Aiman艾曼_BNB

👉what should to know:
The Bank of Japan is poised to raise rates to its highest level since 1995.A rate hike is likely to strengthen the yen against the dollar, and contain inflation.However, it risks further weakening the Japanese economy.
Kazuo Ueda, governor of the Bank of Japan (BOJ), gestures to speak during a budget committee session at the lower house of parliament in Tokyo, Japan, on Tuesday, Dec. 9, 2025. Ueda said the recent pace of increases in Japans long-term bond yields is “somewhat fast,” while adding that long-term yields should be determined by the market in principle.
Japan’s central bank on Thursday kicked off its last policy meeting of the year, with expectations that it will raise benchmark interest rates to their highest in 30 years, as it seeks to move ahead with policy normalization ( Bank of Japan ends the world’s only negative rates regime in a historic move, abandons yield curve control ) set forth last year.
The decision, due Friday, could see rates raised to 0.75% — highest since 1995 — with data from LSEG showing an 86.4% probability of a hike by the Bank of Japan.
A rate hike will likely strengthen the yen against the dollar, and contain inflation, which has run above the BOJ’s target for 43 straight months. But it could further slow a weak Japanese economy that contracted in the third quarter.
Revised GDP numbers showed that Japan’s economy in the three months through September contracted more than initially estimated, shrinking 0.6% quarter on quarter, and 2.3% on an annualized basis.
With a rate hike almost certain, experts said that market focus will be more on the BOJ’s commentary after the decision.

Gregor MA Hirt, global multi-asset chief investment officer at Allianz Global Investors, said in a Tuesday note that the market reaction will depend on the nuances of the BOJ’s communication.

Signals around the neutral, or terminal, rate — one that balances inflation and economic growth — and comments on yen weakness will be some of the things to look out for.
Governor Kazuo Ueda reportedly said earlier this month that it was difficult to estimate the terminal rate, with the central bank pegging it at 1% to 2.5%.

“Unfortunately, the neutral rate of interest is a concept for which we can only produce an estimate with quite a wide range,” Ueda told Japan’s parliament.

While efforts have been made to narrow the rate range, Ueda said that the BOJ must guide monetary policy without clarity on where exactly the neutral rate lies.
Carl Ang, fixed income research analyst at MFS Investment Management, said that an updated estimate on the neutral rate may be shared after the Friday meeting.

👉Pace of rate hikes:
Japan embarked on policy normalization last year, abandoning the world’s only negative interest rate regime that had been in place since 2016. Since then, the BOJ has been consistently maintained it’s stance of gradually raising rates.
Investors will be looking out for the BOJ’s commentary around the pace of future rate hikes.

Dutch bank ING said in a note on Wednesday that while the market largely expects another hike in June 2026, it is more likely that the BOJ will next raise rates only in October.

In contrast, Bank of America estimates a hike in June, while not entirely discounting the BOJ fast-forwarding it to April if the yen weakens rapidly. BofA analysts expect the BOJ to bring the terminal rate to 1.5% by end 2027.
While MFS’ Ang said there were some risks to Japan’s policy normalization path, including a U.S. economic slowdown and escalating China-Japan tensions, it would take a “material shock” to veer the BOJ away from its rate trajectory.

👉Bonds and forex outlook:
The central bank has not directly addressed foreign exchange concerns, but should Ueda comment on the yen’s weakness directly, it would be seen as a “line in the sand,” Allianz’s Hirt said.
The yen has been trading around the 154-157 against the dollar since November, having weakened over 2.5% since Prime Minister Sanae Takaichi, a proponent of looser monetary policy, took office in October
.

#BoJ $BTC

$BTC
U.S. inflation data for November, expected to show a 3.1% increase in CPI, could influence Federal Reserve interest rate decisions.

Bitcoin's price fluctuated between $$86,000 and $90,000 in the last 24 hours, reflecting market uncertainty.U.S. inflation data for November, expected to show a 3.1% increase in CPI, could influence Federal Reserve interest rate decisions.Crypto markets face additional pressure from potential MSCI index exclusions, which could lead to significant outflows.November's consumer price index report, set to be released on Thursday, will be the first one since the U.S. government shutdown ended last month.The Bureau of Labor Statistics has said the release "will not include 1-month percent changes for November 2025 where the October 2025 data are missing." The agency canceled the release of October's data as a result of the 43-day shutdown.
Wall Street is awaiting Thursday's release of the November consumer price index report, as it will mark the first reading for the period since the record-setting U.S. government shutdown ended last month.

According to economists surveyed by Dow Jones, the report – which tracks the average change in prices people pay for a range of goods and services – is expected to show a 12-month inflation rate of 3.1%. When excluding food and energy, core CPI is forecast to post an annual rate of 3.0%.
Crypto traders have had a tough time figuring out the market in the last 24 hours as bitcoin's BTC:$86,761.79 price swung wildly between $86,000 and $90,000.

