Bettors have also pooled well over $500 million on some of the largest political contracts on the site: The market for the U.S. presidential election winner has $319 million invested, one for the Democratic nominee is over $212 million (Vice President Kamala Harris is the overwhelming favorite), while another to decide who will be the Democratic candidate's vice presidential running mate has $10 million.

Biden's Exit Spurs Record $28M Daily Volume on Polymarket as Election Enters Uncharted Territory

SkyBridge Capital founder and CEO Anthony Scaramucci says Bitcoin (BTC) appears ready for more upside as it hovers around its all-time high.

In a new interview on the White Crypto YouTube channel, the hedge fund veteran says Bitcoin could go up by up to 65% from the current level before the end of the year.

“Well, every time I make a price prediction, I get it wrong. But I did say last year that I thought we could close in on $100,000. We didn’t quite get there until after the [President Trump] inauguration. But I do think this is $150,000 to $180,000 by year-end.”

According to Scaramucci, demand for Bitcoin from institutional investors is primed to keep going up.

“Bitcoin supremacy, if you will, is creeping up and I think that’s going to continue because it’s the go-to asset for institutional investors. That’s not to say that the other coins won’t do well. But I think institutional dollars that are coming into the space, something like 80% of those dollars will end up in Bitcoin.”

Scaramucci, however, says Bitcoin is currently facing various headwinds amid the heavy demand.

“There are a lot of things holding Bitcoin back. We’re fighting in the Gulf, we’re fighting in Ukraine and we’re fighting in the former Soviet Union, Russia. There’s global tension. There’s a fear of recession. We’re still getting over the aftermath, economically, of COVID. And so there are a lot of things holding Bitcoin back.

But despite that, there’s very heavy net buying of Bitcoin, particularly through the [exchange-traded funds] ETFs.”

Bitcoin is trading at $109,273 at time of writing.

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any losses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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Anthony Scaramucci Says $180,000 Bitcoin Price Explosion Possible As BTC ‘Supremacy’ Creeps Up – Here’s His Timeline

The most successful asset of the last 15 years is once again annihilating the doubters.

In the last hour, a total of $687.22 million in Bitcoin shorts have been liquidated, according to the crypto data aggregator CoinGlass.

The shorts have provided rocket fuel for a sudden move above $116,000.

BTC began the day at around $111,000, and is up 4.7% in the last 24 hours.

This week’s rally has placed BTC’s total value above tech giant Google, with only Amazon, Apple, Microsoft, Nvidia and Gold remaining in front.

The rally also once again places BTC closer in line with M2 global liquidity, which measures the total money supply, including cash, checking deposits and easily convertible near-money assets.

Although no one knows what’s next Bitcoin, the pseudonymous macro analyst Martin Folb is sharing an updated map of BTC’s price against global liquidity.

He tells his 219,000 X followers that BTC has officially moved past a key accumulation zone.

“Wyckoff Accumulation is officially over. Distribution begins as price follows global liquidity to $125k on way to $160k. I will be posting the next Wyckoff Distrubition to reacculuation schematic in confirmation.”

Wyckoff Accumulation is a technical analysis pattern that strategically tracks an asset during an extended consolidation phase, using price and volume behaviors to identify when supply at lower prices is absorbed.

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any losses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

Featured Image: Shutterstock/solarseven/Natalia Siiatovskaia

$687,220,000 in Bitcoin Shorts Liquidated in Just One Hour As BTC Explodes To $116,000

A zero-knowledge (ZK) proof computer processing altcoin is crashing after suddenly gaining support from the world’s largest crypto exchange platform by trading volume.

In a recent announcement, Binance said it is adding support for Lagrange (LA), preceding a significant dip in price.

“Binance is excited to announce that Lagrange will be added to Binance Simple Earn, ‘Buy Crypto,’ Binance Convert, and Binance Margin.”

After the announcement, the digital asset went from a seven-day high of $0.676 on July 9th down to $0.416 at time of writing, a 32% decrease during the last 24 hours.

Last month, LA saw the opposite happen to its price after gaining support from Coinbase, the top US-based crypto exchange. At that time, the asset saw a staggering gain of 216%, going from a price of $0.253 on June 4th to a peak of $1.50 just a day later.

According to the development team behind Lagrange, the project consists of two protocols – the ZK Prove Network, which provides universal proving services for rollups, apps, coprocessors and interoperability – and the ZK coprocessor, which allows smart contracts to run intensive off-chain computations that can then be verified on-chain.

“The Lagrange Coprocessor is a powerful tool for working with blockchain data, especially when you need to ensure the correctness of your data queries.”

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any losses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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Zero-Knowledge Proof Altcoin Lagrange (LA) Crashes Following Announcement of New Binance Listing

A widely followed crypto analyst believes Bitcoin’s (BTC) bull market is just weeks away from coming to an end.

The analyst pseudonymously known as Rekt Capital tells his 550,400 subscribers on the social media platform X that the Bitcoin bull market could end in two or three months if history repeats itself.

According to the pseudonymous analyst, the Bitcoin bull market typically hits the peak around 518 to 546 days after the halving, suggesting it could occur between mid-September and mid-October. The fourth Bitcoin halving took place in April 2024.

On what is in store for Bitcoin’s price over the coming weeks and months, the widely followed analyst says,

“If Bitcoin really does have two to three months left in its Bull Market…

Then this current period truly is the calm before the storm.”

Bitcoin is trading at $109,386 at time of writing.

Rekt Capital further says that even if the bull market extends beyond October, trying to capture the potential gains would be a high-risk and low-reward endeavor.

