The agentic trust stack we've been monitoring is solidifying into distinct product categories. The core architectural debate has shifted to where identity lives: at the payment layer, where the card networks are aggressively building, or at the protocol layer, as decentralized identity proponents argue. Today's briefing tracks production deployments and the strategic framing from both camps.
Two incorporated AI entities, Clawbank and Shodai, have executed the first AI-to-AI Ricardian contract, a legally binding agreement where the prose is directly linked to self-executing code on the Ethereum blockchain. The milestone, which occurred on Thursday, enabled Shodai's smart contract to automatically trigger a payment upon its AI counterparty, Clawbank, accepting a project milestone. This event marks a significant step in realizing the 30-year-old concept of unifying legal agreements with their automated execution on-chain.
Why it matters
This is a landmark demonstration of autonomous commercial agents operating within a legally and cryptographically defined trust framework. For builders, this moves agentic commerce from theoretical to practical, showcasing a future where legal entities can be entirely programmatic. It eliminates the friction of human intermediaries for negotiation, signing, and settlement, creating a template for automated, continuous compliance. This has profound implications for legal tech, on-chain identity, and the creation of fully autonomous, economically independent software entities.
The execution of a Ricardian contract between two AI agents represents a significant advancement in the field of autonomous systems and smart contracts. It demonstrates the potential for AI-driven entities to engage in complex legal and financial transactions without direct human intervention, leveraging the security and immutability of the blockchain for enforcement. This could pave the way for more sophisticated decentralized autonomous organizations (DAOs) and other on-chain business models.
Following our note earlier this week that Microsoft's governance architecture was being positioned as a potential enterprise standard, the company has formally released a strategic paper outlining its blueprint for deploying autonomous AI agents in asset management, framing 'Trust as Infrastructure' as the foundational layer. The paper, published Wednesday, argues that for agentic AI to be adopted in regulated industries, trust must be engineered into the system from the start. Key mechanisms include continuous authentication, immutable action logging, policy-as-code for defining agent behavior, and real-time compliance monitoring.
Why it matters
This is a significant strategic move from a tech giant to define the essential architecture for enterprise-grade agentic AI. The 'Trust as Infrastructure' concept solidifies the narrative that governance, identity, and accountability are prerequisites for adoption, not afterthoughts. For founders, this paper provides a high-signal framework for what enterprise buyers will demand: systems with auditable, verifiable, and enforceable trust mechanisms. Building with this blueprint in mind is now table stakes for any startup targeting regulated B2B markets with agentic solutions.
Microsoft's framework underscores a critical shift in the enterprise AI conversation, moving beyond model capabilities to the operational realities of deployment in high-stakes environments. The emphasis on engineering trust mirrors concerns from financial regulators and CIOs about the 'accountability gap' of autonomous systems. This blueprint effectively sets a standard for the non-negotiable features required for AI agents to handle financial instruments and critical infrastructure, shaping the product roadmaps for the entire agentic security and governance market.
As we watch payment networks like Visa, Mastercard, and Experian roll out the agent trust solutions we've been tracking (Trusted Agent Protocol, Verifiable Intent, Agent Trust), a critical architectural debate is emerging. In an article on Thursday, decentralized identity provider Concordium argues that building these solutions at the payment layer is a mistake. They contend that making identity a mere 'input' to a payment system, rather than a foundational, protocol-level primitive, compromises portability and creates vendor lock-in. The counter-argument is that identity should be a portable, decentralized verifier that can be used across any network, not just within a specific payment ecosystem.
Why it matters
This debate defines the battle for the core of the agentic economy's trust layer. The outcome determines whether agent identity will be controlled by centralized payment providers or exist as an open, interoperable standard. For builders, this is a crucial strategic consideration. Aligning with a payment-layer solution offers immediate access to established networks, but a protocol-level identity offers long-term flexibility and avoids being locked into a single ecosystem's rules and fees. The distinction is fundamental to the design of truly autonomous and verifiable agents.
The article from Concordium highlights a philosophical and technical split in how to build trust for AI agents. Payment networks are taking a pragmatic approach, integrating identity into existing, trusted rails to speed up adoption and solve immediate commercial needs. Conversely, the decentralized approach prioritizes open standards and user-centric control, arguing this is essential for a truly open and competitive agentic ecosystem. The tension reflects a classic trade-off between the convenience of centralized platforms and the principles of decentralized infrastructure.