Things could get more exciting later Thursday with key U.S. inflation data for November coming up. This will give a fresh look at price pressures in the economy after the record government shutdown canceled the October data and left the Federal Reserve in the dark.
👉What the data might show:
The data is expected to show the headline consumer price index (CPI) increased to 3.1% on a yearly basis in November, up from October's 3%, according to FactSet consensus estimates. Core inflation, which excludes volatile food and energy prices, is forecast at 3.1%.
That's still one full point above the Fed's 2% goal, which could embolden hawks at the Fed to talk down expectations of interest rate cuts. As of writing, markets anticipate at least two 25-basis-point Fed rate cuts next year.

👉Expert view:
"This release is highly anticipated, largely because the recent government shutdown-related data disruptions left the Federal Reserve (and the broader market) flying partially blind. With the October report canceled, this is the first comprehensive look at price developments in weeks," Dr Mohamed A. El-Erian is President of Queens' College, Cambridge University and part-time Chief Economic Advisor at Allianz and Chair of Gramercy Fund Management, said on X.
He added that markets will be looking for two things: whether the disinflation trend in services has stronger legs and what remains of the tariff-driven price pass throughs in good inflation.
👉Why Bitcoin might react:
Should the data confirm disinflation, it could prompt markets to price in additional rate cuts for 2026, galvanizing risk taking in financial markets. Note, however, that BTC did not show a sustained bullish reaction to the jobs data released Tuesday, which showed jobless rate at highest since September 2021.
Besides, the 10-year Treasury yield has held sticky above 4% in recent months despite Fed easing. This is partly due to uncertainty about inflation, as CPI has steadily risen from 2.3% in May to 3% in October.

Longer duration yields like the 10-year incorporate investor bets on inflation trends, economic growth, and Fed policy paths. Higher yields signal stronger expectations in these areas and boost attractiveness of fixed-income instruments, denting the appeal of risk assets.
Against this backdrop, a hotter-than-expected inflation report could raise yields further, complicating matters for BTC bulls.

👉Crypto challenges:
Note that crypto-specific factors aren't helping either. For instance, MSCI's review of digital asset treasuries poses a major headwind.
"MSCI is reviewing the index eligibility of digital-asset treasury companies, with potential exclusions for firms holding more than 50% exposure to crypto. If enacted, passive outflows could reach up to USD 2.8 billion, adding pressure to an already fragile market," the market insights team at Singapore-based QCP Capital said.
#USInflationData #cpinews $BTC

#KİTE $KITE @KITE AI
The blockchain firm’s native token debuted Monday with strong activity on Binance and Korean exchanges, following a $18 million Series A raise in September.
Kite’s token hit a $159 million market cap and $883 million FDV, with combined trading volume of $263 million across Binance, Upbit, and Bithumb in its first hours.The network powers an "agentic economy," where autonomous AI agents can transact, pay, and access data using the token.Kite’s total supply is 10 billion tokens, with 48% allocated to the community, 12% to investors, and 20% to the team and early contributors, according to its whitepaper.
Kite, an artificial intelligence (AI)-powered payments blockchain, rolled out its native token on Monday, generating significant trading volume on South Korean exchanges Upbit and Bithumb.

The token debuted with strong market activity on the whole, reaching a $159 million market capitalization and an $883 million fully diluted valuation (FDV) within its first few hours of trading,
Trading volume on Binance topped $85 million with a similar figure being achieved on Upbit and Bithumb, total volume stood at $263 million at press time.

The launch follows Kite’s $18 million Series A raise in September, which brought its total funding to $33 million. The round was aimed at accelerating the development of Kite’s base layer for AI-driven payments and autonomous agent systems.
Kite’s native token underpins its "agentic economy, serving as the medium for payments, staking, and governance across its blockchain network. It enables machine-to-machine and agent-to-agent transactions, allowing autonomous AI agents to execute payments, access data, and purchase compute resources.

Total supply of the token is capped at 10 billion, with 48% being allocated to the community, 12% to investors and 20% to the team and early contributors, according to Kite's whitepaper.

$XRP
The joint venture aims to source $300 million in Ripple Labs equity for institutional and qualified retail investors in South Korea.
👉what should to know:
VivoPower is partnering with Lean Ventures to acquire Ripple Labs shares, indirectly exposing investors to nearly $1 billion in XRP.The joint venture aims to source $300 million in Ripple Labs equity for institutional and qualified retail investors in South Korea.VivoPower expects to earn $75 million over three years from management fees and performance carry without using its own capital.
Nasdaq-listed VivoPower (VVPR) is expanding its XRP-linked strategy through a new joint venture that aims to acquire hundreds of millions of dollars worth of Ripple Labs shares, giving investors indirect exposure to nearly $1 billion worth of underlying XRP.

