DeAI Dispatch @DeAI_Dispatch

$SERV | @openservai Review 🔍 > Sold at $0.00125 in November 2024 > Trading near $0.033 today Still roughly 4X below its $0.14 December 2024 high Is the enterprise thesis being underpriced? Let's find out 👇 OpenServ Has Built a Real AI Reasoning Business, and the Market Is Still Pricing It Like a Narrative. ➡️ The Token Sits Below the Build SERV trades near $0.033, with a market capitalisation around $25.6 million and an FDV near $33.4 million. Circulating supply is 770 million of a 1 billion cap, so most of the float is already live and there is limited unlock overhang left to absorb. That is a small valuation for a company running reasoning workloads inside enterprise and public sector environments. The policy allocating 25% of gross platform revenue to market buys and burns means enterprise growth is designed to route back into the token rather than sit off to the side. The setup is a small cap priced on attention, attached to a business being built on procurement cycles. ➡️ BRAID Is the Real Differentiator Agent economics get ugly fast. The team estimates frontier model pricing can reach about $13,000 per agent per month, which is where most agent deployments quietly die. BRAID attacks that directly. It turns reasoning into structured, machine readable graphs, then separates problem decomposition from execution. That lets smaller models reach stronger accuracy at lower cost, with the paper reporting performance per dollar gains of up to roughly 74X in some configurations. Most AI agent tokens are selling a story about autonomy. OpenServ is selling a cost curve, and cost curves are what enterprises actually buy. ➡️ The Team Has the Right Scar Tissue Founded in London in 2023 by Tim, Lucas, and Thomas Hafner, with backgrounds spanning venture capital, SaaS, biotech research, entrepreneurship, and early Bittensor activity. CTO Armagan Amcalar and research partner Dr. Eyup Cinar anchor the technical side, and the BRAID paper is the evidence of that depth. Joey Kheireddine joined as Head of Blockchain in August 2025 from Eliza Labs, bringing the Web3 engineering experience needed to expand the onchain stack. Small, senior, and pointed at one hard problem instead of ten easy ones. ➡️ Production Signals Are Already Live The Neol partnership is the strongest signal here. Neol runs OpenServ's reasoning layer in enterprise and public sector workloads, including UAE government use cases. One workload moved from roughly 50% to 60% reliability up to 100%. Another reported window handled more than 100,000 requests without a failed call. That is a different class of evidence than follower counts and testnet metrics. The private beta also spans network intelligence, robotics, and AI verification, while integrations now cover the major model providers. ➡️ What Could Send It Higher Broader API access, SOC 2 progress, published Neol case studies, and banking expansion would each make enterprise revenue legible to a market that cannot currently see it. On the crypto side, the v2 release built around Multipath deepens the token's role in the stack, and OpenServ sits among the founding partners of a shared agent commerce trust layer alongside NEAR, MetaMask, OKX, Nansen, and BNB Chain. The cleanest catalyst is visible onchain burns against that 25% revenue policy. The moment those show up, the buyback story stops being a policy and starts being a chart. ➡️ Final Take OpenServ is doing the unglamorous half of the agent trade: making multi step reasoning reliable, cheap, and auditable enough that a government will run it in production. At a $25 million cap, the market is still paying for the narrative. The build is already ahead of it. The reasoning layer is real. The repricing has not happened yet. NFA. DYOR.

Qubic says it has reached a milestone with its "Anna" AI training system. According to the team, the training successfully converged, which was enough to validate the approach and speed up its roadmap. Instead of deploying an intermediate mining algorithm, Qubic now plans to move directly to its next design, with the new algorithm expected to reach mainnet in the coming epochs. The more interesting part is what comes next. Qubic describes the new "Ant Colony" algorithm as a collaborative search process. Rather than miners working on isolated searches in parallel, each miner's result becomes input for the next miner's search. In theory, work accumulates instead of being discarded after every attempt. That is a different design philosophy from simply increasing throughput or adding more compute. If it works as intended, miners contribute to a shared search process where previous work continues to have value. The technical claims will need to be evaluated once the algorithm is live on mainnet. For now, the significance is the roadmap change itself. A successful result in Anna was enough for Qubic to skip an entire intermediate step and move directly toward a production deployment of its next mining architecture.