“The risk versus reward of that upside will likely not be worth heavy participation.

Is it worth capturing an additional +20 – 30% uptrend while risking a -60 to -70% Bear Market?”

On altcoins, the widely followed analyst says they could enjoy a rally once Bitcoin rises above the current all-time high of just under $112,000.

“When Bitcoin broke out into Price Discovery Uptrend 1 in November 2024…

Altcoins rallied exponentially during that time.

Altcoins would likely run once Bitcoin breaks out into Price Discovery Uptrend 2.”

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Bitcoin Just Weeks Away From Hitting Bull Market Peak if History Repeats, According to Analyst – Here’s His Outlook

A closely followed crypto analyst says that one mid-cap altcoin looks primed to quadruple by August while updating his outlook on Dogecoin (DOGE) and Solana (SOL).

In a new strategy session, crypto trader Ali Martinez tells his 139,600 followers on the social media platform X that Pudgy Penguin (PENGU), the native asset of a non-fungible token (NFT) collection with the same name, appears ready to skyrocket aided by the launch of its upcoming exchange-traded fund (ETF).

“Slap yourself if you are sleeping on PENGU. This is a textbook bullish retest. $0.060 by August is just the start. Once the ETF gets approved, who knows how far this can go.”

PENGU is trading for $0.019 at time of writing, a 31.4% increase during the last 24 hours. A rise to Martinez’s target would represent a 216% gain for the asset.

Moving on to the popular meme asset DOGE, Martinez says that every time it forms a specific pattern, its price tends to rise. The analyst says he envisions the dog-themed digital asset rising to between $0.20 and $0.25.

“Every time Dogecoin forms this pattern, price takes off. Right now, Dogecoin is sitting at the bottom of a parallel channel. A buying spike here could send Dogecoin to $0.20 and maybe even $0.25.”

DOGE is trading for $0.179 at time of writing, a 4% gain on the day.

Concluding his analysis with the smart contract platform Solana, Martinez notes that the asset has broken through its resistance zone and is on its way to a price tag of $164 by the end of the week.

“Solana is forming a symmetrical triangle, and an 8% move could be next. A close above $153 could send Solana above $164.”

SOL is trading for $156 at time of writing, a 1.6% gain on the day.

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any losses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

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Trader Predicts Mid-Cap Altcoin Could Explode 200%+ by August, Maps Path Forward for Dogecoin and Solana

These first-of-kind money market rates transform Aave pool activity into conventional overnight rates to support interest rate derivatives and floating rate loans.

NEW YORK, June 17, 2025 /PRNewswire/ -- CoinDesk Indices, a leading provider of digital-asset benchmarks, in collaboration with Sentora, a pioneer in institutional DeFi solutions, today announced the launch of CoinDesk Overnight Rates (CDOR), the first benchmark interest rates that draw upon Aave's lending pools to provide standardized overnight rates for major stablecoins.

CDOR to Support Industry Growth

CDOR rates are designed to support markets for hedging funding costs, securing yields, and developing cross-currency rate strategies. Calculated and published daily, these rates are accessible to exchanges, market makers, protocol treasuries, and structured-product desks.

Stani Kulechov, Founder of Aave Labs says, "CDOR is a new benchmark interest rate built on Aave's deep onchain liquidity. It provides a transparent, risk-free lending rate that unlocks new use cases for stablecoins, such as derivatives and fixed-income products, enabling more efficient, scalable, and automated financial markets."

The first CDOR rates utilize activity on Aave v3's Core variable borrow pools for USDC and USDT. CoinDesk Indices has released a methodology that converts this on-chain activity into a historical daily (or "overnight") rate that can be aggregated over longer periods. These pools, whose rates react instantly to changes to supply and demand, are important facilities in decentralized finance that reflect activity of a large population of borrowers and lenders.

Andy Baehr, CFA, Head of Product and Research, CoinDesk Indices says "Stablecoins are expected to grow into the trillions, but there is no institutional-grade money market for trading and hedging term rates. CDOR rates provide a cornerstone element for the stablecoin rates markets, using the same conventions as TradFi benchmarks, which support the largest derivatives markets in the world."

Anthony DeMartino, CEO, Sentora says, "Sentora's mission is to make on-chain finance as efficient as traditional finance. With CDOR rates you can switch from floating to fixed funding, or speculate on the curve, in a single, capital-efficient trade; a crucial building block that's been missing for years. These rates will enable new DeFi use cases and Sentora is happy to support the evolution of capital markets on-chain."

Liquidity Providers Signal Support for CDOR

Exchange-traded futures contracts, currently under development, will settle against CDOR rates and will provide market participants with new and powerful tools for risk management and strategy implementation. Galaxy, FalconX, Flowdesk and Tyr Capital will act as founding market makers.

Ed Hindi, CIO, Tyr Capital says, "CDOR rates enable the creation of a broad range of financial derivatives that are currently missing in the crypto financial ecosystem. This addition alongside a clearer regulatory environment should exponentially increase the interaction of institutional players with DeFi. The ability to efficiently manage interest rate risk is a game changer for the CeDeFi markets. Tyr Capital is thrilled to be more widely involved in making the TradFi and crypto relationship more symbiotic."

Jason Urban, Global Head of Trading at Galaxy says, "With CDOR rates, the market gains a powerful rate signal that reflects real-time borrower demand and enables smart, scalable trading strategies. It's a meaningful step in bridging DeFi and traditional finance, making stablecoin markets more accessible and actionable for sophisticated investors."

