When trust is no longer trusted

From Trust Minimization to Trust Instantiation: Cryptofinance Philosophy in the AI Agent Era

Akasha · February 2026

"Do Not Trust, Verify." - But What Then?

Prologue: Morning in Baima Village

In February, the air in Baima Village is as clean as a contract that has not yet been written. Snow fell from yesterday to today, and from today to tomorrow - time is not linear here, but like a state machine that is constantly being covered. Each layer of white is an update of the previous layer, rather than covering it. The moment you step on it, the footprints in the snow are the only fact you can verify.

This scene reminds me of the current moment in the crypto world. Crypto in early 2026 is standing at its most critical philosophical fork. Not about price forks, not about Layer 1 or Layer 2 forks, but about a more fundamental question: When we successfully eliminate trust, can we still generate the future?

This question has never been more pressing in the history of encryption over the past seventeen years. Starting from the sentence "What is needed is an electronic payment system based on cryptographic proof instead of trust" written by Satoshi Nakamoto in 2008, the narrative of the entire industry has been based on a concise and radical philosophical premise - Trust Minimization. We compress trust from human psychological judgment into the execution structure of the code. We replace promises with hashes, relationships with signatures, and faith with verification. All this was once a victory. But today, when AI Agents begin to enter the economic collaboration network in the form of Intent Entity, when the annual transaction volume of the prediction market exceeds 40 billion US dollars, and when the total locked-up value of DeFi remains at the level of 100 billion US dollars after many cycles, we have to face an uncomfortable fact: a machine that can only verify the past is trying to generate the future.

This article is a complete narrative from philosophy to data, from history to the future. It will trace the complete arc of crypto finance from Trust Minimization to Behavioral Coordination to Agent Intent Economy and ultimately to Trust Instantiation. Each argument is based on real market data and cases, but its core concern is always a philosophical question: We have invented a system that does not require trust, but can a world without trust still produce something worthy of trust?

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Chapter 1: The Collapse of Trust—Why We Need to Eliminate Trust

In large-scale systems, trust does not stabilize with scale, but becomes corrupted as complexity increases. This is not a moral judgment, but a systems theory. Banks need to be regulated because banks can do evil; rating agencies need to be audited because rating agencies are complicit; countries need laws because the country itself can default. All systems that rely on the credibility of the subject will gradually evolve into the weakest node in the game in complex networks.

This is not a theoretical deduction, but a history that has been proven repeatedly. In 2008, subprime-backed securities rated AAA evaporated overnight, directly triggering the global financial crisis. Ratings giants like Moody’s and S&P are not out of incompetence, but out of conflicts of interest embedded in their business models—the issuer-pays model turns “objective ratings” into a structural joke. When FTX collapsed in November 2022, more than $8 billion in customer assets were misappropriated, and no one on the chain noticed because those assets were never actually managed on the chain. Platforms can freeze accounts and banks can restrict withdrawals - these are not accidental failures of the system, but the inevitable degradation of trust under conditions of scale.

Therefore, the real goal of Bitcoin has never been "decentralization" - this is just a means - but to avoid relying on trust. Because once future sustainability is entrusted to the ethics of one person or the commitment of an institution, it will eventually become a risk.

Crypto’s philosophical response is radical: compress trust into verification, promises into hashes, and relationships into signatures. On-chain lending protocols such as MakerDAO do not care who the borrower is, only whether the mortgage rate reaches the liquidation threshold. Trust is transferred from a psychological judgment to an execution structure, from the language world to the state machine world. Trust Minimization has become the default premise of the entire system and the spiritual core of the encryption movement in the past seventeen years.

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Chapter 2: The Triumph of Validation—An Economy Without Commitments

When the system begins to only verify behaviors and no longer trusts the subject, the smallest unit of economic collaboration also undergoes fundamental changes: from commitment to execution, from relationship to invocation. An address that complies with the rules is equivalent to a subject; a successful call is equivalent to a decision.