In a Thursday analysis, Jeff Highman, CTO of identity firm Trua, argues that the core security challenge of agentic AI is establishing 'verifiable intent.' As agents execute transactions without direct human intervention, the digital infrastructure built on the assumption of human presence is no longer sufficient. Highman proposes a new trust architecture is needed to anchor agent delegation to a verified human identity, define clear and enforceable rules for agent authority, and enable continuous accountability through risk monitoring.
Why it matters
This analysis moves the agent trust conversation from 'can we trust the agent?' to 'can we prove the human's intent behind the agent's action?' This reframing is critical for any B2B or commercial context. It's not enough for an agent to be capable; its actions must be legally and financially attributable to an authorized principal. For founders, this means the most valuable products won't be the agents themselves, but the identity and delegation systems that make their actions defensible. The ability to produce an immutable, cryptographic record of who authorized what is the key to unlocking high-value agentic commerce.
Highman's argument pinpoints the legal and operational vulnerability in current agentic systems: dispute resolution. Without a robust system for proving intent, any transaction an agent makes is potentially deniable. This creates unacceptable risk for merchants and financial institutions. The proposed solution—a combination of strong identity, scoped delegation, and continuous monitoring—provides a comprehensive framework for building systems that are not only powerful but also accountable and insurable.
Building on Visa's recent agentic commerce partnerships—including its push to embed tokenized transactions into OpenAI's platforms—blockchain infrastructure firm Alchemy, in partnership with Visa Intelligent Commerce, launched AgentCard on Thursday. The platform provides a unified payments and identity stack for AI agents, offering a complete toolkit for conducting online commerce via a single API. This includes a Visa payment token, a dedicated email address and phone number, and a crypto wallet, enabling AI agents to make online purchases on behalf of users with their own verifiable credentials.
Why it matters
This is a critical piece of production infrastructure for agentic commerce, moving beyond pilots to a commercially available product. By bundling payment credentials with a persistent identity layer, AgentCard addresses the practical needs of agents operating in the wild. For builders, this provides a tangible toolset for enabling transactional capabilities in their AI applications. It represents a major step toward a world where agents are not just informational tools but first-class economic actors with their own wallets and credentials.
The collaboration between a crypto-native infrastructure company like Alchemy and a global payment giant like Visa signals a convergence of Web3 and traditional finance to build the rails for the machine economy. The platform is designed to support both traditional card payments and emerging agent payment rails, including crypto, acknowledging the fragmented landscape and positioning itself as a bridge between these worlds.
At the Agentic Finance Summit on Thursday, co-hosted by the EEA and Microsoft, industry leaders argued that the rise of autonomous agents necessitates a shift towards trust-minimized, open on-chain standards for settling high-velocity micro-transactions. Speakers highlighted that agents are disrupting traditional B2B commercial models by programmatically optimizing for the lowest price, requiring new infrastructure for execution and settlement that bypasses slower, human-centric payment systems.
Why it matters
This summit's consensus points to a future where machine-to-machine commerce operates on crypto rails, not because of ideological purity, but for pure performance and cost reasons. For founders, this is a strong signal that the infrastructure for agentic finance is a massive opportunity. The core challenge is building services that enable seamless, auditable, and secure on-chain interactions for autonomous agents. This trend also poses an existential threat to legacy SaaS models, which are not built for high-velocity, programmatic consumption by non-human customers.
The key takeaway from the summit is that agentic AI forces a move to programmatic money and settlement. Traditional financial systems are too slow and expensive for the micro-transaction economy that agents will create. The discussion centered on the need for lightweight, open standards that can handle immense volume, a demand that public blockchains are uniquely positioned to meet, provided they can offer sufficient privacy and scalability.
On Friday, digital identity firm Affinidi and travel tech provider CardInfoLink announced the deployment of Agent Gateway, an independent trust and governance layer for AI agents. The system is now in production on Agenzo, CardInfoLink's agentic commerce platform for travel and hospitality. This marks the first commercial deployment in Asia of AI agents operating with a framework that creates cryptographically verifiable transaction records, establishing clear accountability.
Why it matters
This deployment moves the discussion of agent governance from theory to a live, commercial application in a high-volume industry. It directly addresses the critical trust gap that has hindered enterprise adoption of autonomous agents. By creating an auditable, verifiable record of agent actions, the system mitigates fraud risk and ensures compliance, providing a concrete model for how to securely integrate agentic AI into commercial B2B workflows.
