Powerbuilding Digital Newsletter #131

Fitness / Motivation / Technology & A.I / Crypto

Welcome to Edition 131 of the Powerbuilding Digital Newsletter—a space built for those committed to steady progress and long-term development. Each week, this newsletter aims to bring clarity, insight, and practical ideas across the areas that influence modern life: physical strength, mental resilience, emerging technology, and digital innovation.

Growth rarely happens through sudden breakthroughs alone. More often, it comes from consistent effort, thoughtful learning, and the ability to adapt while staying focused on your direction. This edition continues that approach—grounded, practical, and forward-looking.

Here’s what we’re exploring this week:

Fitness Info & Ideas
Strength-building strategies, training structure, and recovery insights designed to support long-term performance and sustainable progress.
Motivation & Wellbeing
Mental discipline and balanced routines that help maintain focus, reduce stress, and support a steady mindset in a fast-paced world.
Technology & AI Trends
Key developments in artificial intelligence and emerging technologies that are shaping productivity, creativity, and the future of work.
Crypto & Digital Asset Trends
Innovations in blockchain, Web3 platforms, and digital infrastructure that highlight how decentralized technology continues to evolve beyond speculation.

Edition 131 is about staying steady while continuing to evolve. Build strength patiently, keep learning, and stay aware of the changes shaping the future.

Disclaimer:
The information provided in the Powerbuilding Digital Newsletter is for educational and informational purposes only. It is not medical, mental health, legal, financial, or investment advice. Always consult qualified professionals before making decisions related to your health, training, finances, technology usage, or participation in digital assets. Digital assets involve risk, and all actions taken based on this content are solely your responsibility.

Fitness

Training Frequency: How Often Should You Hit Each Compound Lift?

Training frequency is one of the most misunderstood variables in strength development.

People argue over programs.
They argue over exercises.
They argue over rep ranges.

But frequency — how often you practice a lift — is what quietly determines long-term progress.

The question isn’t, “How often can you lift heavy?”

The real question is:

“How often can you recover and improve?”

The Skill Component of Compound Lifts

Squats, deadlifts, presses, and rows are not just muscular events. They are motor skills.

The nervous system improves through exposure. The more frequently you practice a movement with quality, the more efficient you become.

For strength-focused athletes, this matters enormously.

If you only squat once per week, you’re asking your nervous system to refine a complex skill every seven days. Progress will be slower compared to squatting two or three times weekly at appropriate intensities.

Frequency builds familiarity.
Familiarity builds efficiency.
Efficiency builds strength.

Strength vs. Hypertrophy Frequency

Your goal changes your answer.

For Strength Development:
Most lifters respond best to hitting major compound lifts 2–3 times per week in some variation. That does not mean maxing out three times per week. It means distributing volume and intensity intelligently:

One heavier day (higher intensity, lower reps)
One moderate volume day
Optional lighter or speed-focused exposure

This improves neural adaptation without overwhelming recovery.

For Hypertrophy (Muscle Growth):
Muscle protein synthesis peaks and returns to baseline within 24–72 hours for trained lifters. That means stimulating a muscle group only once per week is rarely optimal.

Most research and real-world results suggest training each major muscle group 2 times per week produces superior growth compared to once weekly, assuming total volume is controlled.

You can achieve this through:

Upper/lower splits
Push/pull/legs (repeated twice weekly)
Full-body training

Frequency allows volume to be distributed instead of crammed into one exhausting session.

The Recovery Equation

More frequency is not automatically better.

If performance drops week to week, joints ache chronically, or bar speed decreases consistently, your recovery is compromised.

Recovery depends on:

Sleep quality
Caloric intake
Protein consumption
Stress management
Training intensity management

High frequency only works when fatigue is managed.

Strength is built in recovery — not during the lift itself.

Practical Guidelines

For most intermediate lifters:

Squat: 2x per week
Bench Press: 2–3x per week
Deadlift (heavy hinge): 1–2x per week
Overhead Press or Secondary Pressing: 1–2x per week

Deadlifts are often more taxing systemically, so many lifters progress best with one heavy exposure and one lighter variation per week.