The company said in a Tuesday release its digital asset unit, Vivo Federation, has been engaged by South Korea–based asset manager Lean Ventures to source an initial $300 million of Ripple Labs equity.
Based on current XRP prices, VivoPower estimates the stake represents roughly 450 million XRP tokens, valued at about $900 million.

The structure stops short of buying XRP outright, however. Instead, Lean Ventures plans to establish a dedicated investment vehicle that will hold Ripple Labs shares sourced by Vivo Federation, targeting institutional and qualified retail investors in South Korea — one of XRP’s largest markets globally.
VivoPower said it has received approval from Ripple to purchase an initial tranche of preferred shares and is negotiating additional purchases from existing institutional holders.

It did not provide further details about the transactions when asked, stating: "Please note that we are legally unable to respond to individual inquiries regarding transactions, acquisitions, mergers, or other market-sensitive matters beyond what has already been publicly disclosed."
A Ripple representative said the company was unable to comment on this topic as of Thursday.

As such, the company does not commit its own balance sheet capital but will earn management fees and performance carry, targeting $75 million in net economic returns over three years if the initial $300 million mandate is reached.
The arrangement builds on VivoPower’s recent pivot toward an XRP-centric treasury strategy. Earlier this year, the company raised $121 million in a private placement led by Saudi investor Abdulaziz bin Turki Abdulaziz Al Saud, positioning itself as one of the first publicly traded firms to anchor its digital asset strategy around XRP rather than bitcoin or ether.

VivoPower has already deployed XRP into yield-generating strategies, including a $100 million allocation through Flare’s FAssets system, and adopted Ripple’s RLUSD stablecoin for treasury operations.
#vivopower #xrp $XRP

👉On stablecoins, RWA tokenization, payments & finance:
Better, more clever onramps/ offramps for stablecoins
Stablecoins accounted for an estimated 46 trillion dollars in transaction volume last year, constantly hitting new all time highs. To put that into perspective, that’s more than 20x the volume of PayPal; close to 3x the volume of Visa (one of the largest payment networks in the world); and is rapidly approaching the volume of ACH, the electronic network for financial transactions like direct deposits and more in the United States.
You can send a stablecoin in less than a second for less than a cent. What remains unsolved, however, is how to connect these digital dollars to the financial rails people actually use already every day — in other words, on/offramps for stablecoins.

A new generation of startups is filling this gap, linking stablecoins to more familiar payment systems and local currencies. Some use cryptographic proofs to let people privately swap local balances for digital dollars. Some integrate with regional networks that draw on QR codes, real-time payments rails, and other features to enable bank-to-bank payments… While others are building more truly interoperable global wallet layers and card-issuing platforms that let users spend stablecoins at everyday merchants. Together, these approaches broaden who can participate in the digital dollar economy — and could accelerate stablecoins being used more directly as mainstream payments.
As these on/off ramps mature, with digital dollars plugging directly into local payment systems and merchant tools, new behaviors will emerge. Workers can be paid in real time across borders. Merchants can accept global dollars without bank accounts. Apps can settle value instantly with users anywhere. Stablecoins will fundamentally shift from a niche financial tool to the foundational settlement layer for the internet.
Thinking about tokenization of real world assets, and stablecoins, in a more crypto-native way
We’ve seen strong interest from banks, fintechs, and asset managers to bring U.S. equities, commodities, indices, and other traditional assets onchain. As more traditional assets come onchain, the tokenization is often skeuomorphic — rooted in the current idea of real-world assets, and not taking advantage of crypto-native features.

But synthetic representations like perpetual futures (perps) allow deeper liquidity and are often simpler to implement. Perps also provide easy-to-understand leverage, so I believe they are the crypto-native derivative with the strongest product-market fit. I also believe that emerging market equities are one of the most interesting asset classes to perpify.
It all comes down to the question of “perpification vs. tokenization”; but either way, we should see more crypto-native RWA tokenization in the coming year.

Along similar lines, in 2026 we’ll see more “origination, not just tokenization” when it comes to stablecoins, which went mainstream in 2025; outstanding stablecoin issuance continues to grow.