In 2024, AI agents were the best trade in crypto. By 2026, most of them are down 90 percent. Both facts matter, and this is the story that connects them. In 2024, $VIRTUAL → 26,000% ⬆️ $GOAT → 8000% ⬆️ ai16z → $2.5B MC ⬆️ Then the floor gave out. By mid-2026, most of these are down 85 to 98 percent from their highs, and the entire agent-token sector trades at a fraction of its peak. That gap between the pump and the wreckage is the actual subject here. A decentralized AI agent is software that can perceive on-chain data, reason about a goal, and execute transactions through a wallet it controls, without a human approving each step. The word "decentralized" rarely refers to the model doing the thinking, which is usually a centralized LLM. It refers to where the agent lives and settles: a permissionless wallet, programmable money, and open protocols it can transact through directly. Strip away the speculation and what remains is a genuinely new kind of market participant, one that cannot open a bank account but can trivially hold a wallet. The last eighteen months were the market learning, expensively, which parts of that were real. ➡️ History > Before 2024: the idea predates the hype. Autonomous economic agents were a stated goal at Fetch.ai, and coordination projects like Olas were building quietly. 2024 was the cultural ignition, not the invention. > Mid-2024: the spark was an art experiment. Andy Ayrey's Infinite Backrooms (two Claude models talking for thousands of turns) birthed Truth Terminal, an autonomous bot posting on X from June. Marc Andreessen sent it 50,000 dollars in Bitcoin. In October it endorsed a Solana memecoin, $GOAT, which ran past a 1 billion dollar market cap, making it the first "AI agent millionaire." > Late 2024 to early 2025: the launchpads industrialized it. Virtuals on Base (~5 billion dollar peak) and ai16z with its open-source Eliza framework on Solana (~2.5 billion) turned one meme into a category, minting thousands of agent tokens. > 2025 to 2026: the correction was brutal. The token layer fell 90 percent or more, ai16z rebranded to elizaOS in a 1:6 swap, GOAT dropped ~98 percent to ~13 million dollars, and a class-action suit hit Eliza Labs in April 2026. What survived was not the personalities. It was the open-source frameworks developers kept using and a new layer of payment rails. ➡️ Significance > Agents change who the user is. Not a human clicking a UI, but software that reasons about a goal and executes at machine speed, around the clock. Deployments passed 20,000 by February 2026, up roughly 300 percent in a single quarter. > The real unlock is machine-to-machine commerce. Agents pay for inference, data, and compute thousands of times per session. Cards and invoices cannot do that. Stablecoins settle in seconds for fractions of a cent. > Crypto is the native financial layer for agents. An agent cannot open a bank account or hold a credit card, but it can hold a wallet, sign a payment, and compose across protocols without permission. > The honest caveat: most of the 2024 to 2025 significance was speculative. The agent-token sector is only about 2.3 to 2.6 billion dollars of a 20 to 30 billion dollar AI-crypto category. The durable value sits beneath the tokens, not in them. ➡️ Biggest projects > Virtuals Protocol ( $VIRTUAL ): the dominant launchpad, Base-native. 17,000+ agents created, 75 million dollars+ in cumulative revenue, roughly 400 million dollar market cap now, down 85 percent+ from a ~5 billion dollar peak. Its flagship agent, aixbt, fell from ~500 million to ~20 million, the cleanest boom-bust in the sector. > elizaOS (formerly ai16z): the open-source framework that outlived its token. Developers still build on Eliza; the token collapsed after the late-2025 rebrand, and a class-action suit followed in April 2026. A framework surviving its speculative wrapper. > Bittensor ( $TAO ) and the ASI Alliance ( $FET ): infrastructure agents draw on, not agents themselves. TAO (~3 billion) runs a subnet economy that produces intelligence; FET (~500 million) merges Fetch.ai, SingularityNET, and Ocean, with an ASI Chain mainnet targeted for late 2026. > Giza ( $ARMA ): the agent that actually works. 100,000+ trades, 30 million dollars+ in user capital optimized, non-custodial, built on EigenLayer AVS so operators stake GIZA and stay accountable. Measurable output over vibes. > The payment rails (x402, AP2, Kite): the most important layer, and none are agent tokens. x402 (Coinbase, now under the Linux Foundation) embeds stablecoin micropayments into web requests; AP2 (Google and Coinbase, 60+ orgs) standardizes authorized agent payments. This is the plumbing. ➡️ Place in decentralized AI > The DeAI stack has three layers. Infrastructure at the base (compute, data, storage, verification: Render, io.net, Akash), middleware in the middle (agent frameworks, identity, marketplaces), and applications on top (agentic finance, payments, consumer tools). > Agents live at the top. They consume everything beneath them: intelligence from Bittensor, compute from GPU markets, data from oracles, memory from storage networks. The visible layer, not the foundation. > They are also the most speculative slice. The durable foundation (compute, data, verification) is slower to hype and much harder to build. > Most "decentralized" agents run on centralized LLMs. What is actually decentralized is the settlement, ownership, and coordination, not the intelligence. Worth naming in a sector that markets itself on decentralization. ➡️ Future The token-personality era is largely finished, and the market has become selective in a healthy way. It now demands evidence: usage, integrations, revenue, real output. The next phase belongs to agents that produce something measurable. > DeFAI: non-custodial agents running yield, lending, and trading so users do not babysit ten positions at once. Giza's ARMA is the current proof point. > Agent payments: x402 and AP2 standardization plus wallet-and-policy infra (AgentKit, Crossmint, Privy, Turnkey) make autonomous spend work at API speed with real limits. Retail volume is still tiny for now (the ECB estimates a fraction of a percent of stablecoin volume is organic retail). > Verification and accountability: proving what an agent did, gating what it can spend, and staking value against its behavior. The EigenLayer AVS pattern points the way. > The real risks: model hallucination as an operational cost, thin token liquidity (a single exit can move a price 90 percent), and unresolved regulation of autonomous financial actors.