Bench press, being less systemically demanding, tolerates higher frequency.

The Hybrid Approach (Strength + Size)

If your goal is balanced powerbuilding:

Anchor each week with one heavy compound session.
Add a secondary day with moderate volume and controlled reps.
Follow compounds with hypertrophy-focused accessory work.

This approach reinforces the skill of the lift while driving muscular growth.

The Real Answer

“How often should I train each lift?”

As often as you can recover from while improving performance.

If strength is climbing, joints feel stable, and energy remains consistent — your frequency is appropriate.

If performance stagnates and fatigue accumulates — reduce either intensity or volume before blaming frequency.

Compound lifts reward consistency more than intensity spikes.

Hit them often enough to stay sharp.
Recover enough to stay strong.
Progress enough to stay motivated.

That balance is where results live.

Motivation

Inner Alignment vs. External Pressure

There is a tension most people live with but rarely name.

It’s the tension between who they are becoming
and who the world expects them to be.

External pressure is loud.
Deadlines.
Expectations.
Comparison.
Status.
Performance metrics.
Social validation.

It measures your output.

Inner alignment is quiet.
It asks different questions.

Does this feel right?
Does this build me?
Does this move me toward who I say I want to become?

External pressure pushes from the outside.
Inner alignment pulls from within.

And the direction you follow determines the kind of life you build.

External pressure isn’t inherently negative. In fact, pressure can refine you. It can force discipline, sharpen focus, and reveal weaknesses. Athletes grow under structured demand. Entrepreneurs adapt under market stress. Families mature under responsibility.

But pressure without alignment creates fracture.

When you chase metrics that don’t match your values, your nervous system knows. Stress becomes heavier. Motivation becomes brittle. Success feels hollow because it was never internally chosen — it was externally negotiated.

That’s when burnout appears.

Burnout is often misdiagnosed as exhaustion.
More accurately, it is misalignment sustained over time.

You can work hard and feel energized if your effort matches your internal compass. But even moderate effort becomes draining when it conflicts with who you are.

Alignment doesn’t mean ease. It means coherence.

It means your habits reflect your standards.
Your schedule reflects your priorities.
Your training reflects your identity.

When inner alignment is strong, external pressure becomes fuel instead of threat.

In strength training, this is obvious. If you are lifting to impress others, you rush progress. You chase numbers recklessly. You compare constantly. But if you lift because discipline is part of your identity, the pressure of the bar feels purposeful.

The same principle applies to career, relationships, and personal growth.

Alignment reduces internal friction.

When you know why you are doing something, the “how” becomes manageable.

Without alignment, you are reactive. You respond to expectations, trends, and opinions. Your direction changes with every external shift. Your nervous system stays on alert, scanning for approval or criticism.

With alignment, you are stable. You evaluate pressure rather than absorbing it. You can say no without guilt. You can say yes without doubt.

External pressure is inevitable.

Inner alignment is optional — but powerful.

The strongest individuals are not those who eliminate pressure. They are the ones who anchor themselves deeply enough that pressure sharpens rather than shatters them.

Alignment is not found once. It is maintained.

Through reflection.
Through honest self-audit.
Through disciplined choices that reinforce who you are becoming.

When inner alignment is intact, external pressure loses its chaos.

It becomes resistance — and resistance, when properly engaged, builds strength.

Technology & A.I

CoMP: The Protocol That Could Put a Price Tag on AI Data

A new technical standard may reshape how artificial intelligence systems access the internet’s information.

The nonprofit consortium IAB Tech Lab has released version 1.0 of its Content Monetization Protocol (CoMP) for public comment, proposing a structured framework that would require AI companies to establish commercial agreements with publishers before crawling or ingesting their content.

The specification, published on March 10, 2026, will remain open for feedback until April 9.

At its core, the proposal attempts to address a growing imbalance in the economics of artificial intelligence: AI models depend heavily on high-quality information, yet the web currently provides no standardized system for compensating the creators of that information.

The Missing Layer in the AI Economy

According to Anthony Katsur, the issue is structural.