The victory of this paradigm is clearly visible in the data. As of the third quarter of 2025, the total locked-up value (TVL) of DeFi had hit a record high of US$237 billion. Although it fell back to approximately US$117 billion due to market sell-off in Q4, it remained in the range of US$105-140 billion at the beginning of 2026, nearly twice the low of US$50 billion after the collapse of FTX. Ethereum still accounts for about 56-68% of DeFi TVL, and Solana has become the clear second tier with about $9.2 billion. On-chain DeFi lending captured approximately two-thirds of the record $73.6 billion crypto-backed loan market by the end of 2025.

What is more noteworthy is the internal logic of the verification system. Uniswap's AMM doesn't care who you are, it only cares whether you paid slippage and handling fees. Aave's lending protocol doesn't care about your credit history, only whether you have enough collateral - which is why Aave ranks at the top of the protocol rankings with a TVL of about $27 billion. Yearn can superimpose strategies onto Curve and then onto Convex. The generation of these returns does not rely on any long-term commitment, but only relies on immediate status changes. Lido leads the staking track with a TVL of approximately US$27.5 billion, and EigenLayer has opened up the re-pledge market with a TVL of approximately US$13 billion.

Stablecoin markets are the most spectacular implementation of the verification paradigm. In 2025, the total market value of stablecoins will increase by 49% from US$205 billion at the beginning of the year to more than US$300 billion. USDT occupies approximately 58% of the market with a market value of approximately US$175 billion and an average daily trading volume of US$144 billion; USDC ranks second with approximately US$74 billion. The total stablecoin transaction volume for the year reached 33 trillion US dollars, a year-on-year increase of 72% - which is close to the throughput of Visa's global network. Stablecoin issuers hold approximately $155 billion in U.S. Treasury bonds, collectively becoming one of the largest holders of U.S. government debt in the world. Visa's stablecoin settlement volume has reached an annualized scale of US$4.5 billion by January 2026, a year-on-year increase of 460%.

The philosophical implications behind these numbers are profound: an economic system based entirely on verification rather than trust is no longer an experiment but a reality. Execution replaces commitment, and behavior is more important than subject. So relationships are replaced by status updates, and validation replaces belief.

The system has gained unprecedented stability, but it has also gradually lost its ability to generate the future. Because it can only confirm whether the past happened, but cannot maintain whether the future is aligned.

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Chapter 3: Fatigue of behavioral machines—when verification crushes meaning

However, when all relationships are reduced to verification issues, the system begins to no longer distinguish between trustworthy subjects and verifiable actions. DAO can vote, but no one takes responsibility; governance proposals can be passed, but no one actually implements the roadmap; DeFi can be combined, but no one commits to long-term commitment; NFT can be traded, but no consensus can be formed. Because at the execution level, the success of an action only means that it complies with the rules, but does not mean that it represents any long-term intention.

MEV (Maximum Extractable Value) is the most nakedly material expression of this philosophical dilemma. On Ethereum, MEV bots compete for ordering rights in blocks—sandwich attacks alone accounted for more than 95,000 between November 2024 and October 2025, according to exclusive data from EigenPhi. Although the monthly withdrawal volume dropped from nearly US$10 million at the end of 2024 to approximately US$2.5 million in October 2025 (the average monthly net profit after deducting gas costs is approximately US$260,000), the frequency of attacks remains high, with an average of 60,000 to 90,000 per month. About 70% of sandwich attacks are related to a single entity jaredfromsubway.eth, whose V2 version of the bot can already target up to four victims at the same time.

On Solana, the situation is equally shocking. In the 16 months between January 2024 and May 2025 alone, Sandwich bots withdrew between $370 million and $500 million from users, involving more than 8.5 billion transactions and more than $1 trillion in DEX trading volume. The average profit from each sandwich attack is only about $3 - but with more than 4,400 operations per day, it becomes a non-stop value extraction machine.

