Stablecoin monthly transfer volume fell by nearly 20% over the past 30 days, even as the market’s total supply and holder count continued to rise. 

According to data from RWA.xyz, 30-day stablecoin transfer volume dropped 19.18% to $8.31 trillion as of April 28, while stablecoin market capitalization rose 2.06% to $305.29 billion over the same period. The number of stablecoin holders also increased by 2.32% to 246.94 million, while monthly active addresses edged up 0.26% to 51.28 million.

The divergence suggests that stablecoin growth is not translating evenly into onchain activity. While more capital appears to be sitting in dollar-denominated crypto assets, fewer dollars are being moved across blockchains compared with 30 days earlier. 

The 30-day net flows were led by Tether’s USDT, which added $3.6 billion, followed by Circle’s USDC with $2 billion and MakerDAO’s DAI with $1.2 billion. Ethena’s USDe saw the largest net outflow at $1.1 billion, while Paxos’ PYUSD recorded $509 million in net outflows. 

30-day stablecoin net flows as of April 28, 2026. Source: RWA.xyz

Stablecoin momentum cools after stronger network activity

The decline in broader stablecoin transfer volume comes after stronger stablecoin activity was flagged on some of the major blockchain networks for stablecoins. 

In its Q2 Signals Report, asset manager Fidelity cited Coin Metrics data showing that Ethereum’s stablecoin transfer values had recently exceeded historical averages, with transfer value over the past 12 months surpassing $18 trillion.

Aggregate stablecoin transfer volume. Source: Fidelity

Fidelity said the trend suggested network utility persisted even as crypto prices remained under pressure. The company said the increase may signal that stablecoins are being used for payments, settlement and onchain access to the dollar, regardless of broader market sentiment. 

Related: Stablecoin inflows rebound to $1.7B as Washington battles over yield rules

Solana showed a similar, though smaller, trend. Citing Coin Metrics data, Fidelity showed that Solana consistently processed over $5 billion in stablecoin volume, while its 30-day average transfer volume increased from $6.7 billion to $7.2 billion as of March 31. 

Fidelity said the data suggest that Solana may be moving toward more mainstream financial activity after being closely associated with memecoin trading. 

Magazine: AI-driven hacks could kill DeFi — unless projects act now

Cointelegraph is committed to independent, transparent journalism. This news article is produced in accordance with Cointelegraph’s Editorial Policy and aims to provide accurate and timely information. Readers are encouraged to verify information independently.

Key Highlights

• AI chip design momentum propels Cadence Q1 revenue and backlog expansion

• CDNS shares dip in pre-market trading despite solid Q1 performance

• Company elevates full-year 2026 projections following robust first quarter

• Backlog reaches $8 billion milestone as AI design tools gain traction

• New AI-powered design platforms contribute to margin expansion and earnings growth

Cadence Design Systems (CDNS) delivered impressive first-quarter financial results powered by surging demand for artificial intelligence chip design solutions. The company’s backlog expanded significantly while management upgraded forward guidance. CDNS shares finished the regular trading session at $336.54, gaining 1.10%, though pre-market activity saw the stock retreat to $334.63, declining 0.61%. Results demonstrated momentum across multiple business segments including software platforms, hardware systems, intellectual property, and system design solutions.

Cadence Design Systems, Inc., CDNS

Strong Revenue Performance Driven by AI Design Tools

Cadence announced first-quarter 2026 revenue totaling $1.474 billion, representing significant growth from the $1.242 billion recorded during the comparable period last year. This advancement stemmed from heightened customer demand for electronic design automation platforms serving chip development and system design sectors. Despite solid quarterly performance, early trading activity following the announcement displayed modest downward pressure.

The company’s GAAP operating margin came in at 29.3%, marginally exceeding the 29.1% achieved in the first quarter of 2025. Meanwhile, non-GAAP operating margin expanded to 44.7%, up from 41.7% year-over-year. This margin improvement demonstrated enhanced operational efficiency and favorable product mix dynamics.