AI systems rely on three fundamental inputs:

computing hardware
electricity
information

Only one of those inputs lacks an established commercial marketplace.

“Information is the only input that does not yet have a consistent commercial infrastructure,” Katsur said when announcing the framework.

CoMP aims to create that infrastructure.

Why Publishers Are Demanding Change

The proposal arrives at a moment of mounting tension between publishers and AI developers.

Search engines increasingly present AI-generated summaries that answer user questions directly. While convenient for users, those summaries reduce the number of visitors who click through to original articles.

Industry data suggests the effects are already significant:

Average publisher traffic declines of 20–60% from AI-generated summaries
Some niche sites reporting losses as high as 90%
Overall website traffic down more than 11% over five years

Faced with these losses, many publishers have begun blocking AI crawlers entirely.

Attempts to create softer standards have stalled. The proposed llms.txt protocol — designed to signal whether AI systems can access content — has seen little adoption among major AI companies such as OpenAI, Anthropic, and Google.

How CoMP Would Work

Technically, CoMP introduces a structured handshake between AI systems and content owners.

When an AI crawler arrives at a website:

The bot requests permission to access content.
If no commercial agreement exists, the request can be denied.
The bot is redirected to a licensing endpoint where terms can be negotiated.
Once an agreement is reached, an access token is issued.
That token authorizes specific content ingestion requests.

The token-based system creates an auditable record of who accessed what content and under which commercial terms — something largely absent from today’s open web architecture.

Importantly, CoMP does not replace existing blocking systems. Instead, it creates a commercial pathway after content owners restrict unauthorized crawling.

A Marketplace for AI Training Data

The protocol also anticipates a future marketplace layer.

Instead of negotiating with thousands of publishers individually, AI companies could establish agreements with content marketplaces that aggregate licensed material.

Those marketplaces would deliver content based on defined parameters such as:

relevance
quality
freshness
response latency

Once delivered, the AI system could incorporate the information into its responses.

The framework supports three different compensation structures:

Pay-per-crawl: payment whenever AI bots access content
Pay-per-use: payment when content is actually used in outputs
Outcome-based: payment tied to attribution or user engagement

Rather than forcing a single economic model, the protocol allows different arrangements depending on the use case.

Why Brands Care Too

The framework isn’t only about publishers.

Brands increasingly discover that AI systems summarize their products, services, and corporate information without consulting them. This can strip context or present outdated details.

CoMP introduces a system where brands can expose their content through structured queries, allowing AI models to retrieve information through controlled interfaces rather than uncontrolled scraping.

In effect, AI crawlers would behave more like API clients than anonymous web scrapers.

Industry Reactions

Several media and technology organizations have expressed support for the proposal.

Executives from The Weather Company and Bertelsmann described the protocol as a necessary step toward establishing fair compensation and maintaining high-quality information ecosystems.

Others have emphasized that global standards will be necessary if the AI economy is to remain sustainable for content creators.

Still, some critics argue the standards process moves too slowly relative to the speed at which AI is already disrupting publisher revenue models.

The Larger Infrastructure Project

CoMP is part of a broader effort by IAB Tech Lab to adapt digital advertising and media infrastructure to the rise of autonomous AI systems.

Recent initiatives from the organization include:

an Agentic Real-Time Bidding (RTB) framework for AI-driven ad auctions
a User Context Protocol donated by LiveRamp for agent-based identity exchange
new standards for programmatic advertising transparency

Together, these efforts reflect an attempt to rebuild the digital advertising supply chain around AI-driven agents.

Amazon Pushes Agentic AI Into Healthcare Workflows

Cloud computing giant Amazon Web Services is expanding its artificial intelligence ambitions into healthcare operations, unveiling a new system designed to automate patient interactions, clinical documentation, and medical billing.

The product, called Amazon Connect Health, builds on the company’s existing Amazon Connect service — a cloud-based contact center platform that recently surpassed $1 billion in annual revenue.

Unlike general-purpose AI tools, the new platform is designed specifically for healthcare organizations, with capabilities that extend across the full lifecycle of a patient interaction.