But stablecoins without strong credit infrastructure look like narrow banks, which hold specific liquid assets that are considered extra-safe. While narrow banking is a valid product, I don’t believe it will be the backbone of the onchain economy in the long term.
We’ve seen a number of new asset managers, curators, and protocols start to facilitate onchain asset-backed lending against offchain collateral. Often these loans originate offchain and then are tokenized. I think tokenization offers few benefits here, other than perhaps distributed to users that are already onchain. That’s why debt assets should be originated on chain, not originated off chain and tokenized. Origination onchain reduces loan servicing costs, back office structuring costs, and increases accessibility. The challenging part here will be compliance and standardization, but builders are already working on solving those problems.
👉Stablecoins unlock the bank ledger upgrade cycle — and new payment scenarios:
The average bank is running software that is unrecognizable to modern developers: In the 1960s and 1970s, banks were early adopters of large software systems. The second generation of core banking software started in the 1980s and 1990s (for instance, via Temenos’ GLOBUS and InfoSys’ Finacle). But all this software has been aging, and is being upgraded too slowly. As such, the banking industry — especially critical core ledgers, the key databases that track deposits, collateral, and other obligations — still often run on mainframe computers, programmed with COBOL, and with batch file interfaces instead of APIs.
The large majority of global assets live on those same core ledgers that are also decades old. While these systems are battle tested, trusted by regulators, and deeply integrated into complex banking scenarios, they are also holding back innovation. Adding key functionality like realtime payments (RTP) can take months or more likely years, and requires navigating layers of technical debt and regulatory complexity.
That’s where stablecoins come in. Not only were the last couple years when stablecoins found product-market fit and hit the mainstream, but this year, TradFi institutions embraced them at a whole new level. Stablecoins, tokenized deposits, tokenized treasuries, and onchain bonds allow banks, fintechs, and financial institutions to build new products and serve new customers. More importantly, they can do this without forcing these organizations to rewrite their legacy systems — systems that, while aging, have run reliably for decades. Stablecoins thus provide a new way for institutions to innovate.
👉The internet becomes the bank:
As agents arrive en masse, and more commerce happens automatically in the background rather than through user clicks, then the way money — value! — moves needs to change.

In a world where systems act on intent instead of on step-by-step instructions — moving money because an AI agent recognized a need, fulfilled an obligation, or triggered an outcome — value has to travel as fast and freely as information does today. This is where blockchains, smart contracts, and new protocols come in.
A smart contract can already settle a dollar payment globally in seconds. But, in 2026, emerging primitives like x402 make that settlement programmable and reactive: Agents paying each other for data, GPU time, or API calls instantly and permissionlessly — without invoicing, reconciling, or batching. Developers shipping software updates that come bundled with built-in payment rules, limits, and audit trails — without fiat integrations, merchant onboarding, banks. Prediction markets that self-settle in real time as events unfold — where odds update, agents trade, and payouts clear globally in seconds… without a custodian or exchange.
Once value can move this way, the “payment flow” stops being a separate operational layer and becomes a network behavior: Banks become part of the internet’s basic plumbing, assets become infrastructure. If money becomes a packet the internet can route, then the internet doesn’t just support the financial system… it becomes the financial system.
👉Wealth management for all:
Personalized wealth management services have traditionally been reserved for high net-worth clients at banks: It’s expensive and operationally complex to deliver tailored advice, and personalize a portfolio, across asset classes. But as more asset classes are tokenized, crypto rails enable strategies — personalized with AI recommendations and co-pilots — to be executed and rebalanced instantly and with minimal cost.
This is more than just robo advisors; everyone can access active portfolio management, not just passive management. In 2025, TradFi increased its allocation of portfolio exposure to crypto (either directly or via ETPs), but that was just the beginning; in 2026, we’ll see platforms built for “wealth accumulation” — not just “wealth preservation” — as fintechs and centralized exchanges leverage their tech stack lead to own more of this market.
Meanwhile, DeFi tools like Morpho Vaults automatically allocate assets into lending markets with the best risk-adjusted yield — providing a core yield-bearing allocation in a portfolio. Holding remaining liquid balances in stablecoins rather than in fiat, and in tokenized money market funds rather than traditional money market funds, expands the possibilities for further yield.
Finally, retail investors now have easier access to more illiquid private market assets such as private credit, pre-IPO companies, and private equity, as tokenization helps unlock these markets while still maintaining compliance and reporting requirements. As the various components of a balanced portfolio become tokenized (moving along the risk spectrum from bonds to stocks to privates and alts), they can be automatically rebalanced without having to do wire transfers and more.
👉From know your customer (KYC) to ‘know your agent’ (KYA):
The bottleneck for the agent economy is shifting from intelligence to identity.

In financial services, “non-human identities” now outnumber human employees 96-to-1 — yet these identities remain unbanked ghosts. The critical missing primitive here is KYA: Know Your Agent.