The funding rate of perpetual contracts continues to fluctuate, and the APR of liquidity mining continues to change, and the optimization of these behaviors only means that risks are reallocated faster. In Q3 of 2025, DeFi TVL reached a record high of US$237 billion, but the average number of daily active wallets dropped by 22.4% during the same period, from the Q2 level to an average of 18.7 million per day. The number of active wallets for AI dApps dropped from 4.8 million in Q2 to 3.1 million in Q3. Virtuals Protocol—the benchmark platform in the field of AI Agents—slumped from an average of 10,000 daily active wallets in Q2 to 1,000-1,500.

These figures reveal a deep contradiction: TVL is rising, but reality is not being generated. Capital is pouring in, but humans are withdrawing. Systems are becoming more efficient, but meaning is being squeezed out of them. Crypto has gradually become a behavioral coordination machine - Transfer can occur, but Trust cannot be formed; value can be transferred, but vision cannot be precipitated.

In the third quarter of 2025, hackers stole more than $434 million from crypto systems, with the largest attacks including a $42 million loss in July through malicious contracts exploiting GMX V1’s internal accounting defenses. After DeFi market value hit a peak of $181 billion at the end of September 2025, Q4 plummeted 37.2% to $100.9 billion amid a market sell-off triggered by the threat of tariffs. These are not random events, but inevitable symptoms of a system that only validates behavior but fails to anchor intent.

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Chapter 4: Entry of Agent - When Intention Becomes the Minimum Unit

When AI Agent begins to enter the encryption system, this problem changes from an efficiency problem to an existential problem. Because agents are not simple executors, but intentional entities - they not only act, but also continue to generate desires and preferred paths. As a result, the economic subject gradually shifted from Human to Agent Network. Behavior is no longer the smallest unit, and Intent becomes the smallest unit.

Data is charting the contours of this transformation. As of October 2025, CoinGecko lists more than 550 AI Agent crypto projects with a total market value of approximately $4.34 billion. By August 2025, the AI ​​crypto space has expanded to nearly 1,200 tokens, with a total market capitalization of more than $29.5 billion—a nearly 10-fold increase from $3.2 billion a year ago. In Q1 of 2025, AI was the hottest crypto narrative after Meme coins, occupying 5 seats among the top 20 stories tracked by CoinGecko, capturing 35.7% of global investors’ attention share – exceeding Meme coins’ 27.1%. By Q2, AI dApp’s industry dominance reached 18.6%, almost tying games (20.1%) to become the leading category.

DeFAI - the fusion of AI and DeFi - is becoming the most transformative sector. The field is expected to expand from approximately $1 billion in 2025 to $10 billion. AI Agent scans more than 50 order books around the clock and executes transactions within milliseconds to capture arbitrage opportunities, which account for approximately 5-10% of daily trading volume. Bots have redeployed over $2 billion in TVL across lending and yield farming protocols, chasing 12-20% annualized returns.

Virtuals Protocol has become the leading AI Agent launch platform in the encryption field, allowing anyone to build, own and monetize autonomous agents on Base and Solana through its GAME framework and Agent Commerce Protocol (ACP). At the end of October 2025, VIRTUAL surged nearly 100% in four days after integrating Coinbase’s x402 payment standard, which enables instant stablecoin payments between agents, with weekly transaction volume soaring from less than 5,000 to more than 25,000.

ElizaOS (formerly ai16z Ecosystem) - What started as a Solana DAO modeled after a16z has grown into a developer platform with over 200 open source plug-ins, enabling AI Agents to run across Discord, Telegram, X and on-chain environments. Fetch.ai launches $10 million accelerator to invest in AI Agent startups. Olas announced an accelerator program with grants of up to $1 million to create new autonomous agents in its Pearl app store.

Deeper changes are happening: Large language models (LLMs) are replacing manual transaction signing in favor of intent-based execution. Protocols such as Hey Anon and Griffin already allow users to perform complex operations in natural language, such as “rebalance my portfolio to high-yielding stablecoins on three chains.” CoinMarketCap predicts that by 2026, most mainstream crypto wallets will have introduced natural language intent execution.

