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Bitcoin On-Chain User Attrition at 30%, ETF Hemorrhage at $4.5 Billion: What's Next for the Next 3 Months?
Original Title: Bitcoin looks busy but 31% of its users vanished as ETFs bleed $4.5B in 2026
Original Author: Oluwapelumi Adejumo, CryptoSlate
Original Translation: Deep Tide TechFlow
Deep Tide Synopsis: Trading volume has not collapsed, but active addresses have been shrinking for six months, dropping to a five-year low. This "surface busy, internal hollow" divergence is a contrary signal to the structural health of the bull market.
The article cross-validates three sets of data from Glassnode, Santiment, and CryptoQuant, proposing three future scenarios suitable as a reference framework for assessing BTC's current trend.
Full Text:
Bitcoin's network activity has been weakening for six consecutive months, but this trend has not been reflected in many traders' first-glance core metrics.
A clearer signal is not transaction volume—transaction volume has remained relatively stable—but rather, the breadth of participation. Even as the network continues to process a similar amount of transactions, the number of on-chain active addresses has been declining.
In a price discovery increasingly dominated by ETFs and derivatives markets, this divergence is crucial. It means: Bitcoin's on-chain footprint is narrowing, while market exposure continues elsewhere to be active.
As the bear market persists, this trend has become increasingly hard to ignore.
Glassnode data shows that in mid-August 2025, the eight-day moving average of Bitcoin's active addresses was around 778,680. As of February 23, this number had dropped to around 535,942, a decrease of about 31%.
CryptoQuant has also identified a low network activity for six consecutive months, describing the current stage as a continued period of on-chain participation weakness.
Bitcoin Active Addresses Momentum
Source: CryptoQuant
The last time the market saw a similar pattern was in 2024 — Bitcoin then experienced about a 30% pullback.
This does not mean a replay is certain now, but it reinforces a historical rule: Long-term network softness often coincides with a weakening market confidence.
Breadth Down, But Throughput Unbroken
Bitcoin's transaction count did not drop in sync with active addresses.
In mid-August 2025, the average daily transaction count was about 444,000. Blockchain.com data shows it's been around 439,000 over the past 30 days.
Hourly data still fluctuates, ranging from about 289,000 to 702,000, but the overall throughput trend has not collapsed.
This deviation is key to understanding the current situation.
If transaction volume stays steady while active addresses decline, it indicates fewer entities are conducting an equivalent amount of on-chain activity.
Several factors could cause this, none of which require retail influx. Exchanges and custodians can batch withdrawals; whales can consolidate transfers; institutional fund flows could be handled through fewer wallets; operational activities may also cause a brief surge in transaction counts without true user re-engagement.
The result is: the chain still appears busy, but the underlying participants are shrinking.
This is why breadth declining is more telling than raw throughput. Flat transaction counts may disguise a market increasingly dominated by repeat traders, large institutions, and operational fund flows.
In this scenario, Bitcoin's chain is still functioning normally, but the breadth of user participation it represents is becoming less genuine.
Blockchain analytics firm Santiment provides a more straightforward description from a longer time perspective.
The firm states that since February 2021, the unique addresses transacting Bitcoin have decreased by 42%, and new addresses created have decreased by 47%.
Santiment does not qualify this as evidence that crypto is dead or that a multi-year bear market is locked in, but it does describe a bearish divergence throughout 2025 — Market value rising while Bitcoin's utility metrics weaken.
This tension is now reflected in a six-month trend. Price and market narrative may continue, but the chain itself is becoming increasingly quiet.
Low Fees Point to Shrinking Block Space Demand
Fee data further confirms that Bitcoin Layer 1 is currently in a state of weak demand.
Mempool.space data shows that the network's recent average transaction fee is around $0.24, roughly equivalent to 1.8 sats/vB.
For a network that has experienced sustained block space competition during past price cycles, this fee level is low. Based on the current transaction pace, this fee level implies that the network's daily fee income is less than $100,000.
In contrast, block subsidies currently amount to around 450 BTC per day, making fee income a very small percentage.
Bitcoin Average Block Fees
Source: Mempool.space
This is not an immediate security issue nor does it mean that Bitcoin's security model is facing recent pressure.
This is because block subsidies still dominate miner revenue. However, it does point to a long-term reality that Bitcoin has not yet been forced to confront in this stage of the current cycle.
The topic of transitioning to a fee-supported security budget recurs every cycle, but in the current environment, this transition has not been tested—due to the weak fee demand itself.