Joshua Lim, Global Co-Head of Markets, FalconX says, "We are pleased to partner with CoinDesk Indices and Sentora on their CDOR product suite. The next phase of growth in crypto will be driven by convergence of CeFi and DeFi capital markets."

Reed Werbitt, US CEO, Flowdesk says, "The introduction of CDOR will enable broader institutional adoption and participation in crypto credit markets, enhancing capital efficiency and risk management across our trading strategies. The ability to mitigate interest rate risk is a critical foundation of a functioning capital market, and we're excited to be working with Sentora to bring this product to fruition."

By turning on-chain market activity into standardized interest rates, CDOR lays the groundwork for exchange-traded money-market futures and other rate-based derivatives.

For additional information on CDOR please visit https://sentora.com/cdor-stablecoin-rate.

View the CoinDesk Overnight Rates (CDOR) - Aave | USDC and Aave | USDT.

About CoinDesk Indices

Since 2014, CoinDesk Indices has been at the forefront of the digital asset revolution, empowering investors globally. A portfolio company of the Bullish Group, its indices form the foundation of the world's largest digital asset products. CoinDesk Indices is regulated in the UK by the Financial Conduct Authority and offers products across multi-asset indices, reference rates, and strategies. Flagships such as the CoinDesk Bitcoin Price Index and the CoinDesk 20 Index set the industry standard for measuring, trading, and investing in digital assets. With tens of billions of dollars in benchmarked assets, CoinDesk Indices is a trusted partner.

About Sentora

Sentora, born from the recent merger between DeFi technology specialist IntoTheBlock and financial solutions provider Trident Digital, is a leader in developing institutional-grade DeFi solutions, yield strategies and risk-management infrastructure. Sentora's solutions connect leading digital asset firms and large capital allocators to the advantages of decentralized finance.

About Aave Protocol

Aave is the leading decentralized, non-custodial liquidity protocol, with over $40 billion in total value locked (TVL). It allows users to earn yield on deposits and borrow a wide range of digital assets without intermediaries. Core features include risk management tools such as supply and borrow caps, flash loans, and GHO — a decentralized, overcollateralized stablecoin native to the protocol. Aave is fully governed by the Aave Decentralized Autonomous Organization (DAO). Learn more or participate in governance at https://governance.aave.com.

Disclaimer

CoinDesk is a portfolio company of the Bullish Group. CoinDesk Indices, Inc., including CC Data Limited, its affiliate which performs certain outsourced administration and calculation services on its behalf (collectively, "CoinDesk Indices"), does not sponsor, endorse, sell, promote, or manage any investment offered by any third party that seeks to provide an investment return based on the performance of any index. CoinDesk Indices is neither an investment adviser nor a commodity trading advisor and makes no representation regarding the advisability of making an investment linked to any CoinDesk Indices index. CoinDesk Indices does not act as a fiduciary. A decision to invest in any asset linked to a CoinDesk Indices index should not be made in reliance on any of the statements set forth in this document or elsewhere by CoinDesk Indices. All content displayed here or otherwise used in connection with any CoinDesk Indices index (the "Content") is owned by CoinDesk Indices and/or its third-party data providers and licensors, unless stated otherwise by CoinDesk Indices. CoinDesk Indices does not guarantee the accuracy, completeness, timeliness, adequacy, validity, or availability of any of the Content. CoinDesk Indices is not responsible for any errors or omissions, regardless of the cause, in the results obtained from the use of any of the Content. CoinDesk Indices does not assume any obligation to update the Content following publication in any form or format. © 2025 CoinDesk Indices, Inc. All rights reserved.

Forward-Looking Statements: This press release may include "forward-looking statements" relating to future events or the Bullish Group's future financial or operating performance, business strategy, and potential market opportunity. Such forward-looking statements are based upon estimates and assumptions that, while considered reasonable by the Bullish Group, are inherently uncertain and are subject to risks, uncertainties, and other factors which could cause actual results to differ materially from those expressed or implied by such forward-looking statements. You should not place undue reliance on any such forward-looking statements, which speak only as of the date they are made, and the Bullish Group undertakes no duty to update these forward-looking statements.

SOURCE CoinDesk Indices

CoinDesk Overnight Rates (CDOR) to Support Stablecoin Money Markets based on Aave

Beyond the Prompt: AI and the Expanding Scope of Delegated Work

We asked the AI to document our options endpoint. It wrote the roadmap for our options exchange metadata — and helped us build a significantly better product for our clients.

TL;DR

We added a few features and were using AI to help generate documentation descriptions from our OpenAPI endpoint specs. It’s fast, consistent, and helps us stay lean. But recently, something unusual happened. When we asked Claude to write documentation for our options_v1_markets endpoint, it didn’t just document what was there — it documented what should be there.

The result? A dozen tickets for enhancements, roadmap discussions, and ideas that emerged from the AI’s output. This is a classic case of Delegation Drift: when AI overachieves its narrow task and ends up delegating work back to humans. In our case, that work led to substantial improvements in the quality, scope, and future value of the product. The AI's output ultimately shaped our roadmap for options exchange metadata and led to a more robust solution for our client base.

What Is Delegation Drift?

Delegation Drift describes a shift that occurs when AI tools go beyond their explicitly delegated task, creating new expectations or work downstream. It's not scope creep from stakeholders — it's scope expansion triggered by suggestion-rich AI outputs.

But here’s the thing: that drift isn’t a failure mode. In our experience, it was a feature. Delegation Drift helped us see beyond the limits of our current product and prompted improvements we hadn't scoped yet.

