.
When I read their MiCA-style disclosures, it didn’t feel like marketing copy. It felt more like a risk manual. They clearly say what the token is, what it isn’t, and what they’re not promising. No guarantees, no “we’ll protect you,” no implied safety net. It’s basically: this is software, you use it at your own risk.
At first that sounded harsh to me. But then I realized how rare that honesty is. A lot of projects rely on optimism and ambiguity. FOGO seems to prefer clarity, even if it makes things feel less comfortable.
And I think that changes behavior.
If I know nobody is going to bail me out, I read more carefully. I test more. I take custody and risk management seriously. I don’t treat the chain like a customer support desk. That shift alone makes the ecosystem feel more adult.
The same thing shows up in how they talk about exchanges and markets. They don’t pretend they control listings or outcomes. Trading is between users and venues. That separation is spelled out. It quietly removes the “blame the team” mindset and replaces it with “understand the system.” I actually like that.
Decentralization, too, feels less like a slogan and more like an operations problem. When I looked at the validator zone model and the rotation mechanics, I didn’t just see performance engineering. I saw coordination rules. Validators aren’t just sitting there producing blocks. They’re expected to move, sync, follow procedures. It feels disciplined.
That word — discipline — keeps coming back to me when I think about FOGO.
Even the tooling gives me that impression. Things like sessions and paymasters aren’t presented as flashy features. They read like operator manuals. You have to set up servers, bind domains, configure endpoints. It’s not “plug and play magic.” It’s structured and deliberate.
Some people might call that restrictive. I see it as responsible. Real financial systems don’t start fully open with no guardrails. They add layers carefully. FOGO seems comfortable with that slower, controlled approach.
Their compatibility with the Solana Virtual Machine also feels like more than a technical decision to me. It feels social. Instead of forcing developers to learn a new stack and abandon what they know, they just let them keep their tools and change an endpoint. That reduces friction. It feels less tribal and more pragmatic. I appreciate that mindset.
The big question in my head isn’t whether they can keep blocks fast. It’s whether they can keep this discipline as the network grows. It’s easy to be organized when the system is small. It’s much harder when money, incentives, and egos scale up.
Validator rotation, incident response, audits, incentives — all of that has to keep working under pressure. That’s where most systems break. Governance problems usually show up long before technical ones.
Even the economics look like behavior design to me. Low base fees, optional priority fees, rewards flowing directly to producers, inflation declining over time — it feels less like tokenomics theater and more like nudging people toward predictable behavior. If I want urgency, I pay for it. If I validate, I earn for processing real demand. It’s simple and grounded.
When I look at staking and lending integrations, I don’t just see yield strategies. I see habit formation. Users start thinking in terms of capital efficiency instead of idle balances. That can make the network sticky, but it can also create leverage risks. The fact that they openly document those risks makes me trust it more.
Transparency here doesn’t feel reactive. It feels intentional. Instead of waiting for something to break and then explaining, they explain first. Over time, that kind of consistency builds credibility. Markets remember who was upfront.
Personally, I’ve started to think of FOGO less as “another fast chain” and more as a governance-first trading network. Performance matters, sure. But what really makes a market usable is predictability and fairness. Clear roles. Clear risks. Clear rules.
That’s the vibe I get here: fewer promises, more structure.
There’s definitely risk. A system this coordinated depends on people actually coordinating. If validators slack off or incentives drift, the whole model could wobble. Discipline doesn’t scale automatically.
But if they can maintain it, I think it proves something important — that decentralization doesn’t have to mean chaos. It can mean shared responsibility, organized over time and space.
I’ve seen plenty of chains chase hype, TVL, and listings. Very few seem obsessed with operational clarity. FOGO feels like it’s betting on clarity.
Maybe that’s not exciting in the short term. But for a trading environment, consistency might matter more than excitement. And honestly, that’s a bet I find myself respecting more and more the deeper I look into it.
@Fogo Official
$FOGO
#fogo

Key takeaways:
Bitcoin buyers still need roughly a 9% move higher to gain control ahead of Friday’s $10.5B options expiry.
Bitcoin continues to trade in step with the Nasdaq 100, meaning tech market sentiment remains a key driver of confidence.
Bitcoin climbed to an eight-day peak on Wednesday, carving out a clear double bottom around $62,500. Even with the rebound, price is still down 21% over the past month, leaving bulls at a disadvantage into the large monthly options expiry. A late surge could shift momentum, but the outcome remains uncertain.
Deribit remains the dominant leader with a 76% market share, totaling $4.5 billion in call (buy) options and $3.4 billion in put (sell) instruments. OKX follows in second place with $610 million in calls and $385 million in puts, representing 10% of the aggregate total. CME rounded out the top three with $255 million in calls and $287 million in puts, accounting for a 5% market share.
Put options are better positioned despite having less open interest
At first glance, the aggregate put options open interest appears 25% lower than equivalent call options. However, a more granular view reveals that neutral-to-bullish strategies were caught off guard by Bitcoin’s sharp decline below $75,000 in early February. 88% of call options on Deribit will expire worthless if the Bitcoin price remains below $70,000 on Friday.