In practical terms, the current quiet fee market continues to postpone this discussion.
The chain has not faced sustained congestion pressure, and users have not engaged in fierce bidding wars to get onto the chain. This situation can quickly change in volatile events, speculative frenzies, or new demand shocks, but it has not occurred yet.
Currently, block space is in a noticeably low utilization state compared to previous bull market stages, aligning with the broader backdrop of declining overall participation.
Bitcoin's Empty Mempool
Source: Mononaut
CryptoQuant's analysis also aligns with this fee environment, as low network activity is typically associated with decreased market interest in assets and a general period of losses.
As interest wanes, new participants decline, self-initiated transfers decrease, and fee pressure subsides.
Bitcoin remains an active trading financial asset, but the chain itself no longer reflects broad user participation.
The Macro Environment and ETF Fund Flows are Changing Bitcoin's Trading Behavior
The macro backdrop helps explain why this trend continues.
Bitcoin is becoming more like a macro-sensitive high-beta asset, particularly shining during risk-off periods.
In the past year, U.S. inflation has cooled, with the year-on-year CPI growth rate in January 2026 at 2.4%; the Fed's target rate range was quoted at 3.50% to 3.75% by the end of January.
In a less complex market environment, cooling inflation may support a clearer rebound in risk assets.
However, market attention is focused on several volatility catalysts, including tariff policy uncertainty. This factor has driven sharp swings in rates and the dollar, keeping overall risk appetite unstable.
In this environment, both retail and institutional investors tend to reduce their trading frequency. Retail participation decreases, trader turnover declines. Institutions may hold positions but are more inclined to adjust exposure through off-chain settlement products.
This is why spot Bitcoin ETFs have become key narrative players.
Coinperps data shows that U.S. Bitcoin ETFs have seen continuous net outflows for multiple weeks, with outflows of around $3.8 billion over the past five weeks and about $4.5 billion year-to-date.
Daily Fund Flows for U.S. Bitcoin ETFs in 2026
Source: Coinperps
This has shifted activity from self-custody wallets to broker accounts.
This also explains why the market can remain active while the chain grows quieter. Positions are still changing hands, but more turnover is occurring off-chain.
This marks a significant shift in Bitcoin's role. It is increasingly resembling a financial product wrapped in an institutional shell, while Layer 1 is being more selectively leveraged for settlement, storage, and periodic transfers.
Simultaneously, the daily transactional energy in the crypto space is flowing elsewhere, particularly towards stablecoins.
Coin Metrics identifies stablecoins as a core driver of on-chain activity, with the total stablecoin supply nearing $300 billion and transaction volume steadily rising.
If stablecoins on other chains take on more daily settlement needs, Bitcoin's Layer 1 would naturally become more specialized in function.
This, in itself, does not weaken Bitcoin's investment thesis, but it certainly alters its form.
Three Scenarios for the Next Three to Six Months
The recent six-month decline in network breadth has laid out three potential paths for Bitcoin's future trajectory.
The first is a continuation of apathy, which in a risk-off market environment appears to be the baseline scenario.
In this scenario, active addresses remain low (in the 450K to 600K range), transaction counts remain volatile but not collapsing, fees stay low, and ETF flows remain steady or slightly negative.
Here, Bitcoin could still experience sharp volatility due to macro headlines, but on-chain participation does not confirm a broad-based recovery. The asset's trading logic appears more like a macro tool rather than a network transitioning into a new expansion phase.
The second is a liquidity thaw, representing a more optimistic path.
If inflation continues to cool, loose expectations stabilize risk appetite, ETF flows may shift from net outflows to sustained net inflows. In this environment, the growth of active addresses will be a key confirmation signal.
A rise to 650K to 800K active addresses would signify that participation breadth is recovering, not just a resurgence of price momentum. This appears more like a classic cyclical recovery—price gains supported by the growth in on-chain user participation.
The third is a structural substitution scenario, which may be the most intriguing.
In this scenario, Bitcoin's price rises, but on-chain breadth remains persistently low. ETFs, derivatives, and custodial settlements continue to dominate, while stablecoins take on more transactional demand elsewhere in the crypto space.
Here, Bitcoin is increasingly looking like a digital macro asset and settlement layer rather than a chain with widespread retail activity.
This scenario would mark the evolution of Bitcoin's role, reflecting a profound shift that has taken place compared to years ago.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link
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