An End-to-End AI Workflow

The system introduces a form of agentic AI, meaning autonomous digital agents can perform tasks across multiple steps of a process rather than simply assisting users with isolated actions.

Amazon Connect Health includes five core functions:

Automated patient verification during incoming calls
AI-assisted appointment scheduling
Pre-visit summaries generated for clinicians
Ambient clinical documentation that transcribes visits in real time
Automated medical coding for insurance billing

The goal, according to Rajiv Chopra, is to move beyond individual tools and instead address the entire healthcare workflow.

Rather than delivering “point solutions,” Chopra said AWS aims to build systems that solve operational problems from the first patient interaction through post-visit administration.

Competing With Microsoft in the AI Health Race

Amazon’s push into healthcare AI places it in direct competition with Microsoft, which acquired healthcare voice-recognition specialist Nuance Communications for $19.7 billion in 2022.

Nuance’s DAX Copilot platform is now embedded inside major electronic health record systems and has become a widely used AI documentation tool for clinicians.

At the same time, a wave of AI scribe startups has raised hundreds of millions of dollars to automate medical documentation — a major source of administrative workload for doctors.

Amazon is attempting to differentiate its approach by offering a broader operational platform rather than a standalone documentation product.

Early Adopters

Several healthcare organizations are already testing the system.

Among them:

UC San Diego Health, which manages approximately 3.2 million patient interactions annually
One Medical, Amazon’s own healthcare practice, where the technology has supported documentation for more than one million visits
Netsmart, which supplies electronic health record software to over 1,300 community-based healthcare organizations

The system integrates directly with Epic, the largest EHR platform in the United States, while connecting to other systems through integration partners.

It also links to AWS HealthLake, Amazon’s medical data repository, which is gaining new AI capabilities to standardize and structure healthcare records.

A Test for AI Adoption in Healthcare

Despite rapid advances in AI technology, healthcare institutions have historically adopted new digital tools slowly.

Hospitals often cite several barriers:

strict data privacy requirements
difficulty integrating new systems into existing workflows
uncertainty about financial returns from new technology

However, early research suggests that AI documentation tools may deliver measurable benefits.

A randomized trial published in the New England Journal of Medicine AI found that ambient AI documentation systems reduced clinician administrative workload by about 30 minutes per day per provider while also lowering burnout levels.

Amazon’s Agentic AI Strategy

Amazon Connect Health is part of a broader initiative inside AWS to build industry-specific AI applications rather than simply providing raw computing infrastructure.

The project is led by Colleen Aubrey, whose Applied AI Solutions team focuses on creating finished software products tailored to particular industries.

Aubrey has described the company’s strategy as placing “AI teammates” at the center of business operations — autonomous systems capable of handling routine tasks on behalf of employees.

Healthcare is the first sector receiving a specialized version of Amazon Connect, but AWS has indicated that other industries may soon receive similar AI platforms.

The Bigger Picture

Healthcare administration represents one of the largest sources of inefficiency in the medical system. In the United States, administrative tasks account for hundreds of billions of dollars in annual healthcare spending.

If agentic AI systems can reliably automate scheduling, documentation, and billing processes, they could significantly reduce operational overhead for hospitals and clinics.

At the same time, healthcare’s strict regulatory environment means the sector will likely adopt these technologies more cautiously than other industries.

For Amazon, the success of Connect Health may serve as a key indicator of whether agentic AI can move from experimental tools to operational infrastructure in one of the most complex sectors of the economy.

Datavault AI Draws Institutional Capital as Data Monetization Gains Momentum

Technology firm Datavault AI Inc. is continuing to develop its platform focused on helping organizations manage, secure, and monetize digital information, while expanding its reach across media and enterprise environments.

The company’s platform centers on tools that allow businesses and content owners to treat data not just as operational information, but as a structured digital asset that can be authenticated, distributed, and integrated into commercial workflows.

According to the company, the system combines several core capabilities:

Data monetization infrastructure that enables organizations to license and distribute data in controlled environments
Credentialing technology used to authenticate ownership, rights, and usage permissions
Digital engagement tools designed to connect enterprises, creators, and audiences through data-driven experiences
Real-world asset tokenization systems, allowing digital representation and management of physical or intellectual assets

The company describes the platform as infrastructure that allows organizations to capture the value created by their digital information while maintaining control over how that information is accessed and used.