Just as humans need credit scores to get loans, agents will need cryptographically signed credentials to transact — linking the agent to its principal, its constraints, and its liability. Until this exists, merchants will keep blocking agents at the firewall. The industry that built that KYC infrastructure over decades now has just months to figure out KYA.
👉We’ll use AI for substantive research tasks:
As a mathematical economist, it was difficult to get consumer AI models to even understand my work process back in January this year; yet by November, I could give models abstract instructions in the same way I would to a doctoral student… And they sometimes return novel and correctly executed answers. Beyond my experience here, we’re starting to see AIs used for research more broadly — especially in reasoning domains, where models are now directly aiding discovery and also autonomously solving Putnam problems (perhaps the world’s hardest university-level math exam).
It’s still an open question which fields this type of research assistance will help most, and how. But I’m expecting AI research to enable, and reward, a new type of polymath research style: one that favors an ability to conjecture relationships between ideas, and quickly extrapolate from even more conjectural answers. Those answers may not be accurate, but can still point in the right direction (at least under some topology). Ironically, it’s kind of like harnessing the power of model hallucinations: When the models get “smart” enough, giving them abstract space to bounce around can still produce nonsense — but can sometimes crack open a discovery, just like how people can be most creative when they’re not working in a linear, clearly stated direction.
Reasoning in this manner will require a new style of AI workflow — not just agent-to-agent, but more agent-wrapping-agent — where layers of models help the researcher evaluate the earlier models’ approaches and successively synthesize the wheat from the chaff. I’ve been using this approach to write papers, while others are conducting patent searches, inventing new forms of art, or (unfortunately) finding novel smart contract attacks.

However: Operating ensembles of wrapped reasoning agents for research will require better interoperability between models, along with a way to recognize and properly compensate each model’s contribution — both problems crypto can help solve.
👉The invisible tax on the open web:
The rise of AI agents is imposing an invisible tax on the open web, fundamentally disrupting its economic foundation. This disruption stems from a growing misalignment between the Context and Execution layers of the internet: Currently, AI agents extract data from ad-supported sites (the Context layer), providing convenience to users while systematically bypassing the revenue streams (like ads and subscriptions) that fund the content.
To prevent the erosion of the open web (and preserve the diverse content that fuels AI itself), we need the mass deployment of technical and economic solutions. This could include models like next-generation sponsored content, micro-attribution systems, or other novel funding models. Existing AI licensing deals are also proving to be a financially unsustainable bandaid, often compensating content providers with a fraction of the revenue they’ve already lost to AI-cannibalized traffic.
The web needs a new techno-economic model where value flows automatically. The key transition for the coming year will be moving from static licensing to real-time, usage-based compensation. This means testing and scaling systems — potentially leveraging blockchain enabled nanopayments and sophisticated attribution standards — to automatically reward every entity that contributes information to an agent’s successful task.

👉Privacy will be the most important moat in crypto:
Privacy is the one feature that’s critical for the world’s finance to move onchain. It’s also the one feature that almost every blockchain that exists today lacks. For most chains, privacy has been little more than an afterthought.

But now, privacy by itself is sufficiently compelling to differentiate a chain from all the rest. Privacy also does something more important: It creates chain lock-in; a privacy network effect, if you will. Especially in a world where competing on performance is no longer enough.
Thanks to bridging protocols, it’s trivial to move from one chain to another as long as everything is public. But, as soon as you make things private, that is no longer true: Bridging tokens is easy, bridging secrets is hard. There is always a risk when moving in or out of a private zone that people who are watching the chain, mempool, or network traffic could figure out who you are. Crossing the boundary between a private chain and a public one — or even between two private chains — leaks all kinds of metadata like transaction timing and size correlations that makes it easier to track someone.
Compared to the many undifferentiated new chains where fees will likely be driven down to zero by competition (blockspace has become fundamentally the same everywhere), blockchains with privacy can have much stronger network effects. The reality is that if a “general purpose” chain doesn’t already have a thriving ecosystem, a killer application, or an unfair distribution advantage, then there’s very little reason for anyone to use it or build on top of it — let alone be loyal to it.
When users are on public blockchains, it’s easy for them to transact with users on other chains — it doesn’t matter which chain they join. When users are on private blockchains, on the other hand, the chain they choose matters much more because, once they join one, they’re less likely to move and risk being exposed. This creates a winner-take-most dynamic. And because privacy is essential for most real-world use cases, a handful of privacy chains could own most of crypto.
👉The (near) future of messaging isn’t just quantum-resistant. It’s decentralized:
As the world prepares for quantum computing, many messaging apps built on encryption (Apple, Signal, WhatsApp) have led the way, all doing great work. The problem is that every major messenger relies on our trusting a private server run by a single organization. Those servers are an easy target for governments to shut down, backdoor, or coerce into giving up private data.
What good is quantum encryption if a country can shut down one’s servers; if a company has a key to the private server; or even if a company has a private server? Private servers require “trust me” — but having no private server means “you don’t have to trust me.” Communication doesn’t need a single company in the middle. Messaging needs open protocols where we don’t have to trust anyone.
The way we get there is by decentralizing the network: No private servers. No single app. All open source code. Best-in-class encryption — including against quantum threats. With an open network there is no single person, company, non-profit, or country that can take away our ability to communicate. Even if a country or company does shut down an app, 500 new versions will pop up the next day. Shut down a node and there is an economic incentive (thanks to blockchains and more) for a new one to take its place immediately.
When people own their messages like they own their money — with a key — everything changes. Apps may come and go, but people will always keep control of their messages and identity; the end users can now own their messages, even if not the app.
This is greater than quantum resistance and encryption; it’s ownership and decentralization. Without both, all we’re doing is building unbreakable encryption that can still be switched off.