The Case: options_v1_markets Endpoint

This endpoint exposes static metadata about options markets: launch dates, integration flags, support contact info, mapping totals, and more. The schema was well-defined and reviewed. Claude was tasked with writing doc copy from the OpenAPI spec. Here’s what it inferred as “existing or expected” fields and concepts:

Available Option Chains : Structured listings of tradable option instruments per market. Claude assumed these should be exposed to help consumers understand product coverage at a glance — including granularity of strikes, tenors, and active contracts. This metadata serves as a compact inventory of the market's instrument space. While we already capture this at the instrument level, at the market level it would be useful to provide summary indicators such as the number of listed underlyings, maximum and minimum tenor available, the depth of strike intervals per product type, or whether full chain coverage is consistent across expiries. Because this metadata is curated by our content team and rarely changes, a concise overview could support onboarding, strategy setup, and coverage validation for institutional users without requiring dynamic queries.

: Structured listings of tradable option instruments per market. Claude assumed these should be exposed to help consumers understand product coverage at a glance — including granularity of strikes, tenors, and active contracts. This metadata serves as a compact inventory of the market's instrument space. While we already capture this at the instrument level, at the market level it would be useful to provide summary indicators such as the number of listed underlyings, maximum and minimum tenor available, the depth of strike intervals per product type, or whether full chain coverage is consistent across expiries. Because this metadata is curated by our content team and rarely changes, a concise overview could support onboarding, strategy setup, and coverage validation for institutional users without requiring dynamic queries. Strike Price Intervals : The spacing between strikes in the options chain, critical for understanding market depth and liquidity provisioning. While we maintain detailed strike interval data at the instrument metadata level, Claude flagged the value of exposing general strike spacing patterns at the exchange level. This could include typical interval ranges (e.g., $1, $2.50, $5 strikes), whether intervals are uniform or adaptive based on underlying price, and how strike density varies across product types. This exchange-level perspective is essential for both retail UIs and institutional pricing models, where assumptions about overall market granularity directly affect slippage modeling and volatility surface construction.

: The spacing between strikes in the options chain, critical for understanding market depth and liquidity provisioning. While we maintain detailed strike interval data at the instrument metadata level, Claude flagged the value of exposing general strike spacing patterns at the exchange level. This could include typical interval ranges (e.g., $1, $2.50, $5 strikes), whether intervals are uniform or adaptive based on underlying price, and how strike density varies across product types. This exchange-level perspective is essential for both retail UIs and institutional pricing models, where assumptions about overall market granularity directly affect slippage modeling and volatility surface construction. Expiration Schedules : Metadata around available expiration dates, recurrence patterns (daily, weekly, monthly), and how far into the future products are listed. This directly impacts the usability of the data for strategy backtesting, calendar spread modeling, and portfolio roll planning.

: Metadata around available expiration dates, recurrence patterns (daily, weekly, monthly), and how far into the future products are listed. This directly impacts the usability of the data for strategy backtesting, calendar spread modeling, and portfolio roll planning. Settlement Mechanisms : While we already capture this at the instrument level, Claude implicitly suggested surfacing common settlement characteristics at the market level — e.g., whether an options market supports cash settlement, physical delivery of underlyings, or synthetic mechanisms. These patterns often map to product classes like INVERSE , VANILLA , and QUANTO , depending on the combination of quote, base, and settlement currencies. Providing this summary at the market level helps consumers understand structural constraints without querying the full instrument list.

: While we already capture this at the instrument level, Claude implicitly suggested surfacing common settlement characteristics at the market level — e.g., whether an options market supports cash settlement, physical delivery of underlyings, or synthetic mechanisms. These patterns often map to product classes like , , and , depending on the combination of quote, base, and settlement currencies. Providing this summary at the market level helps consumers understand structural constraints without querying the full instrument list. Implied Volatility Calculations : Metadata indicating whether implied vols are available, how they are derived (e.g., mid-price models, Black-Scholes, skewed surfaces), and whether they are exchange-reported or independently computed.

: Metadata indicating whether implied vols are available, how they are derived (e.g., mid-price models, Black-Scholes, skewed surfaces), and whether they are exchange-reported or independently computed. Exercise Styles (American/European) : Describes which type of contract behavior each market supports, which has downstream implications for pricing, hedging, and early exercise modeling.

: Describes which type of contract behavior each market supports, which has downstream implications for pricing, hedging, and early exercise modeling. Greeks Calculation Metadata : Whether the platform provides Greeks (delta, gamma, theta, etc.), how often they are updated, and what pricing assumptions are used — critical for margining and strategy simulation.

: Whether the platform provides Greeks (delta, gamma, theta, etc.), how often they are updated, and what pricing assumptions are used — critical for margining and strategy simulation. Minimum Tick Sizes : While we already capture precise tick sizes at the instrument level, Claude suggested surfacing general tick size ranges and patterns at the exchange metadata level. This would provide consumers with quick insights into the overall precision characteristics of a market — such as minimum and maximum tick sizes across all option types, or whether the exchange uses uniform vs. variable tick schedules. This exchange-level summary helps with initial market evaluation, trading system configuration, and understanding general quoting constraints without requiring instrument-by-instrument analysis.

: While we already capture precise tick sizes at the instrument level, Claude suggested surfacing general tick size ranges and patterns at the exchange metadata level. This would provide consumers with quick insights into the overall precision characteristics of a market — such as minimum and maximum tick sizes across all option types, or whether the exchange uses uniform vs. variable tick schedules. This exchange-level summary helps with initial market evaluation, trading system configuration, and understanding general quoting constraints without requiring instrument-by-instrument analysis. Benchmark Scores (already present, but underutilized): AI emphasized their role in venue comparison, trading quality assessment, and market structure research. It recommended we surface them more clearly for quantitative and institutional users, helping teams prioritize venue selection and inform strategy allocation.