The Agent Gateway uses decentralized identifiers (DIDs) and verifiable credentials (VCs) to create what the companies call a 'Trust Assurance Framework.' Every action taken by an agent is signed and logged, creating an immutable audit trail. This is particularly important in the travel sector, where complex bookings and payments involve multiple parties and a high potential for error or fraud.
An analysis published Thursday argues that decentralized identity (DID), using open standards like the W3C DID specification and Hyperledger Indy, is the only viable foundation for securing agentic AI. The piece posits that AI agents require cryptographically verifiable 'passports' to ensure every autonomous action they take is authorized, auditable, and, crucially, revocable. This addresses the 'accountability gap' that currently plagues enterprise AI deployments.
Why it matters
This analysis provides a clear architectural thesis for building trustworthy AI agents. For founders, it's a playbook: leverage open DID standards to create a robust identity layer for agents. This allows for 'credentialed reasoning,' where an agent's authority is tied to verifiable credentials, and enables automated identity revocation to prevent 'agentic drift' or unauthorized actions. In a world of autonomous software, proving an agent *was* authorized but *is not anymore* is a critical security function that DIDs are uniquely suited to provide.
The author contends that traditional, centralized identity systems are insufficient for a multi-agent world where software from different organizations must interact securely. A decentralized approach, where identity is self-sovereign and portable, is necessary for creating a truly interoperable and secure agentic ecosystem. The piece emphasizes that without this foundational layer, enterprises will be unable to safely grant agents the autonomy needed to perform high-stakes tasks.
Adding legacy-tech validation to the flurry of agentic governance launches and infrastructure funding rounds we've been tracking (such as Geordie AI's recent $30M Series A), Cisco announced on Thursday its acquisition of WideField Security, a specialist in AI agent security. The move is part of a broader strategy to build an AI-native identity security stack, alongside recent acquisitions of Astrix Security and Galileo. The stated goal is to address the growing 'accountability gap' by developing continuous session intelligence that can bridge the gap between initial authentication and ongoing accountability for autonomous agent actions.
Why it matters
This acquisition by a major infrastructure player like Cisco validates the agentic trust market and signals a focus on a specific, unsolved problem: post-authentication governance. Traditional IAM systems know who an agent is at login, but they go blind once the session starts. Cisco is betting that the real security challenge is tracking and verifying agent behavior throughout its lifecycle. For founders, this highlights the need for solutions that provide continuous, context-aware monitoring, as this is where enterprises see the most significant risk.
WideField's technology reportedly focuses on creating a detailed, real-time 'behavioral graph' for each agent session. This allows security teams to detect deviations from expected behavior and enforce policies dynamically, rather than relying on static, pre-configured permissions. The acquisition suggests the market is moving from simple access control to more sophisticated, intelligence-driven governance for non-human identities.
On Thursday, Google introduced Agentic Resource Discovery (ARD), an open specification designed to allow AI agents to securely publish, discover, and verify AI capabilities across the web. ARD enables agents to locate and connect to tools, skills, and even other agents from different organizations and platforms. Trust is established through domain ownership and verifiable metadata, creating a decentralized registry for agent functions.
Why it matters
ARD addresses the critical interoperability and fragmentation problem in the agentic AI landscape. By providing a standardized 'yellow pages' for agents, it allows them to operate more reliably and accountably across diverse ecosystems. For builders, this is a key piece of infrastructure. Instead of building bespoke integrations for every tool, they can use ARD to make their agents' capabilities discoverable and consumable by others, fostering a more open and composable agent economy. The verification mechanism is key, as it helps prevent agent spoofing and ensures an agent is connecting to the intended, authentic service.
The specification is being positioned as a foundational layer for a more open agent ecosystem, akin to how web standards enabled the growth of the internet. By tying verification to domain ownership, Google is leveraging existing web trust infrastructure. This could accelerate adoption but may also give an advantage to established players with significant domain assets.
Corroborating the recent data we covered showing AI spam is forcing a return to human-led outreach, new research from deliverability platform Folderly finds the flood of AI-generated content is paradoxically harming outbound sales efforts. The study released Thursday found that while 70% of B2B sales professionals now use AI to help write outbound emails, 79% report that prospects never receive their messages. The data suggests that as AI increases email volume, it degrades the quality signals that major providers like Gmail and Microsoft use for filtering, leading to more aggressive and silent deliverability failures.