‘👉secrets as-a-service’
Behind every model, agent, and automation lies a simple dependency: data. But most data pipelines today — what’s fed into or out of the model — are opaque, mutable, and unauditable. This is fine for some consumer applications, but many industries and users (like finance and healthcare) require companies to keep sensitive data private. It’s also a massive blocker for the institutions looking to tokenize real world assets right now.
I believe we need secrets-as-a-service: New technologies that can provide programmable, native data access rules; client-side encryption; and decentralized key management enforcing who can decrypt what, under which conditions, and for how long… all enforced onchain. Combined with verifiable data systems, secrets could then become part of the internet’s fundamental public infrastructure — rather than an application-level patch, where privacy is bolted on after the fact — making privacy core infrastructure.
👉From ‘code is law’ to ‘spec is law’
Recent DeFi hacks have hit battle-tested protocols that have strong teams, diligent audits, and years in production. These incidents underscore an uncomfortable reality: Today’s standard security practice is still largely heuristic and case-by-case.

To mature, DeFi security needs to move from bug patterns to design-level properties, and from “best-effort” to “principled” approaches:
On the static/ pre-deployment side (testing, audits, formal verification), that means systematically proving global invariants rather than verifying hand‑picked local ones. AI-assisted proof tools now being built by several teams can help write specs, propose invariants, and offload much of the manual proof-engineering that used to make this prohibitively expensive.On the dynamic/ post-deployment side (runtime monitoring, runtime enforcement, etc.), those invariants can turn into live guardrails: a last line of defense. These guardrails would be encoded directly as runtime assertions that every transaction must satisfy.
👉Prediction markets go bigger, broader, and smarter:
Prediction markets have already gone mainstream, and this coming year, they’ll only become bigger, broader, and smarter as they intersect with crypto and AI — while also posing new and important challenges for builders to resolve.
First, many more contracts will be listed. This means we’ll be able to access real-time odds not just for major elections or geopolitical events, but for all kinds of in-the-weeds outcomes and complex, intersecting events. As these new contracts surface more information and become part of the news ecosystem (already happening), they’ll raise important societal questions about how we balance the value of this information and how to better design them so they are more transparent, auditable, and more — which is possible with crypto.
To handle the much larger volume of contracts, we’ll need new ways of aligning on truth to resolve the contracts. Centralized platform resolution (did a given event actually happen? how do we confirm it?) is important, but disputed cases like the Zelensky suit market and the Venezuelan election market show the limits. To address these edge cases and help prediction markets scale to more useful applications, new kinds of decentralized governance and LLM oracles can help determine truth for contested outcomes.
Do prediction markets replace polling? No; they make polling better (and polling information can be fed into prediction markets). As a political scientist, I’m most excited by how prediction markets can function in concert with a rich and vibrant polling ecosystem — but we’ll need to lean on new technologies like AI, which can improve the survey-taking experience; and crypto, which can provide new ways to prove that poll/ survey respondents are not bots but humans, among other things.

👉The rise of staked media
Cracks in the traditional media model — with its supposed objectivity — have been showing for a while now. The internet gave everyone a voice, and more operators, practitioners, and builders are now speaking directly to the public. Their perspectives reflect their stakes in the world and, counterintuitively, audiences often respect them not despite their interests but because of them.
What’s new here isn’t the rise of social media, but the arrival of cryptographic tools that allow people to make publicly verifiable commitments. As AI makes it cheap and easy to generate unlimited content — claiming anything from any point of view or persona, real or fabricated — simply relying on what people (or bots) say can feel insufficient. Tokenized assets, programmable lockups, prediction markets, and onchain histories offer stronger foundations for trust: A commentator can publish an argument and also prove they’re putting their money where their mouth is. A podcaster can lock tokens to show they’re not opportunistically flipping or “pumping and dumping.” An analyst can tie forecasts to markets that settle publicly, creating an auditable track record.
👉Crypto offers a new primitive for use beyond blockchains:
For years, SNARKs — cryptographic proofs that let you verify computation without re-executing it — have been largely a blockchain-only technology. The overhead was simply too high: Proving a computation could take 1,000,000X more work than just running it. Worth it when you’re amortizing across many thousands of validators, but impractical anywhere else.

That’s about to change. In 2026, zkVM provers will hit roughly 10,000X overhead with memory footprints in the hundreds of megabytes — fast enough to run on phones, cheap enough to run everywhere. Here’s one reason 10,000x could be a magic number: High-end GPUs have ~10,000x more parallel throughput than a laptop CPU. By the end of 2026, a single GPU will be able to generate proofs of CPU execution in real time.