(already present, but underutilized): AI emphasized their role in venue comparison, trading quality assessment, and market structure research. It recommended we surface them more clearly for quantitative and institutional users, helping teams prioritize venue selection and inform strategy allocation. Order Book and Trade Integration Flags (already present): These detail how real-time and historical data is ingested per exchange — including whether streaming or polling is used for trades and books. Claude proposed documenting them explicitly to help users gauge latency, completeness, and integration maturity.

(already present): These detail how real-time and historical data is ingested per exchange — including whether streaming or polling is used for trades and books. Claude proposed documenting them explicitly to help users gauge latency, completeness, and integration maturity. Margin Requirements and Collateral Specs (already included in internal data, but not highlighted): The AI assumed these were critical metadata points for any serious institutional platform. It recommended highlighting how option margining is handled (fixed, SPAN-based, etc.), whether collateral requirements differ across markets, and how margin offsets apply across multi-leg strategies.

Some of these were not part of the original documentation brief. All of them were plausible. Some of them now exist as tickets in our planning backlog.

What Changed?

This wasn’t our first time using AI to write documentation — we’ve used OpenAPI specs to drive automated doc generation for years. What was different this time was the depth of domain inference. Claude didn’t just reword the schema; it inferred what else should be in there if the goal was to serve real-world institutional options use cases.

The AI took a static spec and recontextualized it as a product brief. It connected dots across markets, assumed advanced use cases like volatility surface modeling and margin analytics, and suggested metadata enhancements accordingly. The result was not simply a better piece of documentation — it became the seed of a more complete and competitive options metadata platform.

Why It Matters

The implications of this Delegation Drift were immediately tangible. It transformed a tactical task — write documentation — into a strategic planning catalyst. The AI raised the bar for what “complete” metadata looked like, and did so based on pattern recognition across financial data architecture.

For our team, this meant creating new product tickets, adjusting our roadmap, and elevating our internal expectations of what our options market metadata should actually include. The suggestions were grounded enough to act on and visionary enough to change our direction.

Delegation Drift, far from being disruptive, pushed us toward excellence — and gave us the foundation to deliver higher value to our clients.

How To Work With Delegation Drift

To take advantage of Delegation Drift, you have to treat AI like a junior product strategist — not just a code assistant. This means reviewing its outputs not only for correctness, but for intent, assumption, and implied value.

You can operationalize this by separating speculative fields from confirmed ones, assigning reviewers for AI-driven insights, and ensuring those insights have a place in the backlog if they’re valuable. It’s also helpful to tune prompts or configure filters when you want strictly bounded behavior — but in our case, that unbounded scope was a gift.

The New Options Metadata Fields

The AI's suggestions materialized into five core metadata fields that significantly enhance our options exchange coverage:

Options Exercise Styles - Captures whether an exchange supports American (any time), European (expiration only), Bermudan (specific dates), or other exotic exercise mechanisms. This directly impacts pricing models and early exercise strategies for institutional users.

Options Settlement Types - Documents how positions are settled: cash settlement, physical delivery, basket settlement, hybrid approaches, or conditional mechanisms. This metadata is crucial for margin calculations and cross-asset hedging strategies.

Options Expiry Intervals - Tracks the variety of expiration schedules available (daily, weekly, monthly, quarterly, bi-annual, annual). Essential for calendar spread modeling and understanding the temporal granularity of each exchange's product offering.

Options Strike Boundary Methods - Defines how exchanges determine strike price ranges: percentage of spot, fixed notional ranges, delta-based boundaries, liquidity-driven limits, or custom discretion. This helps users understand coverage depth and predict available strike ranges for strategy construction.

Options Strike Interval Methods - Captures strike spacing approaches: dynamic by price tier, dynamic by moneyness and expiry, fixed intervals, or custom discretion. Critical for understanding market granularity and liquidity distribution across the options chain.

Additionally, we enhanced the Other Document URLs field to include funding rate methodology documentation and improved the structure for capturing exchange-specific calculation approaches.

These fields transform our options metadata from basic availability flags into a comprehensive framework for institutional options trading infrastructure. Each field addresses specific use cases the AI identified: from volatility surface construction to margin modeling to strategy backtesting - exactly the kind of comprehensive coverage that emerged from Delegation Drift.

Final Thoughts

Delegation Drift isn’t just a pattern — it’s a signal that your AI tools are capable of critical reasoning and synthesis. When used intentionally, this can drive clarity in product thinking, uncover gaps in schemas, and inspire iteration beyond your current roadmap.

In our case, what started as doc generation became cross-functional value creation. The documentation didn't just describe our product — it redefined it.

That’s the kind of drift we want more of.

Delegation Drift (n.) — The phenomenon where AI-generated output expands the scope of a delegated task, resulting in new human obligations or roadmap expansion beyond the original intent — often leading to better product outcomes.

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Delegation Drift: When AI Helps Write Your Docs and Roadmap

Building the foundation for comprehensive blockchain analytics at CoinDesk Data

Following our journey from optimizing block data retrieval with NFS to leveraging Azure's L-Series machines for efficient processing, and most recently introducing our Address Metadata Endpoint, we're excited to share the next major milestone in our infrastructure evolution: comprehensive transaction indexing by blockchain address at scale.