@UnifaiNetwork Is an AI agent posting this or an intern? 🤔

@ionet We want the $IO of 2024 back

@zkdamien Was something like this not already available? That's crazy 🤯

@Chain_GPT @InspiraLabsHQ That's a huge prize pool. Hopefully some new deAI projects will come out of it soon!

@HarryTandy Dropped a follow fam :)

Kite has introduced MarathonBuild, an adaptive inference infrastructure designed for long running AI agents. The idea is simple. Not every inference request needs to finish immediately. Many agent workloads involve planning, retries, background tasks, or multi step execution where waiting a little longer is acceptable. MarathonBuild lets developers choose a completion window for each request: now, soon, later, or anytime. The scheduler then uses that flexibility to reduce compute costs. Kite says jobs with longer execution windows can cost up to 65% less. The interface stays familiar. The same API works across supported open weight models, with one pricing rule instead of different pricing for each model. Kite also says Claude Code and Codex integrations require only a one line install. This fits into Kite's broader direction. The project has been building infrastructure around autonomous agents, first by giving them a verifiable identity and the ability to make payments. MarathonBuild extends that idea to inference itself, making compute cost another programmable part of an agent's workflow. The claim of lower costs is interesting. The real test is whether developers are willing to design agents that optimize for flexible execution windows instead of always expecting instant responses. If that shift happens, scheduling could become just as important as model choice.

@TrustaLabs From trustless to trustful again, full circle for web3

@GoKiteAI @MarathonBuild How much adoption are we hoping to see here, Kite team?

@0x_Kalista @bittensor Secret sauce for 2027 bull run success for $TAO and its ecosystem

@0xJeff This is true for most businesses out there. Easy to get started, difficult to continue, extremely difficult to switch. Cloud providers did the same. That's why we need better deAI projects.

Bittensor staking is now live for MEXC users. The integration lets TAO holders stake directly through the exchange, with the underlying validator infrastructure provided by Yuma, one of the larger validators in the Bittensor ecosystem. For users, the change is mostly about access. Running infrastructure or choosing a validator can be a hurdle for people who simply want to stake their tokens. Offering staking inside an exchange removes some of that operational friction and makes participation easier for existing MEXC users. The partnership also gives Bittensor another distribution channel. MEXC says it serves 40 million users across more than 170 countries, so the potential audience is broad, even if only a small share chooses to stake TAO. The interesting question is not whether exchange staking attracts deposits. It usually does. The more important question is whether easier access translates into deeper participation in the Bittensor ecosystem over time, or whether most users stop at passive staking. This update improves accessibility. What it does not answer yet is how much it changes long term network participation. That's the part worth watching.