👉Trading as a way station, not the last stop, for crypto businesses:
It seems like every crypto company that’s doing well today, outside of stablecoins and some core infrastructure, has pivoted to or is pivoting to trading. But if “every crypto company becomes a trading platform”, then where does that leave everyone? Having so many players all doing the same thing cannibalizes mindshare for the many, and leaves just a few big winners. This means those that pivoted too quickly to trading missed the opportunity to build a more defensible, more durable business.
There’s nothing wrong with trading — it’s an important market function — but it doesn’t have to be the final destination. The founders who focus on the “product” part of product-market fit may end up the bigger winners.

👉Unleashing the full potential of blockchains… when legal architecture finally matches technical architecture:
One of the biggest barriers to building blockchain networks in the U.S. over the last decade has been legal uncertainty. Securities laws have been stretched and selectively enforced, forcing founders into a regulatory framework built for companies rather than for networks. For years, mitigating legal risk replaced product strategy; engineers took a backseat to lawyers.
This dynamic led to lots of weird contortions: Founders were told to avoid transparency. Token distributions became legally arbitrary. Governance became theater. Organizational structures optimized for legal cover. And tokens were designed to avoid economic value/ not have a business model. Worse yet, crypto projects that played fast and loose with the rules often outpaced the good-faith builders.
But crypto market structure regulation — which the government is closer to passing than it’s ever been — has the potential to eliminate all of these distortions next year. If passed, this legislation would incentivize transparency, create clear standards, and replace “enforcement roulette” with more clear, structured paths for fundraising, token launches, and decentralization. After GENIUS, the proliferation of stablecoins has exploded; legislation around crypto market structure would be an even more significant shift, but this time for networks.
In other words, such regulation would enable blockchain networks to operate like networks — open, autonomous, composable, credibly neutral, and decentralized.
#2026Crypto #CryptoMarket

$BTC
Michael Saylor delivered a characteristically bold take on Dec. 16 about Bitcoin and the quantum leap:

“The Bitcoin Quantum Leap: Quantum computing won't break Bitcoin—it will harden it. The network upgrades, active coins migrate, lost coins stay frozen. Security goes up. Supply comes down. Bitcoin grows stronger.”
The statement captures the optimistic case for Bitcoin's post-quantum future. Still, the technical record reveals a messier picture where physics, governance, and timing determine whether the transition strengthens the network or triggers a crisis.

👉Quantum won't break Bitcoin (if migration happens in time):

Saylor's core claim rests on the notion of directional truth. Bitcoin's main quantum vulnerability"Bitcoin is unlikely to face any real threat from quantum computers for another 20–40 years, according to Blockstream CEO Adam Back, who argues that fears are driven more by hype than physics. While Shor’s algorithm could theoretically break Bitcoin’s ECDSA and Schnorr signatures on secp256k1, doing so would require thousands of error-corrected logical qubits—several orders of magnitude beyond today’s noisy, small-scale quantum machines. Crucially, this makes quantum risk a long-term engineering problem rather than an imminent existential crisis. Bitcoin can migrate well before danger arises by adopting NIST-standardized post-quantum signature schemes via soft forks, with proposals like BIP-360 enabling gradual, hybrid transitions. Given existing standards, active developer roadmaps, and decades of lead time, Bitcoin has ample runway to upgrade its cryptography long before quantum computers become cryptographically relevant." sits in its digital signatures, not proof-of-work.
from public keys once a fault-tolerant quantum computer reaches roughly 2,000 to 4,000 logical qubits.

Current devices operate orders of magnitude below that threshold, placing cryptographically relevant quantum computers at least a decade out.

NIST has already finalized the defensive tools Bitcoin would need. The agency published two post-quantum digital signature standards, the ML-DSA (Dilithium) and SLH-DSA (SPHINCS+), as FIPS 204 and 205, with FN-DSA (Falcon) progressing as FIPS 206.
These schemes resist quantum attacks and could be integrated into Bitcoin via new output types or hybrid signatures. Bitcoin Optech tracks live proposals for post-quantum signature aggregation and Taproot-based constructions, with performance experiments showing SLH-DSA can function on Bitcoin-like workloads.

What Saylor's framing omits is the cost. Research from the Journal of British Blockchain Association argues that a realistic migration is a defensive downgrade: security improves against quantum threats, but block capacity could fall by roughly half.

Node costs rise because current post-quantum signatures are larger and more expensive to verify. Transaction fees climb as each signature consumes more block space.
The hard part is governance. Bitcoin has no central authority to mandate upgrades. A post-quantum soft fork would require overwhelming consensus among developers, miners, exchanges, and large holders, all moving before a cryptographically relevant quantum computer appears.