Why it matters
This quantifies a structural problem for any GTM strategy relying on cold outreach: the channel is breaking under the weight of AI-generated spam. It reinforces our previous coverage that it's no longer enough to just send emails; teams must now treat deliverability as a continuous infrastructure challenge. For founders, this means investing in technical monitoring and sender reputation management is now a prerequisite for outbound success. Simply using AI to scale a broken playbook will only result in messages landing in spam folders, wasting sales efforts entirely.
The report indicates a classic 'tragedy of the commons' scenario. The ease of generating email copy with AI has led to a deluge of low-quality, generic messages. In response, inbox providers have tightened their filters, penalizing not just the spammers but also legitimate senders who fail to maintain pristine sender reputations. The solution, according to the report, is a renewed focus on list quality, personalization, and technical deliverability fundamentals.
A Thursday report from Sage Marketing on the state of B2B tech marketing in 2026 highlights a major divergence between companies building 'human-first' marketing engines and those sticking to outdated playbooks. Key trends identified include the collapse of attention for generic content, the failure of high-volume/low-quality AI content, the rise of community-led growth, and the increasing importance of B2B influencers. The report argues that high-converting outbound now relies on warm social signals and highly personalized, low-volume outreach.
Why it matters
This report offers a clear GTM framework for early-stage founders: stop wasting resources on generic content and mass cold outreach. The structural shift is that distribution advantage now comes from owned audiences, genuine points of view, and leveraging key people as assets for the brand. The playbook is to build credibility in communities and use warm social engagement as the primary trigger for one-to-one outreach, a direct counter-narrative to the volume-based tactics that are failing.
The analysis points to a crisis in traditional marketing attribution, as much of the buyer's journey now happens in 'dark social' channels like private communities. This forces a move away from easily trackable but ineffective metrics toward a focus on building genuine brand affinity and trust. The most successful companies, according to the report, are those that invest in making their people—from founders to experts—the face of the brand.
While we've been tracking Ethereum's 'Glamsterdam' upgrade nearing completion and Wall Street's growing acceptance of the network as production-grade infrastructure, Trent Van Epps, a former member of the Ethereum Foundation, issued a stark warning on Friday that Ethereum's core protocol development is facing a severe funding crisis and could run out of money within 3 to 9 months. The alert follows the departure of several senior researchers from the Ethereum Foundation.
Why it matters
This is a critical threat to the long-term health of the Ethereum protocol. A funding shortfall could stall future upgrades, slow down innovation, and compromise network security and stability at the very moment institutional finance is beginning to treat it as production infrastructure. For builders, this introduces significant platform risk. The crisis highlights the precarious nature of funding public goods in a decentralized ecosystem and could force the community to confront difficult questions about sustainable, long-term financing for core infrastructure maintenance.
The warning from a well-respected former contributor is being taken seriously within the Ethereum community. It raises questions about the role of the Ethereum Foundation, the effectiveness of current funding mechanisms like grants DAOs, and whether a more formalized, protocol-funded system is needed to ensure the continued development of the base layer. The timing is particularly sensitive, as any disruption could undermine the confidence of the institutional players currently integrating with the network.
An analysis by Robert Moment published Thursday argues that product-market fit (PMF) is no longer a permanent state but a perishable asset, especially in the AI era. The argument is that AI tools are compressing differentiation by making features easier to replicate, while also reducing buyer urgency. Moment introduces a seven-point framework called AIPROOF™ to help founders diagnose PMF decay before it shows up as declining revenue, noting that a common early signal is a stall in demo-to-close rates, which is often misdiagnosed as a sales problem.
Why it matters
This reframes PMF from a one-time goal to a state that requires continuous defense and validation. For founders, this is a critical strategic insight: you can't just find PMF and then scale; you must actively monitor and rebuild it. The framework provides a structural analysis for detecting the erosion of your market position early. This is a counterintuitive take on a foundational startup concept, offering a more dynamic and realistic model for navigating a rapidly changing competitive landscape.
The AIPROOF™ system suggests founders monitor seven areas: Audience refinement, Ideal customer profile validation, Pain point intensity, Revenue model alignment, Offer differentiation, Onboarding experience, and Fulfillment consistency. According to the author, a weakening in any of these areas can signal that a company's initial PMF is degrading and requires a strategic response to rebuild its moat.