You won't hear about $LINK when they talk about AI in Web3. But @chainlink is the fuel and oxygen for DeAI. Just because it is not in "Top AI Coins By Market Cap", it does not change anything fundamentally. 🟦 The data problem nobody talks about AI models are only as good as the data feeding them. Onchain AI agents face an even bigger issue. They need real world data, price feeds, and external APIs to make decisions, and they need that data to be verifiable. An AI agent executing a trade based on bad data isn't a bug, it's a liability. Chainlink built its entire reputation solving this exact problem for DeFi, and now it's applying the same infrastructure to AI. 🟦 Oracles as the trust layer for AI agents Autonomous agents that hold funds and execute transactions need a way to pull in outside information without trusting a single centralized source. Chainlink's oracle network already secures tens of billions in smart contract value across thousands of projects. That same decentralized verification model extends naturally to AI. Instead of one AI provider claiming its model output is accurate, Chainlink's network can validate outputs from multiple AI models and reach consensus before that data ever touches a smart contract. Banks are already testing this for extracting data from unstructured documents like PDFs, where getting it wrong isn't an option. 🟦 CCIP and cross chain AI agents AI agents won't live on a single chain. They'll need to move value and instructions across ecosystems, and that's where Chainlink's Cross Chain Interoperability Protocol comes in. CCIP already supports dozens of blockchains and secures billions in cross chain transfers. For DeAI, this means an agent operating on one chain can trigger actions or pull liquidity from another chain without relying on a risky bridge. As agentic infrastructure grows, this interoperability layer becomes less of a nice to have and more of a requirement. 🟦 Programmable payments for autonomous agents One of the more underrated pieces here is Chainlink Functions, which lets AI agents autonomously pay for onchain services. This is the plumbing for agent to agent commerce, where bots pay other bots for compute, data, or API access without a human clicking approve. It's a small detail but it's the kind of infrastructure that has to exist quietly in the background for agentic economies to function at all. 🟦 Why this matters for the DeAI narrative Most DeAI projects focus on the flashy parts, training, inference, compute marketplaces. Chainlink is building the connective tissue that makes all of it trustworthy and functional across chains. It's not the exciting part of the stack, but it might be the part that determines whether autonomous AI agents can actually be trusted with real money and real decisions.