This means a fundamental paradigm shift: the market is no longer just a resource allocation field, but has gradually become a real negotiation field. In the prediction market, the price no longer just reflects the current situation, but also folds the preferences of countless agents for the future. Automated funds and AutoFi layers such as Supra and Fetch.ai utilize autonomous agents to execute real-time data-driven strategies without any human intervention.

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Chapter 5: Prediction Market—the first experimental field for real folding

If DeFi is the triumphal monument of the verification paradigm, then prediction markets are the first testing ground for the intention economy – where prices are not a record of the past, but a collective fold of the future.

In 2025, the prediction market experienced explosive growth. Polymarket and Kalshi combined have achieved nearly $40 billion in transaction volume, an increase of nearly 400% over the previous year. By the end of 2025, monthly trading volume will stabilize at more than $13 billion. Polymarket processed more than $33 billion in transactions throughout the year, and Kalshi's annualized transaction volume reached $50 billion. Together, the two platforms hold about 85-90% of the market share.

Behind these numbers lies a philosophical revolution. The 2024 U.S. election is prediction markets’ “Cambrian moment” — when all the mainstream polls say it’s “too close,” Polymarket’s odds are steadily pointing to a Trump victory, with total bets reaching $3.7 billion. The final Electoral College result of 312 to 226 accurately verified the market’s collective judgment. Academics are beginning to revisit an age-old question: Is asking people to "vote with their money" really more honest than expert predictions? The data gives the answer - Polymarket's accuracy rate exceeded 94% in the entire month before market analysis, and the Brier score was concentrated around 0.09 (close to 0 indicating perfect prediction), and in the last few days it was close to 0.00-0.01.

But prediction markets also expose deep cracks in the verification paradigm. Across Polymarket’s 860,000 transactions and 17,218 markets, only 0.51% of wallets achieved a net profit of more than $1,000. Arbitrageurs extracted more than $40 million in "risk-free profits" from Polymarket between April 2024 and April 2025. Cross-platform arbitrage, information arbitrage, speed trading—these strategies are exactly the same as MEV extraction in DeFi, but they are just disguised as an "information discovery mechanism."

Even more ironic is the "Maduro trade" incident: a Polymarket user made $400,000 betting on Maduro's arrest hours before international news agencies officially reported it. This raises a core tension: How to maintain market accuracy while preventing it from becoming a "hotbed of insider trading"? U.S. Representative Ritchie Torres has proposed the "Public Integrity Financial Prediction Markets Act of 2026", which aims to prohibit government officials from trading in policy-related markets.

ICE's (parent company of the New York Stock Exchange)'s $2 billion investment in Polymarket, Kalshi's $5 billion valuation in a $300 million funding round (with participation from Sequoia, a16z, Paradigm), Robinhood naming event contracts as its fastest-growing business line (estimated annual revenue of $300 million) - these all mark the transformation of prediction markets from a "speculative casino" to an "information-as-asset class."

However, what the prediction market can fold is still only the probability judgment about the future, not the generation of the future itself. It is the middle ground in the transition from the verification paradigm to the intention economy - it starts to process "future" information, but its mechanism is still transactions and settlements, rather than collaboration and commitment.

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Chapter 6: The Limits of Trust Minimization—Why Trustless Structures Can’t Generate Reality

Verification cannot save the intent. On-chain voting can confirm whether a certain resolution is passed, but it cannot guarantee whether the executor is willing to invest in the long term. The future is not traded, but generated - the generation of multi-subject reality requires long-term desire folding, and the trustless structure precisely cancels this folding ability.