A16z's recent analysis emphasizes that coordination and timing pose greater risks than the cryptography itself.
👉Exposed coins become targets, not frozen assets:
Saylor's claim that “active coins migrate, lost coins stay frozen” oversimplifies the on-chain reality. Vulnerability depends entirely on the address type and whether the public key is already visible.

Early pay-to-public-key outputs place the raw public key directly on-chain and permanently expose it.

Standard P2PKH and SegWit P2WPKH addresses hide the public key behind hashes until the coins are spent, at which point the key becomes visible and quantum-stealable.

Taproot P2TR outputs encode a public key in the output from day one, making those UTXOs exposed even before they move.
Analyses estimate that roughly 25% of all Bitcoin is already in outputs with publicly revealed keys. Deloitte's breakdown and recent Bitcoin-focused work converge on this figure, encompassing large early P2PK balances, custodian activity, and modern Taproot usage.

On-chain research suggests approximately 1.7 million BTC in “Satoshi-era” P2PK outputs and hundreds of thousands more in Taproot outputs with exposed keys.

Some “lost” coins are not frozen, but rather ownerless and could become a bounty for the first attacker with a capable machine.

Coins that have never revealed a public key (single-use P2PKH or P2WPKH) are protected by hashed addresses, for which Grover's algorithm provides only a square-root speedup, which parameter adjustments can compensate for.
The most at-risk slice of supply is precisely dormant coins locked to already-exposed public keys.

👉Supply effects are uncertain, not automatic:
Saylor's assertion that “security goes up, supply comes down” separates cleanly into mechanics and speculation.

Post-quantum signatures, such as ML-DSA and SLH-DSA, are designed to remain secure against large, fault-tolerant quantum computers and are now part of official standards.

Bitcoin-specific migration ideas include hybrid outputs that require both classical and post-quantum signatures, as well as signature-aggregation proposals to reduce chain bloat.
But supply dynamics are not automatic, and three competing scenarios exist.

The first is “supply shrink via abandonment,” where coins in vulnerable outputs whose owners never upgrade are treated as lost or explicitly blocklisted. The second is “supply distortion via theft,” where quantum attackers drain exposed wallets.

The remaining scenario is “panic before physics,” where the perception of looming quantum capability triggers sell-offs or chain splits before any actual machine exists.

None of these guarantees a net reduction in circulating supply that is cleanly bullish. They could just as easily produce a messy repricing, contentious forks, and a one-time wave of attacks on legacy wallets.
Whether supply “comes down” hinges on policy choices, uptake rates, and the attacker's capabilities.
SHA-256-based proof-of-work is relatively robust because Grover's algorithm only gives a quadratic speedup.

The more subtle risk lies in the mempool, where a transaction spending from a hashed-key address reveals its public key while it waits to be mined.

Recent analyses describe a hypothetical “sign-and-steal” attack in which a quantum attacker watches the mempool, quickly recovers a private key, and races a conflicting transaction with a higher fee.

👉What the math actually says:
The physics and standards roadmap agree that quantum does not automatically break Bitcoin overnight.
There is a window, possibly a decade or more, for a deliberate post-quantum migration. However, that migration is costly and politically hard, and a non-trivial share of today's supply already sits in quantum-exposed outputs.

Saylor is directionally right that Bitcoin can harden. The network can adopt post-quantum signatures, upgrade vulnerable outputs, and emerge with stronger cryptographic guarantees.

However, the claim that “lost coins stay frozen” and “supply comes down” assumes a clean transition in which governance cooperates, owners migrate over time, and attackers never exploit the lag.
Bitcoin can come out stronger, with upgraded signatures and possibly some effectively burned supply, but only if developers and large holders move early, coordinate governance, and manage the transition without triggering panic or large-scale theft.

Whether Bitcoin grows stronger depends less on quantum capability timelines than on whether the network can execute a messy, expensive, politically fraught upgrade before the physics catches up. Saylor's confidence is a bet on coordination, not cryptography.
👉In short✅
The article argues that while quantum computing is unlikely to break Bitcoin in the near term, Michael Saylor’s claim that it will ultimately “harden” the network overlooks serious transition risks. Technically, Bitcoin has decades of lead time and viable post-quantum cryptographic standards already exist, meaning a successful upgrade is possible. However, migrating to post-quantum signatures would be costly, reduce efficiency, and require rare, broad consensus across the ecosystem.

Crucially, around 1.7 million BTC already sit in outputs with publicly exposed keys, making them vulnerable to future quantum attacks rather than safely “frozen.” Supply reduction is therefore not guaranteed and could instead come through theft, panic, or contentious governance decisions. The article concludes that Bitcoin’s quantum resilience depends less on physics and more on whether the network can coordinate a timely, politically difficult upgrade before quantum capabilities arrive.
$BTC #bitcoin #MichaelSaylor