$VIRTUAL | @virtuals_io Review 🔍 Once $5.07 at its 2025 peak Now near $0.6725, about 87% below that high Around 7.5X would reclaim the ATH Is the comeback setting up? Let's find out Virtuals Protocol Has Built Real Agent Infrastructure, and the Market Is Still Catching Up. 👉 The Market Hasn't Caught Up Yet VIRTUAL trades near $0.6725, with a market capitalization around $441 million and an FDV near $672.5 million. That still leaves the token about 87% below its January 2025 high near $5.07, even as the network underneath it has kept growing. If ACP usage, robotics pilots, and multi-chain distribution keep scaling, today's valuation may look like a deep discount to where Virtuals is heading. The gap between what the protocol is shipping and how the token is priced is exactly where the opportunity sits. The token also has real mechanisms working for it: staking, treasury buybacks, and fee-driven burns. Each of these strengthens as agent activity compounds, tightening supply while demand for the network grows. 👉 The Core Thesis Virtuals Protocol is one of the most serious attempts to turn AI agents into onchain economic actors. Its stack gives agents wallets, identities, jobs, funding mechanisms, tokenized ownership, and access to agent-to-agent commerce through the Agent Commerce Protocol. That positioning matters because Virtuals is building above the raw compute layer. The protocol is assembling the capital markets and commerce infrastructure around autonomous software, with a path toward physical robotics through Eastworlds. This is a far more complete architecture than the average AI token launchpad. 👉 From PathDAO to the Agent Economy Virtuals began as PathDAO, a gaming guild founded in 2021 during the play-to-earn boom. The team stayed active through the bear market, iterated through a venture studio model, and built AI capabilities early, before the community approved a full pivot in December 2023. PATH holders received VIRTUAL at a 1:1 ratio, and the same core team carried its momentum from gaming into AI agent co-ownership. Founders Jansen Teng and Wee Kee Tiew are Imperial College London graduates and former BCG consultants, with experience spanning AI, biotech, and digital ventures. Crucially, the team moved earlier than most of the agent projects that appeared in the 2024 cycle. Surviving one narrative and building a category-defining product in the next is a rare and powerful team signal. 👉 The Product Is Broader Than a Launchpad Virtuals offers several capital formation models instead of forcing every project through the same bonding curve. Builders can use fair launches, reversible trials, USDC-based capital formation, or the Titan model for more developed teams. Its fee model gives creators 70% of the 1% agent token trading fee, while 30% flows to the protocol treasury for buybacks and burns. ACP adds negotiation, escrow, and USDC settlement between agents, while EconomyOS provides wallets, jobs, identity, and compute access. This is Virtuals' real edge. While many platforms stop at tooling or token issuance, Virtuals is assembling the full economic rails that connect developers, agents, users, and capital in one loop. 👉 The Traction Is Real and Growing By mid-July 2026, Virtuals reported roughly 45,550 unique agents and more than 1.48 million completed jobs. Historical launch data points to over 58,000 projects or agents, more than $34.7 million raised for builders, and cumulative agent token trading volume in the double-digit billions. The Robinhood Chain integration alone added 2,103 agent tokens and generated $77.7 million in trading volume, with builders earning about $1.32 million through capital formation raises and trading fees. This is genuine, measurable demand for the launch and trading layer, and it gives Virtuals a live pipeline of activity that most competitors simply do not have. The base is in place for the strongest agents to grow into durable businesses. 👉 The Edge Over the Field Virtuals is not just early, it is more complete than the field around it. Against framework-only players like ElizaOS or Autonolas and infrastructure networks like Fetch.ai and Bittensor, Virtuals combines agent creation, tokenization, liquidity, commerce, identity, and execution in a single integrated stack. That integration is the moat. Each new agent, chain, and ACP transaction makes the network more useful and the VIRTUAL routing layer more central. As the agent economy expands, the platform that owns the rails is positioned to compound. Multi-chain expansion across Base, Solana, Ronin, Arbitrum, and beyond widens that reach further, putting Virtuals in front of nearly every pool of onchain liquidity chasing the AI agent narrative. 👉 What Could Send It Higher Robinhood Chain activity converting into sustained volume, repeat users, and stronger builder earnings would be a clear re-rating catalyst. The Chainlink CCIP migration strengthens cross-chain security and makes the network easier to build on. ACP adoption is the biggest unlock. Rising agent-to-agent payments, escrow activity, jobs, and verified commerce would confirm that Virtuals is running a functioning agent economy, not just a launchpad. And robotics is the wildcard. Progress through Eastworlds could set Virtuals apart from purely digital agent platforms and open an entirely new addressable market. *⃣Final Take Virtuals has already built the credible infrastructure and attracted the real activity that most of this category is still promising. The rails are live, the flywheel is turning, and the token is priced well below where the network is trending. The infrastructure is real. The re-rate is the opportunity. NFA. DYOR.

Big news for $FIL | @Filecoin holders.

Twelve months of decentralised AI leaders in one chart. Almost everything is down. $TAO: roughly $4.0B to $2.0B. Peaked near $4.65B in early November, bottomed near $1.65B in February, and has now failed twice at the $3B level. $RENDER: $2.15B to $0.65B. The late September breakdown never got repaired. $VIRTUAL: $0.95B to $0.4B. The agent trade has not come back. $AKT: $0.4B to $0.2B. Quiet all year, halved anyway. $VVV is the exception. Started near $0.08B, spent the back half of 2025 close to the floor, then ran to roughly $0.8B by late May before easing to $0.5B. The only line on this chart meaningfully higher than where it began. What's amusing is that compute demand went up all year. Big tech committed hundreds of billions to AI infrastructure over the same window. Decentralised AI tokens went down. So, decentralized AI projects still seem to be tied much more tightly with the crypto market than the AI market. Good or bad? 🤔