On the earnings front, GAAP diluted earnings per share climbed to $1.23 versus $1.00 in the prior-year quarter. Non-GAAP diluted earnings per share advanced to $1.96 from $1.57. Therefore, Cadence posted simultaneous expansion in both top-line revenue and bottom-line profitability.

Substantial Backlog Reinforces Full-Year Projections

Cadence concluded the quarter with total backlog reaching $8.0 billion. Additionally, the company anticipates generating $4.0 billion in revenue from remaining performance obligations within the coming 12 months. This substantial backlog position provides enhanced revenue visibility and demand predictability.

Leadership elevated the company’s 2026 revenue guidance to reflect 17% year-over-year expansion at the midpoint. Cadence currently projects full-year revenue falling between $6.125 billion and $6.225 billion. The firm anticipates non-GAAP operating margin landing in the 43.5% to 44.5% range.

Additionally, Cadence forecasts GAAP diluted earnings per share between $4.39 and $4.49 for the full year. Non-GAAP diluted earnings per share guidance spans $7.85 to $7.95. As a result, Cadence approaches the remainder of 2026 with strengthened earnings confidence.

New AI Platform Introductions Accelerate Growth Trajectory

Cadence unveiled AgentStack throughout the quarter as a cornerstone element of its artificial intelligence design ecosystem. This framework facilitates knowledge integration across chip design, 3D integrated circuit development, and system-level design processes. Furthermore, it unifies Cadence’s comprehensive design tool portfolio into a cohesive operational architecture.

The organization also released ViraStack targeting analog and custom design applications. Additionally, InnoStack was introduced for digital implementation and design signoff workflows. Combined with the existing ChipStack platform, Cadence now addresses an expanded spectrum of chip development stages.

Core electronic design automation revenue advanced 18% year-over-year reflecting robust customer engagement. Hardware revenue achieved a quarterly record, propelled by artificial intelligence and high-performance computing applications. Intellectual property revenue surged 22%, while system design and analysis revenue posted 18% growth.

 

Core Scientific is driving a transformative shift in its business model, planning to convert its Pecos, Texas campus into a high-density AI-focused data center complex that could reach up to 1.5 gigawatts of gross power capacity. The company said that roughly 1 GW of that capacity would be available for leasing, signaling a move beyond traditional cryptocurrency mining toward AI compute infrastructure amid growing demand for data center capacity.

In a press release issued on Monday, Core Scientific outlined the transition as part of its strategy to differentiate its buildout of next-generation AI infrastructure using its in-house engineering capabilities. The project’s initial data hall has completed foundational work and is moving into vertical construction, with the company targeting first capacity in early 2027. Core Scientific noted that about 300 megawatts of power at the Pecos site, previously allocated to Bitcoin mining, are being repurposed for the new data center operations.

The expansion is supported by new power agreements, including an additional 300 megawatts secured under contract with the local utility provider, and land acquisitions to support scale. Core Scientific said it has acquired more than 200 acres in the Pecos area to accommodate the buildout.

The company also disclosed a broad financing plan to fund the expansion, revealing plans to raise approximately $3.3 billion through senior secured notes due 2031, intended to finance data center development across multiple states including Georgia, Texas, North Carolina and Oklahoma. This follows a separate $1 billion senior credit facility secured from Morgan Stanley in March, underscoring the capital-intensive path of building out AI-ready infrastructure at scale.

Core Scientific has historically derived a substantial portion of its revenue from mining digital assets, but it has gradually shifted toward offering infrastructure services. The Pecos project illustrates how miners are repurposing existing facilities to capitalize on the sustained demand for AI compute capabilities, even as the economics of mining face ongoing pressures.

Core Scientific shares have risen about 44% so far this year. Source: Yahoo Finance

Key takeaways

• Core Scientific aims to build a Pecos, Texas, data center campus with up to 1.5 GW gross capacity, roughly 1 GW of which could be leased to customers for AI workloads.
• About 300 MW of power previously used for Bitcoin mining at Pecos is being repurposed for data center operations, with the first data hall expected to deliver initial capacity in early 2027.
• The company has acquired over 200 acres in Pecos to support the build, and it has secured additional power contracts totaling about 600 MW when combined with existing arrangements.
• Financing support includes a $3.3 billion plan via senior secured notes due 2031, complemented by a $1 billion Morgan Stanley credit facility, signaling a broad push into AI-ready infrastructure across several states.