CEO Nathaniel Bradley summarized the idea behind the system by describing data as an increasingly important operational resource for modern businesses.

“Data is no longer just information. It’s an asset class,” Bradley said, emphasizing the need for tools that allow enterprises and media organizations to manage that value securely.

Expanding Media and Content Integrations

As part of its platform development, Datavault AI has been extending its technology into media and content ecosystems.

Recent collaborations include agreements with Sports Illustrated and NFL Alumni, where the company’s technology is expected to support digital engagement initiatives and data-driven content distribution.

The company has also expanded its media capabilities through the acquisition of API Media, which adds infrastructure for managing and distributing digital media assets.

These integrations are intended to help content organizations better manage licensing, audience interaction, and digital rights across multiple platforms.

Building Infrastructure Around Data Ownership

Datavault AI’s platform is designed to address several challenges that organizations face when working with large amounts of digital information, including:

protecting intellectual property and digital rights
managing content distribution across multiple platforms
creating new revenue channels from existing data
verifying authenticity and usage permissions

The company’s tools are intended to operate across enterprise systems, media networks, and emerging digital asset environments where information is increasingly treated as a tradable resource.

Continued Platform Development

As Datavault AI expands its technology stack, the company says it is focusing on building infrastructure that enables businesses to securely capture, manage, and distribute data at scale.

By combining credentialing systems, media distribution capabilities, and digital asset frameworks, the platform aims to provide organizations with a unified way to manage the growing economic value associated with their digital information.

Crypto

VeryAI Builds Palm-Scan Identity System to Detect Real Humans Online

Startup VeryAI has introduced a biometric identity platform designed to help digital platforms distinguish real users from AI-generated accounts and automated bots.

The company recently secured $10 million in seed funding, led by Polychain Capital, to support the launch of its palm-scan verification technology.

The system is aimed at cryptocurrency exchanges, fintech applications, and online communities that are increasingly dealing with deepfakes, synthetic identities, and automated bot networks.

How the Palm-Scan System Works

VeryAI’s technology uses a smartphone camera to capture an image of a user’s palm. Instead of storing the image itself, the platform converts the scan into an encrypted biometric signature.

That signature is then used to verify that a real person is interacting with a platform.

Key technical features include:

Palm biometrics captured through a smartphone camera
Conversion of the scan into irreversible biometric feature representations
Zero-knowledge proof verification, allowing users to prove they are human without revealing personal information
Identity attestations recorded on the Solana blockchain

Because the system stores only encrypted biometric representations rather than raw images, the company says the original biometric data cannot be reconstructed.

Why Palm Biometrics?

VeryAI chose palm scans rather than facial recognition for identity verification.

According to the company, palm patterns are highly distinctive and less publicly exposed than facial features, which are widely available in photos and videos online.

This reduces the risk that biometric data could be scraped or spoofed by AI systems.

The platform converts palm features into mathematical signatures that confirm a user’s uniqueness while keeping their identity private.

Addressing the Rise of AI-Generated Accounts

Founder and CEO Zach Meltzer said the technology is intended to address a growing challenge across the internet.

“We’re entering a period where the internet can no longer assume that every account, message, or video is created by a real person,” Meltzer said.

Advances in generative AI have made it easier to create automated accounts that imitate real users, sometimes at massive scale.

These systems can be used to:

create fake social media accounts
manipulate token incentives through Sybil attacks
impersonate users in crypto communities
distribute scams or misinformation

Identity systems that verify the presence of a real person are increasingly being explored as a way to address these risks.

Privacy-Focused Identity Models

The design of VeryAI’s system reflects a broader trend in decentralized identity development: balancing authentication with privacy.

Instead of revealing full personal identities, users can prove specific attributes — such as uniqueness or humanity — using cryptographic techniques.

This concept has been advocated by Vitalik Buterin, who has promoted identity systems that rely on zero-knowledge proofs to confirm information without exposing underlying data.