Even after excluding call options aimed at $105,000 and above — often tied to multi-leg setups with cheaper premiums — just 37% of the remaining positions are placed below $75,000. This leaves the effective call open interest on Deribit near $780 million. Under these conditions, it raises the question of whether bearish traders may have pushed their bets too far.
$1.44 billion in put options open interest on Deribit targets Bitcoin prices below $60,000, although it is unlikely that bets at $40,000 and $45,000 effectively aimed for those specific levels. Calendar strategies and ratio spreads are typically associated with extreme price targets, as they do not require a price crash to achieve profitability.
Put options at $72,000 and above total $1.15 billion in open interest on Deribit, which is more than enough to offset existing call options. Although Bitcoin’s decline toward $60,000 was likely not tied to macroeconomic trend, the relevance of Nvidia’s (NVDA US) earnings outcome after the US market close on Wednesday should not be understated.
The success of the artificial intelligence sector, particularly the sustainable operational margins of the world’s largest companies, remains decisive for every risk market. History suggests that Bitcoin’s correlation with the stock market seldom lasts long, but the fate of Friday’s $10.5 billion options expiry could be decided by stock market performance.
The current 90% correlation between Bitcoin and the Nasdaq 100 Index is clear evidence that the tech play is the leading driver of trader confidence, but as long as Bitcoin price remains below $75,000, the advantage continues to favor put options.
Below are three probable outcomes for Friday’s BTC options expiry at Deribit based on current price trends:
From $65,000 to $69,000: The net result favors the put (sell) instruments by $1.15 billion.From $69,001 to $71,000: The net result favors the put (sell) instruments by $845 million.From $71,001 to $74,000: The net result favors the put (sell) instruments by $470 million.
Ultimately, Bitcoin bulls need a 9% rally from the present $68,800 level to flip the tables on the February options expiry.
$BTC

When I look at Fogo, I don’t see another chain trying to be everything for everyone. I don’t get the feeling it’s chasing NFTs, gaming, social apps, and every new trend all at once. What I notice instead is how narrow the focus is.
And honestly, I kind of respect that.
To me, it feels like Fogo is saying, “Let’s just do one thing really well.” That one thing is markets.
I keep coming back to this idea that in trading environments, timing isn’t a nice-to-have. It’s the whole game. A few milliseconds can change whether you get filled or slipped, whether you’re safe or liquidated. So when a blockchain says it’s built for finance, I think less about TPS charts and more about consistency. Does it behave the same way when things get messy?
That’s where Fogo’s approach clicks for me. It doesn’t feel obsessed with expansion. It feels obsessed with execution.
I see the influence of Solana in the design philosophy, especially around performance, but it doesn’t feel like a copy. It feels more like taking those ideas and tightening them up. Bringing in a validator framework inspired by Firedancer tells me they care about reliability at the lowest level, not just flashy numbers on a dashboard.
Because I’ve learned the hard way that theoretical throughput doesn’t mean much when the network is stressed. Everything looks fast in perfect conditions. What matters is whether it still behaves cleanly when volume spikes and everyone rushes at once.
That’s usually where chains start acting weird.
Another thing I like is the decision to support the Solana Virtual Machine. From my perspective, that’s just practical. Developers don’t want to rewrite everything from scratch just to try a new chain. If I already have something that works, I want to plug it in and focus on improving it, not rebuilding the foundation.
So instead of reinventing the wheel, Fogo seems to be saying, “Bring what you’ve built. We’ll just make it run better.”
In DeFi especially, delays aren’t harmless. I’ve seen how small lags turn into real costs. Orders fill worse than expected. Slippage creeps in. Liquidations cascade because the system reacts too slowly. And sometimes it feels like the fastest actors extract value simply because the infrastructure can’t keep up.
That kind of friction adds up.
What I think Fogo is trying to do is shave down those tiny inefficiencies that most people ignore. Faster confirmations, tighter timing, more predictable behavior. Not just speed for the sake of marketing, but stability you can actually rely on.
And when execution gets cleaner, a lot of things suddenly become possible. Fully on-chain order books start to make sense. Liquidation systems can be more precise instead of chaotic. Auctions can price assets more fairly. Even MEV opportunities shrink because there’s less timing slack to exploit.
To me, that’s what “performance” really means — fewer weird edge cases.
While a lot of Layer-1s compete with big narratives or incentives, Fogo feels more like it’s competing on engineering. Less hype, more structure. It’s almost positioning itself like infrastructure for serious capital rather than a playground for experiments.
I find that mindset refreshing.
If DeFi actually wants to stand next to traditional finance someday, we can’t just rely on vibes and growth hacks. We need systems that behave predictably under pressure. Systems where timing is tight and execution feels deterministic.
That’s how I interpret Fogo. Not as another general-purpose chain, but as a bet that the future of DeFi will belong to whoever executes best, not whoever shouts the loudest.
@Fogo Official
$FOGO
#fogo