Let’s face the paradox in the data. 2025, DeFi TVL hit a record high, and stablecoin trading volume reached an astronomical figure of 33 trillion US dollars, but at the same time: the daily active wallets in the dApp industry dropped by 22.4%; the activity of AI dApps plummeted by 35%; although NFT sales hit a new high (Q3 exceeded 18.1 million pieces), wallet participation was only Growth of 28.6%, suggesting deepening belief among existing participants rather than an influx of new users; RWA (real world asset) tokenization has grown from $6 billion in 2022 to more than $30 billion by the end of 2025, but this is essentially an on-chain mirroring of traditional assets rather than the creation of a native digital reality.

This is a systemic signal: capital is increasing, but participants are decreasing; efficiency is improving, but meaning is diluting. The fluctuations in the perpetual contract market, the intensification of MEV competition, and the proliferation of short-term arbitrage strategies have gradually made the entire system TraFi-like, that is, casino-like. All financial activities remain in the cycle of short-term risk hedging and yield optimization.

The global AI market is valued at US$294 billion in 2025 and is expected to grow to US$376 billion by the end of 2026 and reach US$2.48 trillion by 2034. At the same time, the crypto AI sector is only $22 billion – less than one-tenth of the global AI market. This "structural decoupling" is no accident: mainstream AI benefits from institutional funding, government support, and regulatory clarity, while the crypto-AI sector relies mainly on retail funding and faces liquidity challenges and investor skepticism.

The nature of the problem is not technical, but philosophical: How can a system designed to eliminate trust foster long-term collaboration that requires trust to exist? When Agents begin to pour into the system as intentional entities, what they need is not more verification, but a brand-new mechanism - making trust no longer a psychological state, but an executable structure.

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Chapter 7: Trust Instantiation——The instantiation of trust

Trust Instantiation is the possible future. Instead of returning to the interpersonal trust of the old world, or institutional commitment, let Trust move from a psychological state into an execution structure, making it a Reality Participation Weight - it no longer determines what you can do, but determines what will happen in the future.

When AI turns intelligence and execution capabilities into infrastructure that can be replicated, outsourced, and biddable, an implicit premise that the old finance and old encryption systems rely on is completely changed: the reason why past collaboration can rely on trust minimization to a certain extent is because "decision-execution-commitment" is still highly bound to a small number of subjects in reality. The cost of behavior, change of words, and regret is high. Therefore, as long as Verification locks transactions and performance, it is enough to maintain most of the market order; but in Agent In this era, intention expression and execution are automatically separated. Subjects can issue unlimited intentions, launch unlimited strategies, generate unlimited narratives and assets at almost zero cost, and realize short-term benefits immediately, while outsourcing long-term consequences to the system and others. As a result, "verifiable actions" will become cheaper and cheaper, and "non-verifiable commitments" will become increasingly scarce. This constitutes a structural reversal: the better the system is at verifying behavior, the more it will make the behavior worthless; the less the system lacks the measurement of commitment, the more it will make commitment become an exploited public good. Therefore, the key scarcity in the future is no longer execution ability, but commitment ability and collaborative continuity across time. Trust must be upgraded from a psychological state to an execution structure, otherwise the long-term intentions of multiple agents cannot be precipitated in the system and will only be continuously drained by short-term strategies.

Under this new condition, the boundary of Trust Minimization becomes clear: it can guarantee Execution Stability, but it cannot guarantee Intent Continuity. AI agents can split the same target into countless paths to solve, arbitrage, sort, and attack, and can even perform millisecond-level rewrites between different chains, different protocols, and different liquidity sources, resulting in a market that "runs according to rules" more like a continuously optimized behavioral machine - transactions, clearing, and routing are all smoother, but there is no mechanism to write "who is continuously delivering the same future" into the system state. In other words, Verification can only answer "what happened" but cannot answer "who is responsible for the future"; and when the Agent network becomes a mainstream participant, the latter is the key variable that determines whether the market can return to reality from the casino. Therefore, trust is no longer a dispensable emotion, but a hard input to the collaborative structure: if the system does not instantiate commitment, then the intention economy will degenerate into batch cashing out of one-time intentions, and long-term collaboration will continue to collapse under the strictest rule enforcement.