Early Integrations

VeryAI says it is already working with several crypto and technology platforms.

Organizations integrating the system include:

MEXC
Colosseum
Clique
Talus

Additional exchanges and wallet providers are reportedly preparing to implement the verification system.

The funding round also included participation from the Berggruen Institute and Anagram, while Anatoly Yakovenko joined as an angel investor.

The Growing Market for “Proof of Human”

As artificial intelligence continues to blur the distinction between human and machine activity online, identity verification tools are becoming a key area of development in the crypto and technology sectors.

Projects such as World, co-founded by Sam Altman, have explored similar ideas using iris-scan verification.

These systems attempt to create a digital credential proving that a user is a real person — without requiring disclosure of personal data.

For developers, the goal is not just to confirm that humans exist on a platform, but to ensure that each account represents a unique and authentic individual.

As AI-generated content and automated identities continue to grow, technologies capable of verifying human presence may become an increasingly important layer of internet infrastructure.

Coinbase Pushes Back on Claims It Opposed Bitcoin Tax Relief

Leaders at Coinbase are rejecting online claims that the company has been lobbying against tax relief for small Bitcoin transactions in the United States.

The allegations circulated widely among cryptocurrency advocates on social media, suggesting the exchange had discouraged lawmakers from adopting a so-called de minimis tax exemption for small Bitcoin payments while supporting similar exemptions for stablecoins.

Coinbase executives say those claims are inaccurate.

Coinbase Leadership Denies Allegations

CEO Brian Armstrong responded publicly, calling the accusations “totally false” and describing them as misinformation.

Armstrong said he has personally advocated for a tax exemption that would allow small Bitcoin transactions to occur without triggering capital gains reporting requirements.

“I’ve spent a bunch of time lobbying for Bitcoin’s de minimis tax exemption and will continue doing so,” he said.

Other executives echoed that message.

Paul Grewal, Coinbase’s chief legal officer, wrote that the company has “never lobbied against BTC,” while Faryar Shirzad also dismissed the claims.

Why Tax Policy Matters for Bitcoin Payments

Under current U.S. tax rules, cryptocurrency transactions are generally treated as taxable events.

That means even small purchases using Bitcoin — such as buying a cup of coffee — can require users to calculate capital gains or losses based on the asset’s price at the time of the transaction.

Advocates argue this requirement creates a major barrier to Bitcoin’s use as a day-to-day payment system.

A de minimis exemption would remove tax reporting obligations for transactions below a certain threshold, making small payments more practical.

Legislative Efforts in Washington

Several lawmakers have attempted to introduce such exemptions.

In 2025, Cynthia Lummis proposed legislation that would have allowed tax-free crypto transactions up to $300, with a total annual exemption cap of $5,000.

However, the proposal failed to gain sufficient support in Congress.

Current draft legislation under discussion — including elements related to the CLARITY Act — reportedly focuses more on tax treatment for stablecoins rather than Bitcoin transactions.

According to Bitcoin Policy Institute, the proposed tax exemption in that framework would apply primarily to U.S. dollar-pegged stablecoins.

Advocacy Groups Continue Pushing for Reform

Crypto policy groups are continuing to propose alternative frameworks.

The Washington-based Blockchain Association recently submitted a new set of digital asset tax recommendations to U.S. lawmakers aimed at simplifying compliance rules for cryptocurrency users.

Supporters of a de minimis exemption argue that clear tax policies could encourage broader adoption of digital assets for payments and everyday transactions.

For now, however, small crypto payments in the United States remain subject to existing capital gains rules — leaving the debate over tax reform unresolved.

U.S. Senate Moves to Block a Federal Reserve Digital Dollar

The U.S. Senate has approved a measure that would prevent the Federal Reserve from issuing a government-run digital dollar, marking one of the strongest congressional statements yet against the idea of a U.S. central bank digital currency (CBDC).

The provision passed as part of the broader 21st Century ROAD to Housing Act, receiving overwhelming bipartisan support in an 89–10 Senate vote. However, the proposal now faces uncertainty as the legislation moves to the U.S. House of Representatives, where lawmakers may challenge parts of the housing bill.