This advancement represents a fundamental shift in how we approach blockchain data , enabling developers to build everything from portfolio tracking tools to sophisticated blockchain analytics platforms. Today, we're diving deep into the technical architecture that makes it possible to efficiently query, paginate and analyze transaction histories for any address across multiple blockchains.

The Scale Challenge

Bitcoin : 1.42 billion addresses, 1.26 billion transactions

: 1.42 billion addresses, 1.26 billion transactions Ethereum : 325 million addresses, 2.86 billion transactions

: 325 million addresses, 2.86 billion transactions Solana: 2.32 billion addresses, 419 billion transactions

When it comes to handling vast amounts of data, the scale of blockchain networks presents unique hurdles. Traditional approaches either couldn't handle this or came with prohibitive costs. We needed a solution that was both performant and economically viable for a data company operating at our scale.

The Storage Challenge

After extensive evaluation of various database technologies—including BigQuery, Snowflake, ClickHouse, and specialized blockchain databases—PostgreSQL emerged as the clear winner. But not for the reasons you might expect.

The API Cost Reality: At our scale of millions of API calls per month, usage-based pricing becomes prohibitive. Google BigQuery costs ~$5 per TB queried. With our normalized datasets ranging from 254GB (Bitcoin) to 61TB (Solana), even simple address queries would be costly (per thousand calls). At millions of monthly API calls, we'd be looking at $50,000-$500,000+ in query costs alone. Compare this to PostgreSQL infrastructure costs of $5,000-$15,000 monthly for equivalent performance.

Query Latency for Real-Time APIs: Our users expect sub-100ms API responses. BigQuery's cold start penalty means even simple queries take 2-10 seconds. Snowflake has similar latency issues for small, frequent queries. PostgreSQL with proper indexing consistently delivers 10-50ms response times for our specific query patterns—transaction lookups by address with pagination.

Write Performance for Blockchain Ingestion: Blockchain data arrives in real-time bursts. New blocks every 12 seconds (Ethereum) or 400ms (Solana) require sustained write performance. BigQuery has streaming insert limits of 100,000 rows/second and charges $0.01 per 200MB. PostgreSQL handles 1M+ sustained inserts/second on proper hardware without additional costs. For Solana's transaction volume, BigQuery's streaming costs alone would exceed $50,000 monthly.

Complex Join Performance: Our normalization strategy requires efficient multi-table joins. PostgreSQL's cost-based optimizer and B-tree indexes excel at the address_id → transaction_id → hash lookups that power our pagination. Analytical databases optimize for columnar scans, not the row-level lookups and joins that APIs require.

What PostgreSQL Loses: We're honest about the trade-offs. ClickHouse would crush us on analytical aggregations across full datasets. BigQuery's columnar compression would reduce our storage costs by 60-80%. For pure analytics workloads, we'd choose differently. But we're building APIs, not running occasional analytics queries.

The Technical Truth: PostgreSQL won because at millions of API calls with sub-100ms latency requirements, operational costs matter more than theoretical performance. The best database is the one you can afford to run at scale.

The Hybrid Storage Architecture

Our solution combines the best of both worlds: PostgreSQL for indexing and relationships, Cloudflare R2 for blob storage.

PostgreSQL: The Index Layer

We store three normalized tables per blockchain: ‍

-- Address normalization (saves 24 - 46 % storage vs denormalized) CREATE TABLE address_eth ( id BIGINT PRIMARY KEY GENERATED ALWAYS AS IDENTITY, blockchain_address TEXT NOT NULL UNIQUE ); -- Transaction references with auto-incrementing IDs CREATE TABLE transaction_eth ( id BIGINT PRIMARY KEY GENERATED ALWAYS AS IDENTITY, hash TEXT NOT NULL UNIQUE ); -- The junction table that makes everything work CREATE TABLE address_transaction_eth ( address_id BIGINT NOT NULL, transaction_id BIGINT NOT NULL, timestamp TIMESTAMP NOT NULL, PRIMARY KEY (address_id, transaction_id), FOREIGN KEY (address_id) REFERENCES address_eth(id), FOREIGN KEY (transaction_id) REFERENCES transaction_eth(id) );

This normalization delivers massive space savings. For Ethereum alone, we reduced storage from 825.87 GB (denormalized) to 449.12 GB (normalized)—a 45.6% reduction. When popular exchange addresses participate in millions of transactions, storing the full address string repeatedly becomes prohibitively expensive.

Cloudflare R2: The Detail Layer

While PostgreSQL handles the indexing and relationships efficiently, we store the full transaction details as compressed JSON blobs in Cloudflare R2. Each transaction gets a blob identified by its hash (0x5c504ed432cb51138bcf09aa5e8a410dd4a1e204ef84bfed1be16dfba1b22060.json.gz):

This hybrid approach means:

Fast pagination through PostgreSQL indices

through PostgreSQL indices Rich transaction details when needed from R2

when needed from R2 Cost optimization by keeping expensive detailed data in object storage

by keeping expensive detailed data in object storage Flexibility to evolve transaction schemas without database migrations

Horizontal Sharding Strategy

Different blockchains require different sharding strategies based on their scale:

Bitcoin (1 shard): At 254GB total, a single PostgreSQL instance handles the load comfortably. Bitcoin's lower transaction throughput doesn't require horizontal scaling yet.

Ethereum (5 shards): With ~90GB per shard, we achieve the sweet spot between performance and operational complexity. Address-based sharding using hash(address) % 5 ensures natural distribution.