This is the meaning of Trust-Instantiation: to move trust from psychological judgment to an executable structure, making it a measurable, inheritable, and protocol-callable Reality Participation Weight. It does not label someone as "credible", but turns the ability to "continue to assume the future" into a weight and cost function within the system: whoever wants to enter higher-value, longer-term negotiations must carry a trackable commitment record, or pledge capital that can be reduced; whoever wants to realize one-time intentions will have to pay higher discounts, frictions or restrictions in the structure. In this way, trust no longer determines "whether something can be done" (authority), but determines "what is more likely to happen in the future" (path weight): the same intention, proposed by subjects with different weights, will get different realization probabilities in terms of negotiation, routing, resource allocation and execution priority. Governance, prediction, payment and collaboration in the AI ​​era are essentially competing for this point - not for who can trade, but for who can write the future into reality.

Therefore, the core functions of the financial system must also migrate: in the behavioral economy, what the market solves is Asset Allocation (allocating capital to assets to obtain returns); in the intention economy, what the market solves is Agency Realization (distributing weight to a network of subjects and agents that can continue to fulfill intentions to generate reality). When AI makes "action" redundant, what is truly scarce is "commitment"; when Agent makes "execution" cheap, what is truly valuable is "continuity." Trust-Instantiation is not a negation of Trust Minimization, but its inevitable upgrade in the AI ​​era: from hollow executable stability to solid affordable stability - only in this way can Crypto transform from a behavior coordination machine to a reality generation machine.

Let us trace the beginnings of this trend from the facts that have already occurred.

Signal No. 1: Reputation is gaining economic weight. The on-chain reputation system is affecting the weight of Agent in future collaboration. In the convergence of ZKML (zero-knowledge machine learning) and FHE (fully homomorphic encryption), we see a "cryptographic seal" taking shape - by 2026, your private data never leaves your device, even if it is being processed by the world's most powerful models. Zama’s fhEVM coprocessor, Modulus Labs’ collaboration with Tools For Humanity, are all embedding ZK proofs into the World network. This is not only privacy protection, but also the structuring of trust - when an Agent's calculation process can be proven correct without exposing sensitive weights or data, trust changes from "I believe you" to "Mathematics guarantees you."

Second signal: Payment is binding intent. Coinbase’s x402 payments standard is an underrated paradigm breakthrough. When instant stablecoin payments can be made between agents, payment is no longer just a transfer of value, but an alignment signal of intent. After integrating x402, Virtuals Protocol's transaction volume soared from less than 5,000 to more than 25,000 - not because transactions became easier, but because the "desire alignment" between Agents became executable. B2B stablecoin payments have soared from a monthly average of less than $100 million in early 2023 to more than $6 billion in mid-2025. Visa’s stablecoin settlement will reach an annualized scale of US$4.5 billion by January 2026. These are evidence that trust is being transformed from psychological judgment into economic structure.

The third signal: Forecasting is shifting from probability judgment to reality generation. Intent-Based Protocols enable probabilistic folding of future paths. The prediction market has been upgraded from "speculative casino" to "information finance" (Information Finance). CNN and CNBC have reached exclusive data agreements with Kalshi, and algorithmic trading robots use prediction market data as the main data source. When the Brier score of the prediction market approaches 0.00-0.01 in the last few days, what we see is not just an accurate probability estimate, but a process of collective intentions being materialized in monetary form.

The fourth signal: Continuous payment flows are binding long-term partnerships. Stablecoin lending has issued a cumulative $670 billion in loans over the past five years, with monthly on-chain lending volume reaching $51.7 billion. Yield stablecoins and RWAs have attracted over $20 billion in value. These are no longer instruments of speculation, but on-chain expressions of long-term economic relationships. When Ethena’s USDe—a synthetic U.S. dollar maintained through a delta hedging strategy—surges from less than $6 billion to over $14 billion at the beginning of the year, what we see is a new kind of trust structure: one that does not rely on institutional commitments but on verifiable hedging strategies.