Core Scientific’s Pecos expansion: from mining to AI data centers

The Pecos plan represents a deliberate pivot from pure mining activity toward high-density AI compute, leveraging Core Scientific’s engineering expertise to design scalable, data-center-centric infrastructure. The company emphasized that the first data hall has progressed to vertical construction, with a timeline that anticipates initial capacity becoming operational in early 2027. The repurposing of roughly 300 MW of the site’s existing power load highlights a broader industry trend: crypto facilities are increasingly being repurposed to support AI workloads as demand for compute power grows beyond blockchain validation.

Adam Sullivan, Chief Executive Officer of Core Scientific, underscored the strategic rationale, stating, “We continue to leverage our deep in-house expertise to differentiate how we build and scale next generation artificial intelligence infrastructure.” This sentiment reflects a broader industry push to convert crypto-era assets into flexible, AI-forward data centers capable of housing GPU-intensive workloads, training models, and running inference at scale.

The Pecos project also includes a furniture of land assets—Core Scientific has acquired more than 200 acres—to anchor long-term expansion, aligning with plans to deploy a significant amount of capacity in a single campus. The plan to carve out roughly 1 GW for leasing aligns with a perceived demand gap in premium AI compute space, particularly for operators seeking co-location and predictable power contracts.

Funding the buildout: debt, power, and land

Financing a multi-hundred-megawatt, multi-state data center push requires patient capital. Core Scientific’s plan to raise about $3.3 billion through senior secured notes due 2031 signals a move from opportunistic opportunism to a structured capital strategy designed to sustain multi-year construction, feed-in power capacity, and support ongoing operations as customers come online. This funding plan sits alongside a $1 billion Morgan Stanley credit facility announced earlier in the year, which the company described as part of its broader financing framework to accelerate data center development across Georgia, Texas, North Carolina and Oklahoma.

Power availability remains a central constraint in the AI-data-center equation. Core Scientific’s Pecos expansion hinges on securing reliable, scalable power amid a regional energy market that has historically supported large-scale computing deployments. The company’s additional 300 MW under contract with the local utility provider helps de-risk the project, but ongoing power planning and grid coordination will be critical as the campus scales toward 1.5 GW gross capacity.

Beyond Pecos, Core Scientific’s strategy includes pursuing further expansion via behind-the-meter solutions and additional land acquisitions to sustain a longer-term growth trajectory. The company’s move mirrors a broader trend among crypto miners: diversify revenue streams by converting facilities into data centers that can host AI workloads, a market dynamic that has attracted attention from investors seeking exposure to AI compute infrastructure without the volatility of mining cycles.

A broader AI-infrastructure shift in crypto-mining

Core Scientific is not alone in this pivot. The sector has seen several peers exploring revenue streams tied to AI compute and data-center capabilities alongside their mining operations. In February, MARA Holdings disclosed the acquisition of a 64% stake in Exaion, a French infrastructure company expanding into AI services, signaling a strategic move to broaden AI-focused offerings beyond traditional mining. The broader lineup of miners—Hive, Hut 8, TeraWulf and Iren—have also signaled and undertaken steps to repurpose mining facilities into data centers or AI-focused campuses as margins in mining tighten and AI workloads proliferate. MARA’s Exaion stake is a notable example of this trend.

Related developments in the energy-to-AI transition include the reported near-term sale of idle assets in the industrial sector. Alcoa is close to selling its Massena East smelter in upstate New York to NYDIG, a deal expected to close by mid-year, as the plant has remained idle since 2014 due to high energy costs and global competition. The move aligns with a broader wave of crypto miners seeking to anchor AI data-center capacity in repurposed industrial assets. Massena East and, earlier, Century Aluminum’s Hawesville smelter sale to TeraWulf for $200 million to be converted into a high-performance computing and AI facility illustrate this trend in action. Century Aluminum Hawesville was cited in industry reporting as part of the same wave of industrial-to-AI data-center conversions.

