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

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

I have looked into a lot of so-called high-speed blockchains over the past few years, and honestly, most of them sound the same at first. Low fees, huge TPS numbers, near-instant finality — it all looks great on paper. But I’ve learned that those metrics only tell part of the story. What really matters is how a network behaves when real money and real demand hit it.
I always ask myself a simple question: what happens when things get crowded? Does the chain still feel smooth, or does it start slowing down right when it matters most?
That’s what made Fogo Official interesting to me.
From what I’ve seen, it’s not just trying to market speed. It’s built on the Solana Virtual Machine, which allows parallel execution, so transactions don’t just pile up in a single line. They can be processed at the same time when possible. To me, that’s less about flashy benchmarks and more about staying reliable under pressure.
Because real infrastructure isn’t tested during quiet days. It’s tested when volume spikes and everyone needs execution at once.
If you’re talking about cross-border settlements, on-chain order books, or tokenized real-world assets, you can’t afford random delays or unpredictable latency. Institutions don’t treat slowdowns as “normal.” They treat them as risk. And risk is the last thing serious capital wants.
That’s why I don’t see $FOGO as just another Layer 1 trying to compete on hype. I see it more as a network aiming for consistency and predictability, something that feels closer to professional trading infrastructure than an experimental chain.
For me, speed might grab attention, but reliability is what builds trust. And trust is what actually brings adoption.
If blockchain is going to support real economies and not just speculation, I think networks focused on steady performance, like Fogo, will matter a lot more than the ones just chasing big numbers.
That’s how I look at the bigger picture behind $FOGO.

@Fogo Official $FOGO
#fogo

Key takeaways:
Past cycles show Bitcoin tends to recover and outperform during trade tensions and liquidity support, even if fear dominates early on.
Steady mining activity and growing net long exposure on Chicago Mercantile Exchange futures indicate professional traders are quietly buying the pullback.
Bitcoin traders are growing uneasy after nearly three weeks below $75,000, with sentiment worsening following a drop to $64,200 as global equities weakened. Fresh uncertainty emerged after Donald Trump raised baseline import tariffs to 15%, pushing investors toward a more cautious, risk-off approach.
Still, similar macro stress in the past has often set the stage for Bitcoin strength. Miner stability remains intact, and institutional players appear to be using the dip to accumulate rather than exit.
While these events appear negative at first glance, Bitcoin has a history of outperforming during bearish macroeconomic shifts. More importantly, risk perception is gradually improving; Bitcoin miners have shown resilience, and professional traders used the recent dip to add exposure.
On April 2, 2025, the Trump administration signed an executive order imposing sweeping "reciprocal tariffs" on nearly every trading partner. The situation escalated on April 9, 2025, as additional tariffs were applied to 75 countries, including a 34% rate for China. This move coincided with Bitcoin hitting a five-month low at $74,600, which was followed by a 38% rally over the next month.
Traders choose cash over Bitcoin during periods of uncertainty
The natural instinct for traders during periods of uncertainty is to seek shelter in cash and government bonds. Despite its unique benefits, Bitcoin is not yet considered a safe haven by most investors. However, once the market realizes that governments may be forced to inject liquidity to stimulate the economy, Bitcoin tends to outperform.
The Federal Reserve provides short-term cash loans against Treasury collateral to keep funding markets and settlements functioning smoothly. While this isn’t considered a direct liquidity injection, it often reflects temporary balance sheet stress. Still, extreme spikes in this metric — including the $100 billion surge on March 16, 2020 — have historically aligned with turning points in Bitcoin’s price.
Following the 2020 pandemic-driven crash, Bitcoin began a sustained recovery, climbing from $4,400 to $42,000 over the next several months. At the time, many doubted its long term outlook while it traded 55% below its previous $19,900 high between May and July, but that skepticism proved misplaced. A comparable setup could emerge in 2026 if liquidity pressures intensify again.
Nvidia (NVDA US) is scheduled to report quarterly earnings after the US stock market closes on Wednesday. Results from the chipmaker will likely set the investor mood, particularly as concerns regarding rising tech sector debt mount. Notably, shares of Coreweave (CRWV US) and Oracle (ORCL US) have already plunged over 50% from their previous all-time highs.
While conditions for companies supporting the artificial intelligence sector weaken, the exodus of investment from Bitcoin miners represents less of a risk now that the network hashrate has fully recovered from a 25% dip in January. More importantly, ASIC miners released in 2024 and early 2025 remain profitable even at an electricity cost of $0.07 per kilowatt-hour.
The de-escalation of "miner death spiral" fears may have helped instill bullishness among professional fund managers. Large speculators, including hedge funds, have shifted from a net short to a net long position on CME Bitcoin futures, according to a CFTC report published last week. Analyst Tom McClellan noted that two similar historical shifts preceded significant Bitcoin price bottoms.
While no single reversal indicator can confirm if the $60,200 level on Feb. 6 marked the cycle low, the combination of liquidity concerns, fears of excessive AI sector valuations, and resilience in the mining sector could push Bitcoin’s price back toward $75,000 in the near term.
$BTC