The core philosophy of Trust Instantiation is not complicated: let trust become a calculable, executable, and accumulable system parameter, rather than an unreliable psychological premise or an unverifiable moral assumption. It neither returns to the "trust me" of the old world nor stays in the "trust no one" of the current world, but opens up a third path: Let trust become the execution weight in the system that generates the future.

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Chapter 8: The Generation of Parallel Worlds—Phase Change of Economic System

Only under the conditions of Trust Instantiation, a parallel world with multi-subject consensus can be generated. Otherwise finance simply circulates risk rather than generating reality.

When Trust was instantiated as an execution structure, multi-agent collaboration had the possibility of continuous alignment across time dimensions for the first time: The reason why the past financial system was called a "risk redistribution machine" was because its main function was to transfer uncertainty cyclically between different assets and entities, rather than folding dispersed intentions into a common path; Verification can ensure that each transaction is executed correctly, but it cannot ensure that these transactions point to the same reality in the long term. Therefore, in the absence of a cumulative commitment structure, the market is more like a secondary market for risks rather than a primary production for the future.

Once Trust-Instantiation makes the ability to "bear the future" a participatory weight within the system, the meaning of payment will also shift: from a value transfer channel to an intent-aligned interface. Today’s payment solves the problem of “how to get money from A to B faster”, but in a collaborative structure with intention as the smallest unit, payment will be more used to express “which future path I am willing to provide continuous support for”, thus allowing resources to flow to entities that are structurally responsible for the same goal. Therefore, payment no longer just completes exchange, but becomes a coordination mechanism for the alignment of multi-subject wishes.

Similarly, in prediction markets and information aggregation systems, Trust-Instantiation will change its core function: the current prediction market is mainly used to price the probability of existing events, but when participation weights and commitment records are incorporated into the collaborative structure, predictions will gradually shift from passive estimation of the future to active generation of the future. The degree of continuous commitment of different entities to a certain result will directly affect resource scheduling and execution priority, making prediction itself a part of realistic path selection. Therefore, prediction is no longer just a reflection of information, but an input variable for reality generation.

In the governance system, this migration will be more obvious: the existing on-chain governance counts preferences through voting, but cannot synchronize the continuous commitment of subjects in path selection. As a result, although decisions can be achieved, the execution often lacks long-term consistency. When trust is instantiated into participation weights, governance will transform from a one-time decision-making process to a path synchronization mechanism, allowing multiple agents to continuously adjust execution strategies around common goals. Governance therefore ceases to be simply the distribution of power and becomes the dynamic alignment of paths to reality.

In this structure, the core function of the financial system will no longer be limited to risk circulation, but will begin to assume the coordination task of reality generation, allowing the market to gradually evolve from a resource allocation field to a reality construction space for multi-subject consensus.

Let’s imagine a possible picture for 2026-2028:

Scene 1: Agent Economy is in full swing. The blockchain AI market is valued at US$562 million in 2024 and is expected to grow at a compound annual growth rate of 25.3% to US$4.278 billion in 2033. But this is only a conservative estimate. If the DeFAI sector really expands from 1 billion to 10 billion US dollars, and if the industry dominance of AI dApps continues to rise from 18.6% and surpasses games to become the first category, then we will see an economic network dominated by Agents - they not only execute transactions, but also negotiate intentions, fold the future, and allocate realistic participation weights.

Scenario 2: Stablecoins serve as global financial infrastructure. The total supply of stablecoins is expected to exceed $1 trillion by the end of 2026. Standard Chartered predicts that $1 trillion in bank deposits in emerging countries may flow into stablecoins. The signing of the GENIUS Act in July 2025 marks the United States providing a regulatory framework for stablecoins. Circle, Ripple, Paxos, Fidelity and BitGo have received provisional banking license approval from the OCC. Stablecoins are evolving from crypto-native tools to programmable global financial layers—the infrastructural premise of Trust Instantiation.