The confluence of higher AI compute demand, capital-intensive buildouts, and the repurposing of mining infrastructure suggests a structural shift in how crypto players engage with data center economics. The trend also dovetails with broader coverage of AI data-center backbones that quietly emerged from the crypto era, underscoring how the sector’s assets are being repurposed to power the next wave of digital infrastructure. CoreWeave and related reporting have underscored these dynamics for investors looking beyond immediate mining yields.

What to watch next

As Core Scientific advances toward its 2027 capacity milestone, investors and industry observers will be watching several key factors: the pace of vertical construction at Pecos, the timing and reliability of power deliveries, and whether the leasing demand materializes at the projected scale. The financing package will also come under scrutiny as proceeds are deployed across multiple sites, with the ability to meet debt obligations and service ongoing capital needs a critical consideration for lenders and future project partners.

Beyond Core Scientific, the sector’s AI-forward pivot remains under observation. The timing of AI deployment milestones at Exaion, the integration of repurposed mining facilities into AI data centers, and the long-term profitability of these ventures will shape how crypto miners position themselves in a world where AI infrastructure investment appears increasingly attractive to both developers and institutions.

Readers should monitor updates from Core Scientific as project approvals progress, as well as any additional capital-raising moves or land acquisitions that may signal further capacity expansion across the United States.

Crypto infrastructure company Startale Group has selected Sunnyside Labs’ Privacy Boost as the official privacy partner for its Startale App, built for Soneium, a Sony-linked blockchain network. 

Startale Group said Tuesday that the integration will add self-custodial private transfer features to the app, including shielded balances, private peer-to-peer transfers and privacy-enabled payment flows on Soneium.

The move adds a consumer-facing privacy layer to Startale’s Sony-linked Soneium ecosystem as crypto apps try to give users more control over visible onchain activity while preserving compliance mechanisms for operators.

Sunnyside Labs co-founder and CEO Taem Park told Cointelegraph that selective auditability means transaction details remain hidden from the public, while authorized service operators can review them through a feature called Audit View. 

Related: Japan’s SBI VC Trade launches retail USDC lending as stablecoin use grows

He compared the system to traditional finance, in which banks can view customers’ transactions for compliance purposes. “This means AML and regulatory obligations can be met without requiring all activity to be publicly transparent. This is a fundamentally different architecture from privacy tools that obscure transactions from everyone, including the operator,” Park told Cointelegraph. 

The design leaves a key question over who ultimately controls access to private transaction data. While Privacy Boost is designed to hide transaction details from the public, its Audit View model preserves operator-level visibility for compliance purposes. That means users are relying not only on cryptography, but also on Sunnyside Labs’ controls around when and how shielded transaction records can be reviewed. 

Selective disclosure faces privacy, compliance tradeoffs

The Audit View model puts Startale’s integration in the same category as privacy systems that try to keep transaction data hidden from the public while still allowing some form of review by trusted or authorized parties.

Zcash, one of the earliest privacy-focused blockchain networks, uses zero-knowledge proofs and supports selective disclosure through viewing keys. Secret Network uses a similar access-control concept for private smart contract data, with its documentation describing viewing keys as encrypted passwords for viewing data tied to a specific smart contract and private key.

Examples of selective disclosure implementations. Source: TRM Labs

Blockchain analytics company TRM Labs said in a Feb. 19 report that transaction view keys provide “strong privacy but weak compliance utility,” particularly for high-value transfers, rapid fund movements or systemic monitoring. 

Privacy Boost’s Audit View model appears to take a different approach by giving authorized operators access to private transaction records for compliance purposes. That may make the system more practical for regulated consumer applications, but it also means disclosure is not controlled only by users.

In its findings, TRM Labs said that “No single privacy regime satisfies all stakeholder needs.” However, the company added that hybrid approaches combining visibility, access controls and limits around private-asset conversions may offer the most workable path.

Magazine: AI-driven hacks could kill DeFi — unless projects act now

Cointelegraph is committed to independent, transparent journalism. This news article is produced in accordance with Cointelegraph’s Editorial Policy and aims to provide accurate and timely information. Readers are encouraged to verify information independently.