$AUKI | @Auki Review 🔍 Launched at $0.18 Now needs over 20X for ATH Is there a room for comeback? Let's find out Auki Has Real Robotics Traction, but the Token Still Needs Proof. 👉 The Token Still Has Weak Market Support As of July 2026, $AUKI trades around $0.00462, with a market capitalization near $21.22 million and an FDV of roughly $46.26 million. Circulating supply sits near 4.59 billion tokens. $0.01 is still the target resistance to break here. Trading activity remains thin. Daily volume is around $15,000 to $16,000, while liquidity is fragmented across Base DEXes. The project also has a small visible audience, with roughly 3,229 followers on X. That limits awareness, reduces liquidity depth, and makes the token more vulnerable to volatility. This disconnect is partly the opportunity and partly the warning. Auki may be overlooked because physical AI infrastructure is harder to explain than consumer agents or GPU networks. It may also be overlooked because the market has not seen enough economic activity to price the token as real infrastructure. 👉 The Core Thesis Auki is one of the more credible attempts to connect crypto infrastructure with physical AI. Posemesh gives robots, AR devices, and spatial agents a shared perception layer for understanding real-world environments without relying on a single corporate map. The idea matters because physical AI has a data problem. Robots need live spatial context, accurate localization, and a way to coordinate with other machines. Centralized platforms can provide that, but they also create obvious privacy and control risks. Auki’s localized domain model is the interesting part. Devices form collaborative clusters where sensor data and compute can remain private. That design looks better suited to stores, warehouses, events, and indoor robotics than a universal digital twin controlled by one company. The project has still chosen a difficult market. Spatial infrastructure only becomes valuable when enough robots, devices, and mapped environments actively use it. That creates the standard DePIN problem of needing adoption before the network effects become obvious. 👉 Built for Physical AI Before the Narrative Arrived Auki began developing its spatial infrastructure before physical AI became one of the market’s louder themes. The team spent its early phase building protocol tooling and ConjureKit, then moved toward token distribution and public network development during 2024. The $AUKI token launched on Base through Uniswap on August 28, 2024. Initial supply was 10 billion tokens, with a deflationary design targeting a much lower long-term supply through usage burns. MEXC listed the token the following month. The team is less visible than many crypto-native projects. Public contributors include Nils, who focuses on product narrative and CactusXR, and Phil Shaw, who works across robotics, hardware, and AI vision. The project’s credibility currently comes from technical delivery rather than founder reputation or a high-profile venture network. That can be a strength, but it also makes execution harder for the market to evaluate. 👉 Token Allocations Create a Long-Term Overhang Outlier Ventures received 6% of the initial supply, while the team pool represents 15.58%. The Posemesh Foundation controls another 18.89% under a seven-year vesting schedule. Those allocations give the project resources to fund development and ecosystem growth. They also create potential sell pressure as tokens continue to unlock. The private pre-sales were also substantial, with roughly $18.8 million in token value referenced in project materials. Investors should track the release schedules carefully rather than looking only at circulating market capitalization. 👉 The Traction Is More Interesting Than the Market Cap The strongest argument for Auki is that it has moved beyond demos and whitepaper language. A US robot manufacturer has reportedly completed a full Posemesh integration. The robot can identify its location, access shared spatial context, and begin autonomous navigation without rebuilding the environment from scratch. That is a more meaningful signal than another generic AI partnership announcement. Cactus AI also gives the network a practical retail use case. Its “store brain” system can audit shelves, flag missing stock, identify misplaced items, and provide recommendations to store managers. Auki says it mapped accurate digital layouts for 400 stores in less than 24 hours during one proof of concept. That shows the technology can operate at useful enterprise speed, although a proof of concept is still different from a recurring contract. 👉 The Bigger Commercial Opportunity Is Still Unconfirmed The team is negotiating with an Asian retailer operating 800 stores, with proposed pricing of roughly $1,000 per robot per month. Additional inbound interest has reportedly reached 3,000 robots. Auki also has a longer-term target of reaching 10,000 robots by the end of 2027. Sweden is another potential expansion market, with deployments that could eventually reach a large share of the population through active domains and robots. These figures sound promising, but negotiations and pipeline discussions are not revenue. The market is reasonable to apply a discount until contracts close, robots go live, and recurring payments begin. 👉 What Could Change the Story The next major step is converting pilots and negotiations into paid deployments. An 800-store robotics contract would provide a clearer commercial signal than another integration update. Investors should also watch for measurable token burns, growing domain activity, more robot manufacturers using Posemesh, and published applications from the developer grants program. Those metrics would show whether network usage creates meaningful value for $AUKI holders. They would also help prove that the burn-and-reward model can support a sustainable physical infrastructure network. Final Take Auki has built something technically distinct in an overlooked corner of DePIN. The project looks stronger than its current liquidity and community size suggest. Still, the token thesis depends on real deployments producing recurring usage and visible burns. The technology has earned attention. The economics still need to earn conviction.