In a significant blow to the federal-supremacy argument we've been tracking closely across multiple state lawsuits, a Michigan judge denied Polymarket's request for a preliminary injunction against state enforcement on Wednesday. The judge ruled that Polymarket's sports-related event contracts—a category we previously noted accounts for up to 80% of volume on rival Kalshi—are not 'swaps' under the federal Commodity Exchange Act. Instead, the judge determined these contracts fall under state gambling laws, leaving Polymarket vulnerable to state-level prosecution and reinforcing a fragmented regulatory landscape for prediction markets in the US.
Why it matters
This ruling directly undermines the prediction market industry's attempt to use CFTC approval as a shield against state gaming commissions. It sets a precedent for other states to assert their own gambling regulations over specific types of contracts, particularly those related to sports. This creates major operational uncertainty and compliance costs for platforms like Polymarket, forcing them to navigate a patchwork of state laws rather than a single federal framework, and could bifurcate the market between financial/political contracts and sports-related ones.
Polymarket had argued that its CFTC approval should preempt state laws. However, the judge found that the specific contracts in question did not meet the definition of a commodity swap and therefore were not subject to federal jurisdiction. This legal battle is one of many, with Kentucky also suing Polymarket and Kalshi, and a coordinated crackdown on unlicensed platforms underway in Europe.
Putting a structural lens on the data we've been tracking—where 65% to 75% of recent venture capital has concentrated into just five AI companies—a Friday analysis argues that the venture capital industry is now fundamentally structured to shut ordinary Americans out of the AI wave. The traditional path of a startup going public via an IPO to give public investors access to its growth has been replaced by a private market system. Mega-rounds for companies like OpenAI, Anthropic, and SpaceX allow them to stay private longer, with large funds front-running the returns that used to be captured in public markets.
Why it matters
This piece documents the structural consequences of the extreme capital concentration we've been monitoring. It creates a 'barbell' market: a handful of AI companies attract enormous valuations, while most other startups face a tougher fundraising environment. It also means the exit landscape has changed; the IPO is no longer the default goal, and strategic positioning for acquisition or staying private longer becomes more critical. This pricing distortion shapes what gets built and who gets funded.
The author contends that this shift is driven by a combination of factors, including increasing regulatory burdens that make going public less attractive and the sheer amount of capital that large institutional investors need to deploy. This creates a self-reinforcing cycle where the biggest companies attract the most capital, further cementing their market dominance and making it harder for smaller competitors to emerge.
Ad-tech firm PubMatic launched its Creator Marketplace on Thursday, the first programmatic auction specifically designed to connect independent creator media companies with advertising demand on connected TV (CTV). The platform allows creators with premium video content to access programmatic advertising budgets, with outdoor lifestyle brand MeatEater announced as the inaugural launch partner.
Why it matters
This is a major piece of new infrastructure for the creator economy, providing a new monetization and distribution mechanic beyond direct sponsorships or walled-garden platforms like YouTube. It allows creators to tap into the large, performance-driven budgets of programmatic advertising, treating their content as premium media inventory. For operators and writers, this signals the increasing professionalization of the space and creates a new pathway for building sustainable media businesses.
The marketplace is designed to serve both creators and advertisers. For creators, it offers a way to generate revenue from their CTV content at scale. For advertisers, it provides access to niche, high-engagement audiences that are increasingly hard to reach through traditional linear TV. The inclusion of 'agentic' demand in the announcement also points to a future where AI agents could programmatically purchase ad inventory on behalf of brands.
The Hashgraph Group and Truesense announced on Friday the filing of a European patent for a 'Continuous Identity Trust Infrastructure' (CITI). The system is designed to verify an individual's physical presence at a specific place and time without revealing personal data. It combines ultra-wideband sensing for location, decentralized digital identity (DID), and zero-knowledge proofs (ZKPs) to create a privacy-preserving audit trail.
Why it matters
This is a significant development in bridging the digital and physical worlds with verifiable credentials. The ability to prove 'proof of presence' without compromising privacy has broad applications in high-trust environments, from securing financial transactions to verifying supply chain logistics or ensuring compliance in regulated industries. For builders, this provides a new primitive for trust and verification, enabling use cases that require attestation of real-world actions while respecting user privacy.