Scenario 3: The prediction market becomes a real negotiation field. The 2026 FIFA World Cup will be a catalyst for prediction markets. DraftKings, FanDuel and Robinhood are all launching regulated prediction products. Kalshi’s valuation doubled to $11 billion from $5 billion mid-year, and Polymarket reportedly raised funding at a $12 billion valuation. Prediction markets are transforming from "event betting" to the go-to "truth signal" for economists, strategists and analysts predicting global events - replacing traditional polls. This is a precursor to a future that is shifting from being traded to being negotiated.

Scenario 4: Integration of privacy computing and trust structure. ZKML proves the correctness of model execution without exposing sensitive weights or data, and FHE allows computations to be performed on encrypted data - the 2026 fusion of the two will create a "cryptographic seal" that ensures private data never leaves the device while being processed. 1X Technologies’ NEO humanoid robot is available for pre-order for $20,000, with first shipments planned for early 2026. When blockchain and robotics begin to overlap—with projects like XMAQUINA and PrismaX leveraging DePIN to fund and train machines—the application scenarios for Trust Instantiation will extend from purely financial to the physical world.

The economic system is shifting from Asset Allocation to Agency Realization. Trust Instantiation makes payment become desire alignment, prediction becomes reality generation, and governance becomes path synchronization.

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Final Chapter: The White Horse Is Not a Horse

Gongsun Long said that a white horse is not a horse. The power of this proposition lies not in denying the existence of the white horse, but in revealing the rift between "naming" and "existence." The white horse is an instantiation of horse. It is not equal to the abstract concept of "horse", but it is more real than the abstract concept - because you can ride it.

Trust Instantiation is similar. Trustlessness is the negation of the concept of "trust" - it says: We don't need horses. Trust Minimization is a compromise - it says: we need as few horses as possible. But Trust Instantiation says something else: What we need is not the abstract concept of a horse, but a concrete, rideable, verifiable white horse. Trust doesn’t need to be psychological, moral, or fragile—it can be structured, calculable, and enforceable. It doesn't need to be "believed", it just needs to be "instantiated".

Satoshi Nakamoto accomplished a great negation in 2008: eliminating dependence on trust. But denial is never the end. We will eventually need a great affirmation - not a return to old world trust, but the creation of a new, enforceable trust structure. This is the most important philosophical project in the crypto world over the next decade.

The numbers in 2026 are already telling the story: $312 billion in stablecoin market capitalization, $40 billion in prediction market trading volume, $29.5 billion in AI crypto market capitalization, $33 trillion in annual stablecoin transactions, 1,200 AI tokens, and 550 AI Agent projects. These are not just numbers – they are traces of a new world being instantiated.

Return to Baima Village. The snow is still falling, and the mountains in the distance emerge from the fog, layer by layer, starting from the outline, stacked into a brand new sketch. Each new layer of snow is not a negation of the old snow, but an inheritance and renewal of it - like a future that is continuously folded.

It's very much like how the future will be created.

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Appendix: Key data sources

DeFi TVL: DefiLlama, DappRadar, CoinDesk (2025 Q3 peak $237B; early 2026 $105-140B)

Stablecoin: DeFi Llama, Arkham Intelligence, Stablecoin Insider (market cap $312B, annual trading volume $33T)

Prediction Market: The Block, Gambling Insider, ChainCatcher (2025 trading volume $40B+, Polymarket/Kalshi duopoly)

AI Crypto: CoinGecko, FXStreet, BingX (1200+ AI tokens, market value $29.5B, 550+ Agent projects)

MEV: EigenPhi, Cointelegraph Research, Shell & Coin (Ethereum has an average of 60,000-90,000 sandwich attacks per month, Solana $370-500M withdrawal)

AI Market: Fortune Business Insights, SkyQuest (Global AI $294B/2025, Blockchain AI CAGR 25.3%)