What the Bill Would Do

The provision included in the Senate legislation would prohibit the Federal Reserve from issuing a digital dollar — either directly or indirectly through banks or financial intermediaries — until at least the end of 2030.

The language in the bill states that the Fed:

“may not issue or create a central bank digital currency or any digital asset that is substantially similar to a central bank digital currency.”

While the Federal Reserve has studied digital currency systems, the United States has not moved beyond research and pilot discussions, unlike some other major economies that are testing or deploying CBDCs.

Concerns Around Financial Privacy

Opposition to a U.S. CBDC has been strongest among Republican lawmakers, who argue that a government-issued digital currency could create new forms of financial surveillance.

Industry groups supporting the provision framed the vote as a step toward protecting financial privacy.

Cody Carbone, head of Digital Chamber, said the Senate’s vote reinforces the idea that digital financial innovation in the United States should come primarily from the private sector rather than the government.

Supporters of the ban also argue that private stablecoins and blockchain-based financial services already provide digital payment solutions without requiring a government-issued token.

A Bill With Broader Political Challenges

Despite the strong Senate vote, the future of the measure remains uncertain.

The CBDC restriction is embedded within a much larger housing bill that includes provisions aimed at limiting how many homes large institutional investors — such as private equity firms — can own.

That housing policy has generated debate among lawmakers in the House, raising the possibility that the bill could face revisions or delays before becoming law.

Political Dynamics

The legislation also intersects with broader political priorities.

Donald Trump has previously expressed support for efforts to expand housing availability, one of the goals behind the bill.

However, the president has also indicated that he may delay signing legislation until Congress passes measures related to voter identification and citizenship verification ahead of upcoming midterm elections.

That political uncertainty could affect the timeline for the housing legislation and the CBDC prohibition contained within it.

The Bigger Digital Currency Debate

The Senate vote highlights the ongoing debate over how the United States should approach digital currency infrastructure.

Globally, several central banks — including China’s — are actively developing CBDCs as part of broader financial modernization efforts.

In the United States, however, policymakers remain divided over whether a government-issued digital dollar is necessary or desirable.

For now, the Senate’s decision suggests that lawmakers are leaning toward allowing private-sector digital assets and stablecoins to lead innovation in the country’s digital financial system rather than introducing a government-run alternative.

JPMorgan Sued Over Alleged Role in $328M Crypto Investment Scheme

A proposed class-action lawsuit filed in federal court accuses JPMorgan Chase of providing banking infrastructure that allegedly enabled a $328 million cryptocurrency investment scheme operated by Goliath Ventures.

The complaint was submitted to the U.S. District Court for the Northern District of California and brought by investor Robby Alan Steele on behalf of more than 2,000 individuals who say they suffered losses.

Steele, a California resident, claims he personally lost about $650,000, including funds withdrawn from a retirement account.

Allegations of a Crypto-Based Ponzi Scheme

According to the lawsuit, Goliath Ventures promoted “joint venture agreements” that promised profits from cryptocurrency trading and digital asset arbitrage strategies.

Federal prosecutors have separately alleged that the operation functioned as a Ponzi scheme, where funds from new investors were used to pay earlier participants rather than being generated through legitimate trading.

Authorities arrested Goliath’s chief executive, Christopher Delgado, on February 24 in connection with the case.

Banking Activity Under Scrutiny

The lawsuit claims that JPMorgan served as Goliath’s primary banking partner from January 2023 through mid-2025.

According to the filing, bank records show:

$253 million deposited into a Chase account associated with the company
$123 million transferred from that account to cryptocurrency wallets at Coinbase
About $50 million distributed to investors as supposed returns

The complaint alleges those payouts were largely funded by incoming deposits from new investors.

Plaintiffs argue that these patterns resemble classic Ponzi scheme cash flows.

Alleged Compliance Failures

The lawsuit claims the bank ignored multiple indicators that should have triggered closer scrutiny under anti-money-laundering regulations.