I have been thinking a lot about how the crypto market has changed over the years. In the early days, it felt like anything with a big idea could get attention. Then came the growth phase, where ecosystems and hype cycles drove everything. Now, it feels different. The space is maturing, and performance isn’t just a bonus anymore — it’s the baseline.
That’s the lens I look through when I think about Fogo.
To me, it doesn’t come across as another chain trying to be the loudest or promise the biggest numbers. It feels more like a team quietly focused on one thing: execution. And honestly, that focus makes more sense today than ever.
As on-chain markets get more complex, the stakes are higher. We are not just swapping tokens for fun anymore. There are perpetuals, automated strategies, arbitrage bots, and serious capital moving fast. In that kind of environment, small delays actually matter. A few milliseconds can mean worse fills, unexpected liquidations, or missed trades. I’ve started to realize that network performance directly affects outcomes in ways that weren’t obvious a few years ago.
That’s why infrastructure suddenly feels so important. It’s not abstract tech in the background — it’s the difference between something working smoothly and something breaking under pressure.
What stands out to me about Fogo is that it seems built with this reality in mind. Instead of chasing theoretical throughput, it focuses on responsiveness and consistency. Things like fast block times and tighter finality aren’t just marketing points; they’re meant to make execution more predictable. And in trading or DeFi, predictability is everything.
I also like that it doesn’t try to reinvent everything from scratch. By aligning with the Solana Virtual Machine, it keeps things familiar for developers. From my perspective, that’s a practical decision. It lowers friction and lets builders focus on improving performance instead of relearning a whole new stack. It feels less experimental and more disciplined.
Another thing I have noticed is how the market seems to be moving toward specialization. Not every chain needs to do everything. Some will focus on gaming, some on consumer apps, others on institutions. Fogo looks like it’s carving out a niche around high-performance financial use cases. That narrower focus might limit breadth, but it also gives it a clearer identity.
Of course, none of this really matters unless it holds up when things get messy. I think the real test for any network comes during volatility — when volumes spike, liquidations pile up, and everyone rushes to transact at once. That’s when you find out whether the architecture actually works or was just good on paper.
For me, that’s where Fogo’s story will be decided. If it stays stable and responsive under stress, then the design choices make sense. If not, it’s just another experiment.
Overall, I feel like crypto is entering a more disciplined era. Hype still exists, but serious users care more about reliability and efficiency. Networks that quietly work well might end up winning over those that just promise big things.
From that angle, Fogo’s approach feels less flashy and more grounded. And in a maturing market, that kind of focus might matter more than ambition alone.
$FOGO @Fogo Official #fogo

Bitcoin appears to have carved out a bottom after futures traders on Chicago Mercantile Exchange flipped net bullish back in April 2025. Now, a similar positioning shift is showing up again in 2026, increasing the chances of a near-term BTC rebound.
Key points:
• Smart money has scaled back bearish exposure over the past month.
• A comparable sentiment change previously led to a 70% rally in 2025 and a 190% surge in 2023.

Futures positioning and chart signals both suggest a possible move toward $85,000.
Data from the latest Commodity Futures Trading Commission Commitment of Traders report shows non-commercial traders trimming their net stance to around -1,600 contracts, down from roughly +1,000 just a month ago, reflecting a clear shift in sentiment.

In practice, this means that large speculators, including hedge fund and similar financial institutions, have shifted from net short to long, with bulls outnumbering bears on the CME.
The rapid net-short unwind implies that “ smart money” added longs “with some urgency,” said analyst Tom McClellan, while pointing to two similar past swings that preceded Bitcoin price bottoms.
For instance, BTC’s price gained around 70% after a sharp dip in CME Bitcoin futures net shorts in April 2025. In 2023, BTC price rose by over 190% under similar futures market conditions.
As of February, the smart money swing is flashing once again, just as Bitcoin defends its 200-week exponential moving average (200-week EMA, the blue line), which has acted as a bear-market floor in most major drawdowns of the last decade.
On Sunday, BTC’s 200-week EMA was hovering around near $68,350.
The last time Bitcoin traded around this moving average during deep sell-offs (in 2015, 2018 and 2020), it eventually marked the end of the downtrend and the start of a new recovery phase.
Bitcoin’s weekly relatibe strength index RSI
remains in oversold territory, a sign that selling pressure is nearing exhaustion.
That further raises Bitcoin’s odds of recovering in the coming weeks. A decisive rebound from the 200-week EMA could trigger a run-up toward the 100-week EMA (the purple wave) at roughly $85,000 by April.
Bitcoin bulls aren’t out of the woods yet
McClellan cautioned that the smart money shift is “a condition, not a signal,” meaning Bitcoin could still slide from its current price levels before a durable low forms.
That may trigger the 2022 scenario, wherein BTC plunged by over 40% after breaking below its 200-week EMA despite similar oversold conditions.
A repeat of that 40% plunge in 2026 could result in BTC prices falling toward $40,000, or 60% from its record high of around $126,270.
Some analysts, including Kaiko, also see BTC potentially bottoming around $40,000–$50,000 based on its “ four year cycle” framework.
$BTC