The CITI system aims to address the stringent requirements of European digital identity regulations. By using ZKPs, a user can generate a proof that they were at a certain location at a certain time without ever disclosing the location itself to the verifier, unless explicitly required for an audit. This 'selective disclosure' capability is key to its utility in privacy-critical applications.
'Pub tokens' are emerging as a primary catalyst for the Decentralized Science (DeSci) movement, according to a Bitget report from Friday. These tokens are used to tokenize scientific contributions, such as research papers and peer reviews, moving the entire academic publishing lifecycle onto the blockchain. The goal is to address long-standing issues in traditional publishing, such as high costs, slow review processes, and the 'reproducibility crisis,' by creating a system of direct incentives for researchers and reviewers.
Why it matters
This represents a fundamental rethinking of how scientific research is funded, validated, and distributed. By creating liquid, on-chain assets from research contributions, the DeSci movement offers a potential solution to the funding gaps and misaligned incentives that plague traditional science. This model could accelerate innovation by making it easier for novel or unconventional research to secure funding and by creating a more transparent and efficient peer-review process.
The report highlights the growing demand for open-access research and the maturation of cross-chain protocols that allow for the fractionalization of research into tradable assets. This shift could democratize science funding and create new economic models for researchers, but it also raises new questions about valuation, speculation, and the potential for market dynamics to influence scientific inquiry.
An article from Underthrow, published Thursday, is reviving the concept of 'subscription government' and 'panarchy'—a system where individuals can freely choose among competing governance providers for services like law, welfare, and education. Inspired by Chris Rufer's 'Philosophy of Human Respect,' the model envisions a society based on voluntary cooperation where governance associations must persuade citizens to subscribe, fostering accountability and diversity in social organization.
Why it matters
This is a direct exploration of the experimental governance models that underpin the philosophy of many intentional communities and network states. It moves beyond the idea of a single, monolithic government to a competitive marketplace of governance services. For those experimenting with new community structures, this provides a theoretical framework for how to design systems of collective action and service provision that are based on consent and choice, rather than territorial monopoly.
The article presents this model as a solution to the perceived failures of modern nation-states, arguing that competition would lead to more efficient and responsive governance. Critics of panarchy, however, often raise concerns about the potential for inequality, the challenge of providing universal public goods, and the difficulty of managing disputes between members of different governance associations.
The Agentic Trust Stack Solidifies and Debates its Architecture A wave of new products and partnerships (Affinidi/CardInfoLink, Alchemy/Visa, Cisco, Microsoft, Google) are creating a production-ready trust layer for AI agents. However, a key architectural debate is emerging: payment networks are embedding identity at the transaction layer, while decentralized proponents argue for a foundational, protocol-level approach to ensure portability and neutrality.
GTM Shifts to Signal-Based Outreach and Distribution-Led Growth Multiple analyses this week confirm that traditional B2B outreach is failing. The new playbook prioritizes signal-based outbound, founder-led content, and building distribution power as the primary moat, as AI commoditizes product features. The focus is shifting from volume to precision and from lead generation to pipeline quality.
Prediction Markets Face a Global Regulatory Pincer Movement Regulators are closing in on prediction markets from multiple angles. In the U.S., a Michigan court denied Polymarket an injunction, Kentucky filed suit, and the House opened an insider trading probe. Simultaneously, nine European regulators launched a coordinated crackdown, and the Netherlands is fining Polymarket for a delayed exit.
Ethereum's Institutional Integration Deepens Amidst Protocol Stress Wall Street's adoption of Ethereum for tokenization is moving from pilots to production. At the same time, the protocol is facing internal challenges, with a former contributor warning of a core development funding crisis within months. This highlights the tension between growing external reliance and the sustainability of its core open-source maintenance.
The Creator Economy Institutionalizes with New Infrastructure The creator economy is maturing with the launch of new infrastructure like PubMatic's Creator Marketplace and Instagram's 'Series' tab. The focus is shifting from individual influencers to building programmatic and structural support for monetization, distribution, and business operations, turning creator-led media into a more established business discipline.
What to Expect
2026-07-10—Deadline for public consultation on Malta's proposal to integrate DeFi and DAOs into the EU's MiCA framework.
2026-09-02—Identity Week America 2026 begins in Washington D.C., with a focus on decentralized identity, non-human identities, and agentic AI.
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