CoinDesk Indices presents its daily market update, highlighting the performance of leaders and laggards in the CoinDesk 20 Index.

The CoinDesk 20 is currently trading at 2071.97, down 0.4% (-9.25) since 4 p.m. ET on Friday.

Eight of 20 assets are trading higher.

Leaders: APT (+1.3%) and AAVE (+0.6%).

Laggards: XLM (-1.7%) and HBAR (-0.9%).

The CoinDesk 20 is a broad-based index traded on multiple platforms in several regions globally.

Decentralized finance (DeFi) has transformed financial transparency by making vast amounts of blockchain data publicly accessible. However, access does not equal understanding. Without the right analytical approach, even experienced participants can misinterpret signals and make costly decisions. This article explores how to properly read Total Value Locked (TVL), leverage analytics platforms, identify opportunities through on-chain data, and avoid misleading metrics.

1. Understanding TVL (Total Value Locked) Beyond the Surface

Total Value Locked (TVL) is one of the most widely cited metrics in DeFi. It represents the total value of assets deposited in a protocol’s smart contracts. While often used as a proxy for trust and adoption, TVL can be misleading if interpreted naively.

Key considerations:

• Price Sensitivity: TVL fluctuates with token prices. A rise in TVL may reflect asset appreciation rather than new capital inflows.
• Double Counting: Assets can be reused across protocols (e.g., staking LP tokens), inflating TVL figures artificially.
• Capital Efficiency: High TVL does not necessarily indicate efficiency or profitability. Some protocols generate more revenue with lower TVL.
• Liquidity Composition: Understanding whether TVL consists of stablecoins, volatile assets, or incentivized deposits is crucial.

Takeaway: TVL should be contextualized alongside metrics like protocol revenue, user activity, and capital turnover.

2. Leveraging Analytics Platforms

Modern DeFi analytics platforms provide tools to interpret blockchain data effectively. Among the most widely used is Dune Analytics, which allows users to query blockchain data using SQL and visualize it through dashboards.

Popular platforms include:

• Dune Analytics — Custom dashboards, community-driven insights
• DeFiLlama — TVL tracking across chains and protocols
• Nansen — Wallet labeling and smart money tracking
• Glassnode — Advanced metrics for macro-level insights

Best practices:

• Cross-check data across multiple platforms to avoid bias
• Understand the methodology behind each metric
• Customize dashboards to track specific strategies or protocols

Takeaway: Tools are only as powerful as the user’s ability to interpret them critically.

3. Finding Opportunities Using On-Chain Data

On-chain data offers a transparent view into market behavior, enabling users to identify emerging opportunities before they become widely known.

Key strategies:

• Wallet Tracking: Monitor “smart money” wallets to identify early positioning in new protocols
• Liquidity Flows: Track capital entering or exiting protocols to gauge momentum
• Token Distribution: Analyze holder concentration to assess risk and decentralization
• Yield Analysis: Compare real yield (fees generated) versus incentivized yield (token rewards)

For example, a sudden increase in liquidity combined with rising user activity—but without excessive token incentives—may indicate organic growth.

Takeaway: Early signals often appear in behavior, not headlines.

4. Avoiding Misleading Metrics

Not all metrics are created equal. Some are intentionally designed to attract users rather than inform them.

Common pitfalls:

• Inflated APYs: High yields often rely on unsustainable token emissions
• Vanity Metrics: User counts or transaction volumes can be inflated through bots or incentives
• Short-Term Spikes: Temporary liquidity mining campaigns can distort long-term viability
• Ignoring Risk Factors: Metrics rarely account for smart contract risk, governance issues, or market volatility

A protocol offering 1,000% APY may appear attractive, but if the reward token rapidly depreciates, real returns may be negative.

Takeaway: Always distinguish between nominal and real value.

Conclusion

DeFi analytics is not about memorizing metrics—it is about understanding context, questioning assumptions, and synthesizing multiple data points into a coherent view. Tools like Dune Analytics and Nansen empower users to navigate this landscape, but critical thinking remains the most valuable asset.

In a market driven by transparency yet clouded by noise, those who can interpret on-chain data effectively gain a decisive edge.

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