Solana (10 shards): The massive 61.75TB dataset necessitates aggressive sharding. Each shard manages ~6.2TB, keeping individual PostgreSQL instances within manageable limits. ‍

const getShardConnection = ( assetId, address ) => { const shardCounts = { 1 : 1 , 2 : 5 , 3 : 10 }; // BTC: 1, ETH: 5, SOL: 10 const shardId = crypto.createHash( 'sha256' ) .update(address) .digest() .readUInt32BE( 0 ) % shardCounts[assetId]; return `PG_BC_ADDRESS_COLLECT_ ${(shardId + 1 ).toString().padStart( 2 , '0' )} ` ; };

Efficient Pagination at Scale

The real magic happens in our pagination strategy. Instead of traditional offset-based pagination (which becomes slow at large offsets), we use cursor-based pagination with our auto-incrementing transaction IDs: ‍

// Get latest 100 transactions for an address const getLatestTransactions = async (assetId, address, limit = 100 ) => { const shard = getShardConnection(assetId, address); return await shard.query( ` SELECT t.id, t.hash, at.timestamp FROM address_transaction_ ${assetId} at JOIN address_ ${assetId} a ON at.address_id = a.id JOIN transaction_ ${assetId} t ON at.transaction_id = t.id WHERE a.blockchain_address = $1 ORDER BY at.timestamp DESC, t.id DESC LIMIT $2 ` , [address, limit]); }; // Get next page using cursor const getTransactionsBefore = async (assetId, address, beforeId, limit = 100 ) => { const shard = getShardConnection(assetId, address); return await shard.query( ` SELECT t.id, t.hash, at.timestamp FROM address_transaction_ ${assetId} at JOIN address_ ${assetId} a ON at.address_id = a.id JOIN transaction_ ${assetId} t ON at.transaction_id = t.id WHERE a.blockchain_address = $1 AND t.id < $2 ORDER BY at.timestamp DESC, t.id DESC LIMIT $3 ` , [address, beforeId, limit]); };

This approach maintains consistent performance regardless of how deep users paginate through transaction histories.

Application-Level Data Federation

When users need full transaction details, our application layer federates data from PostgreSQL and Cloudflare R2: ‍

const getTransactionDetails = async (transactionHashes) => { // Batch fetch from R2 for efficiency const r2Promises = transactionHashes.map( hash => fetchFromR2( ` ${hash} .json.gz` ) ); const transactionDetails = await Promise .all(r2Promises); return transactionDetails.map( detail => JSON .parse(detail)); }; const getAddressTransactionsWithDetails = async (assetId, address, limit) => { // Get transaction references from PostgreSQL const transactions = await getLatestTransactions(assetId, address, limit); // Fetch full details from R2 const details = await getTransactionDetails( transactions.map( tx => tx.hash) ); // Merge at application level return transactions.map( ( tx, index ) => ({ ...tx, details : details[index] })); };

The Building Blocks for Blockchain Analytics

This infrastructure provides three foundational APIs that enable comprehensive blockchain analysis:

Transaction Indexing: Complete, paginated transaction histories for any address Block Data: Full block information by number (available on our API) Address Metadata: Comprehensive address insights (covered in Series VI, available on our API)

Together, these APIs provide everything needed to build:

Portfolio Tracking Tools : Real-time and historical balance calculations across all addresses

: Real-time and historical balance calculations across all addresses Risk Analysis Platforms : Transaction pattern analysis and compliance monitoring

: Transaction pattern analysis and compliance monitoring DeFi Analytics : Liquidity tracking, yield farming analysis, and protocol interactions

: Liquidity tracking, yield farming analysis, and protocol interactions Institutional Analytics: Large-scale blockchain data analysis for financial institutions

Performance Benchmarks

Our production deployment delivers:

Sub-50ms response times for address transaction queries (first page)

for address transaction queries (first page) Consistent pagination performance regardless of offset depth

regardless of offset depth 99.9% uptime across all blockchain networks

across all blockchain networks Linear scaling as we add new blockchains and shards

Looking Forward

This transaction indexing infrastructure is already powering several internal tools at CoinDesk Data, and we're preparing to expose these capabilities through our public API in the coming months.

The combination of cost-efficient PostgreSQL sharding, intelligent data federation, and hybrid storage represents a scalable foundation that will grow with the blockchain ecosystem. As new chains emerge and transaction volumes continue to explode, our architecture can adapt without fundamental changes.

In our next post, we'll explore how we're using this transaction indexing infrastructure to power real-time portfolio analytics and cross-chain analysis tools. The ability to efficiently query transaction histories at scale opens up entirely new possibilities for blockchain data products.

On-Chain Series VIII: Scaling Transaction Indexing with PostgreSQL and Hybrid Storage Architecture

Bitcoin (BTC) snapped a three-day decline after January job growth in the U.S. fell short of expectations.

The largest cryptocurrency rose above $100,000 for the first time since Feb. 4, according to CCData, after the Bureau of Labor Statistics said the economy added 143,000 jobs in January, below the forecast 170,000 and down from 256,000 in December.

Still, the unemployment rate dropped to 4%, compared with an expected 4.1% and December’s 4.1% and growth in average hourly earnings blew past estimates coming in at 0.5% compared with the expected at 0.3%. "Relatively high wage inflation and a low unemployment rate mean that the Federal Reserve isn't likely to cut rates anytime soon, but markets already know that," said Zach Pandl, Grayscale’s head of research. "As long as equity markets remain broadly stable, Bitcoin could make news highs later this quarter".

The chance of the Federal Reserve lowering the benchmark interest rate at its March meeting fell to 8% from 15% after the report, according to CME FedWatch data.

