Tokenized Assets Have Grown 224% Since 2024: Dune & RWA Report

TheCryptoTimesPubblicato 2025-09-17Pubblicato ultima volta 2025-09-17

Being one of the hottest primitive in the finance world, the real-world assets (RWA) market has grown to over $300 billion, representing a surge of nearly 224% since the beginning of 2024. It includes a wide array of financial instruments like treasuries, bonds, credit, equities, institutional funds, commodities, as well as stablecoin, which dominates the sector with a significant margin. 

The report, prepared jointly by blockchain data platform Dune and tokenized assets data aggregator RWA.xyz, reveals that tokenization is democratizing access to assets which were previously limited to institutions only. With permissionless nature and interoperability between multiple blockchains, the field is attracting a broader and more diverse investor base. 

In the current decentralized finance (DeFi) ecosystem, tokenized assets are becoming building blocks, which are largely used as collateral, yield primitives, and trading instruments. The report noted Maple Finance’s syrupUSDC Centrifuge’s deRWA wrapper, and Aave’s Horizon RWA Market, as prime examples for this, which eventually enhance composability and liquidity. 

Leading instruments in tokenized markets

Dune also notes that tokenized U.S. Treasuries have achieved significant scale in the past few years and it is a proven product-market fit (PMF) with over $7.37 billion, as per market data

Unlike the traditional way of accessing these treasuries, its tokenized version offers enhanced access alongside institutional credibility, secure yield, 24/7 liquidity, and collateral utility. Such features make them a compelling alternative to stablecoins and a cornerstone of on-chain capital markets.

Beyond US treasuries, investors are also moving to higher-yielding assets like long-term bonds, private credit, and equities, reflecting growing demand for risk-adjusted assets. 

Stablecoins dominating the RWA sector

Stablecoins, especially those backed by USD reserves, currently dominate the tokenization landscape, accounting for nearly $280 billion. Stablecoins were the first assets to be tokenized on blockchains and they have become a key foundation for on-chain capital markets. 

“The lines between stablecoins and other tokenized assets are blurring: more yield-bearing stablecoins are launching, and issuers are integrating RWAs into their reserves,” the report notes. 

Apart from stablecoins, which have roughly 94% of the total assets on-chain as per RWA.xyz data, private credits, commodities, and institutional funds, are topping the total value locked (TVL), having reached $15.9 billion, $2.4 billion, and $1.7 billion in total assets, respectively. While gold is currently dominating tokenized commodities, the share for agricultural products and energy assets are emerging. 

Top beneficiaries in assets tokenization wave

Among all blockchain networks, Ethereum has remained a top choice for institutions to convert real-world assets into tokens. It currently has a market share of over 56% in total stablecoins supply and a 30.9% in total tokenized assets. Besides, Polygon—which has 62% of global bonds—Arbitrum, Solana, Plum is also leading the charge. 

Ondo Protocol, one of the most popular RWA platforms, also played a key role in the expansion of tokenized assets markets. It generated over $141 million in mint/redeem volume during the first week of launch. Ostium, a leveraged tokenized assets trading platform, also gained significant momentum with it generating over $17 billion in cumulative volume. 

Also Read: Coinbase Hack Suspect Stored 10,000+ Customer Records on Phone


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Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

Jensen Huang, alongside AI leaders like Peter Norvig, Boris Cherny, and Andrew Ng, is advocating for a shift from "prompt engineering" to "loop engineering" as the new paradigm for AI development. Instead of manually crafting individual prompts, the focus is now on designing autonomous loops—systems where AI agents execute tasks, self-validate results, and iterate until completion without constant human oversight. A loop is a management framework that enables agents to operate independently. Key implementations are seen in Claude Code (with features like /loop, /goal, and /schedule) and OpenAI Codex, which employ multiple agents working in parallel within isolated environments. A core principle is the separation of roles: one agent (or model) performs the task, while an independent agent (or a smaller, separate model) validates the output to ensure objectivity. The article outlines a practical roadmap for implementing loops, starting with a "four-condition test" to assess suitability, building a minimal viable loop, and emphasizing critical pitfalls to avoid, such as lacking hard stop conditions or allowing loops to handle tasks requiring human judgment. This evolution is framed as the fourth major shift in AI interaction: from Prompt Engineering (crafting instructions) to Context Engineering (providing background information), then to Harness Engineering (building tool-enabled environments), and finally to Loop Engineering (creating self-sustaining systems). This progression reflects a consistent trend of increasing abstraction, moving human involvement from direct instruction to system design and rule-setting. The concept has academic roots in frameworks like ReAct, which formalized the "reason-act-observe" cycle. While loop engineering promises greater automation, experts caution about managing token costs and warn against outsourcing understanding—AI can assist, but deep problem comprehension remains essential.

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Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

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