Among the warning signs cited in the complaint:

rapid inflows and outflows of funds
investor deposits being commingled in the same accounts
transfers between accounts allegedly controlled by Delgado
circular payment patterns associated with Ponzi schemes
little evidence of genuine cryptocurrency trading revenue

Financial institutions are required to maintain monitoring systems and file Suspicious Activity Reports when transactions raise potential fraud concerns.

The complaint also notes that JPMorgan uses Actimize, a compliance platform designed to flag unusual transactions using data analytics and automated monitoring.

Despite those systems, the lawsuit alleges the bank continued servicing the accounts.

Claims Presented in the Lawsuit

The complaint brings several legal claims against JPMorgan, including:

aiding and abetting fraud
aiding and abetting breach of fiduciary duty
negligence
unjust enrichment
violations of California’s Unfair Competition Law

Plaintiffs are seeking class-action status for affected investors, along with financial damages, restitution, and the recovery of any fees or benefits the bank allegedly received from the accounts.

The filing also demands a jury trial.

Legal Context

Banks have faced similar lawsuits in past financial fraud cases, where plaintiffs argued that financial institutions should have detected suspicious activity earlier.

In many cases, courts examine whether the bank had actual knowledge of the fraud or whether the transaction patterns were sufficiently unusual to require intervention.

For now, the allegations remain claims presented in a civil lawsuit, and the case will proceed through the federal court system unless dismissed or settled.

The outcome may help clarify how financial institutions are expected to monitor cryptocurrency-related activity as digital assets become increasingly integrated into the traditional banking system.

Insurance Industry Tests Stablecoin Payments for Premium Settlements

Global insurance brokerage Aon plc has completed a proof-of-concept trial using stablecoins to settle insurance premium payments, marking a new experiment in how blockchain-based dollars could be used in traditional financial operations.

The initiative involved collaboration with Coinbase and Paxos, the issuer behind the PayPal USD stablecoin.

According to Aon, the trial demonstrated that premium payments could be processed using dollar-backed digital tokens rather than conventional bank transfers.

How the Pilot Worked

During the demonstration, insurance premiums tied to internal programs were settled using stablecoins across multiple blockchain networks.

The transactions included:

USD Coin operating on the Ethereum network
PayPal USD (PYUSD) operating on the Solana network

Stablecoins are digital tokens designed to maintain a stable value by being backed by traditional currencies such as the U.S. dollar.

The pilot explored how these tokens could be used to move funds quickly while maintaining auditability and transparency across insurance transactions.

Exploring Blockchain in Insurance Operations

Aon said the test was designed to build practical experience with blockchain-based financial systems rather than immediately replace traditional payment infrastructure.

Tim Fletcher, head of Aon’s financial services group, described the trial as part of a broader effort to understand emerging financial technologies.

“As tokenized instruments become more widely used, clients need confidence that speed and innovation do not come at the expense of control,” Fletcher said.

He added that gaining hands-on experience with stablecoins helps the company advise clients on issues related to governance, risk management, and operational resilience.

Regulatory Context

The pilot comes shortly after the introduction of the GENIUS Act, which established a regulatory framework for stablecoin payments in the United States.

Clearer regulatory guidelines have encouraged financial institutions to begin exploring how blockchain-based payment systems could integrate with existing financial infrastructure.

Why Stablecoins Are Being Tested

Stablecoins offer several characteristics that appeal to financial institutions experimenting with blockchain payments:

near-instant settlement compared with traditional banking rails
transparent transaction records on public blockchains
programmable payments that can be integrated into financial systems
global accessibility across digital asset platforms

For industries such as insurance, which often involve large cross-border payments and complex settlement processes, these features may help streamline financial operations.

A Broader Trend in Financial Infrastructure

Aon’s trial reflects a growing interest among large financial institutions in testing blockchain-based payment systems.

While stablecoins were originally developed within the cryptocurrency sector, banks, payment providers, and financial service firms are increasingly evaluating how these digital tokens could function as part of mainstream financial infrastructure.

The proof-of-concept does not yet represent widespread adoption, but it illustrates how traditional industries are beginning to explore the operational potential of digital dollar systems as the financial technology landscape continues to evolve.