The Fed cut the fed funds rate by 100 basis points over the last four months of 2024, and several weeks ago investors were expecting more of the same in 2025. A string of strong economic and inflation data since, however, has had the Fed quickly backtracking on its dovishness and traders pricing out the odds of any further policy ease.

UPDATE (Feb. 7, 13:59 UTC): Adds bitcoin price reaction in headline and first two paragraphs, Fed rate-cut chances in fourth. UPDATE (Feb. 7, 14: 23 UTC): Adds bitcoin price tops $100,000

UPDATE (Feb. 7, 15: 08 UTC): Adds quote from Grayscale’s head of research in fourth paragraph.

This story originally appeared on Coindesk

Bitcoin Tops $100K After U.S. Added Fewer Than Forecast Jobs in January

Bitcoin just blew past $113,800 on Thursday, setting a new all-time high. The oldest digital asset has been on a tear for the last several months — and has nearly doubled over the past year, climbing from $57,899 a year ago today.

CoinDesk analysts and industry experts are watching closely to see if bitcoin

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can rise to $120,000, or if this week's price action is just an ephemeral gasp.

James Van Straten, CoinDesk Bitcoin analyst (18:55 UTC) : The 2021 bull run's second half was purely leverage and derivatives-driven. It had a 50% hash rate correction, and all on-chain metrics were bearish, plus we had incoming fed rate hikes for the first time. Market cycle is completely different with a new buyer in the market, a new Fed chair potentially incoming with cuts and a crypto-pro U.S. president. Also, don't forget the swath of bitcoin buying treasury companies.

Oliver Knight, co-leader of CoinDesk data and tokens (18:55 UTC) : Net accounts are still short (CoinDesk's Omkar Godbole mentioned this was a retail indicator) . This is interesting, as in previous cycles, we had retail euphoria, but not so much this time.

However, while on the surface a record high for bitcoin is almost certainly bullish, a number of technical indicators paint a different picture: the daily RSI has now made three lower highs, an example of bearish divergence indicating the move could be short-lived. Trading volume has also dropped off since the initial record high in January, and BTC is still below its respective record highs against EUR and GBP, indicating dollar weakness over BTC strength.

BTC's volume and RSI indicators. (TradingView)

Also, the trading firms I speak to are bearish, but it is worth noting that they were also bearish from BTC's $30k to $70k run in the last cycle's double top.

BTC $113K All-Time High Liveblog: Is This Run Different?

New Zealand is preparing to impose new limits on international cash transfers in a bid to strengthen efforts to combat serious financial crimes.

Associate Justice Minister Nicole McKee says the government is taking further steps to overhaul the nation’s anti-money laundering and counter-terrorism financing (AML/CFT) regime.

The objective is to prevent criminal misuse of the financial system while bringing more clarity and consistency for businesses.

“Cabinet has agreed to introduce a bill to strengthen enforcement powers for police and regulators to crack down on those involved in money laundering.

It will also establish a new financial sanctions supervisory regime and initiate engagement on a sustainable levy to fund AML/CFT system improvements.”

The government wants to place a cap of 5,000 NZD, or $3,000, on international money transfers. The plan also involves preventing criminals from tapping into crypto to move the proceeds of their illicit activities.

“An upper limit will be set on how much cash can be transferred internationally ($5,000 per transfer), reducing the ability of the criminal organization to move its funds offshore.

We will also make it more difficult for criminals to convert cash to high-risk assets such as cryptocurrencies by banning crypto ATMs.”

The Financial Intelligence Unit (FIU) will likewise be authorized to order banks and other businesses subject to the AML/CFT Act to provide relevant information on persons of interest.

“Since 2019, the global financial and regulatory landscape has shifted significantly. We need a smarter, more agile AML/CFT system – one that targets criminals’ ability to launder money, while enabling New Zealand businesses to operate efficiently and competitively.”

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Disclaimer: Opinions expressed at The Daily Hodl are not investment advice. Investors should do their due diligence before making any high-risk investments in Bitcoin, cryptocurrency or digital assets. Please be advised that your transfers and trades are at your own risk, and any losses you may incur are your responsibility. The Daily Hodl does not recommend the buying or selling of any cryptocurrencies or digital assets, nor is The Daily Hodl an investment advisor. Please note that The Daily Hodl participates in affiliate marketing.

Generated Image: Midjourney

$3,000 Cap on International Transfers Hitting New Zealand Amid Anti-Money Laundering Efforts

Bitcoin

clinched a fresh record high above $113,000 on Thursday, attempting to break away from the range it has been trading in for months.

The largest and oldest cryptocurrency hit $113,313 during the U.S. session, CoinDesk price data shows. It was up 3.7% over the past 24 hours.

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The new record comes less than a day after it briefly topped $112,000 on some exchanges, then retreated below $111,000 in the later hours.

Bitcoin's rally to new highs was buoyed by strong inflows into ETFs, relentless corporate adoption by crypto treasury companies and an increasingly favorable regulatory climate, Gerry O'Shea, head of global market insights at Hashdex, said in a note.

"While the macro environment will continue to remain uncertain, we believe the bull market is far from over and new catalysts, including more institutional platforms allowing access to bitcoin, may help drive the price of BTC to $140,000 or higher this year," he said.

The broader crypto market was also climbing higher on Thursday. Ethereum's ether

topped $2,800 and was up more than 5%, while XRPgained 3.5%. The broad-market CoinDesk 20 Index advanced 3.4% to its strongest level since May.

UPDATE (July 10, 17:15 UTC) : Updates prices.

Biden's Exit Spurs Record $28M Daily Volume on Polymarket as Election Enters Uncharted Territory

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