Today on The Distribution Desk: thirty-nine states have petitioned the Supreme Court to dismantle the federal preemption shield protecting prediction markets, while Google Cloud introduces protocol-native execution gateways for enterprise AI agents.
Following Microsoft's release of the Agent Governance Toolkit we tracked yesterday, Google introduced the Gemini Enterprise Agent Platform alongside a preview of its Agent Gateway at Cloud Next '26 on Thursday, October 8. Built on Envoy and Kubernetes, the protocol-native gateway parses Model Context Protocol (MCP) and Agent-to-Agent (A2A) payloads to enforce Role-Based Access Control (RBAC) during mTLS handshakes using SPIFFE workload identities. Paired with Google's Model Armor, the system extracts requested tool names and inspects parameters to intercept prompt injections and tool poisoning attempts before execution.
Why it matters
Moving agent governance down to the transport proxy layer fundamentally changes how enterprise security teams mitigate execution risks. Rather than relying on non-deterministic LLM alignment or prompt wrappers, inspecting MCP messages directly inside the proxy gateway allows hard isolation of tool invocations. This architecture sets a precedent for how B2B platforms will gate high-privilege sub-agent execution across corporate perimeters.
Google Cloud engineers contend that protocol-native parsing inside proxy gateways is the only reliable method to prevent model-level prompt injections from compromising internal APIs. Conversely, open-source maintainers note that wrapping dynamic agent interactions in rigid SPIFFE RBAC rules risks restricting adaptive agent planning and creating heavy gateway configuration overhead.
Security analyses published by Palo Alto Networks on Thursday, October 8, provide new context on the 109-to-1 ratio of non-human to human enterprise identities we cited last month. The updated report specifies that AI agents now account for 79 of those 109 credentials. Following recent high-profile breaches—including state-sponsored attacks leveraging Claude Code and an autonomous breach at Hugging Face—the analyses confirm that static service accounts fail when dynamic sub-agents escalate permissions mid-session. The report calls for mandatory short-lived runtime credentials and isolated behavioral monitoring.
Why it matters
The exponential proliferation of autonomous agents has turned legacy enterprise identity and access management into an operational vulnerability. Because AI sub-agents routinely generate ephemeral tasks and request elevated privileges at runtime, static API keys and standing service accounts create massive persistent attack surfaces. Enterprise security budgets are consequently shifting toward real-time identity brokers capable of issuing self-destructing access tokens tied to specific tool invocations.
Enterprise CISOs argue that mandatory short-lived credentials and kernel-level behavior monitoring are non-negotiable to prevent agentic privilege escalation. Cloud infrastructure teams warn that enforcing continuous mTLS handshakes and token revocation checks at high concurrency introduces severe latency bottlenecks into real-time sub-agent execution.
On Thursday, October 8, billing startup Paid launched a specialized platform for developers building autonomous AI agents to manage margins, configure outcome-based pricing, and issue customer value receipts. The system tracks every sub-agent action, API tool call, and token cost in real-time, translating raw execution telemetry into human-readable business metrics like cost savings, time saved, and revenue generated. The platform includes a hardened billing engine that executes credit card billing alongside cryptographic value receipts.
Why it matters
As autonomous AI agents shift from chat interfaces to programmatic action executors, traditional per-seat SaaS pricing models collapse. Developer margins are highly sensitive to unconstrained sub-agent tool calls and LLM inference loops. Providing real-time margin tracking alongside verifiable value receipts gives enterprise software vendors the billing infrastructure necessary to charge per task or outcome safely.
Paid's founders contend that transparent, tool-call-level value receipts are required to convince enterprise CFOs to transition from predictable per-seat SaaS software to variable outcome-based agent billing. Skeptical RevOps executives warn that calculating subjective metrics like 'risk avoided' or 'time saved' on billing receipts invites customer invoicing disputes.
UK advertising startup pubX announced a $5 million Series A round on Tuesday, October 6, led by Chicago Ventures, while concurrently acquiring digital governance firm Compliant. Led by CEO Andrew Mole, pubX builds buyer and seller AI agents that transact media buys directly via the open Ad Context Protocol (AdCP), entirely bypassing legacy demand-side (DSP) and supply-side (SSP) platforms. The acquisition embeds Compliant's data integrity verification signals directly into pubX's agentic negotiation layer.
Why it matters
Traditional ad-tech intermediaries extract heavy fee take-rates while routing programmatic impressions through opaque auction hops. Replacing legacy DSP/SSP infrastructure with direct agent-to-agent negotiation over open protocols like AdCP drastically cuts transaction overhead for publishers and media buyers. Embedding third-party data governance directly into the agent protocol ensures automated media buying satisfies corporate compliance rules.
pubX leadership maintains that legacy programmatic ad stacks are structurally incapable of handling split-second agentic trade negotiations without excessive fee extraction. Incumbent ad-tech executives assert that established DSPs provide deep liquidity networks and fraud protection that open agent protocols cannot match at scale.
Building on Forrester's retirement of the MQL metric we tracked yesterday, GTM guides published Thursday detail an industry-wide pivot toward 'Inbound-Led Outbound' (ILO). Prompted by strict Google and Yahoo 0.3% spam-rate ceilings, revenue teams are configuring hybrid pipelines triggered by first-party intent signals—such as anonymous pricing-page revisits, competitor comparison views, and review site research de-anonymized via visitor identification APIs. These pipelines route high-intent accounts into targeted sequences, prioritizing qualified replies per 1,000 sends over raw activity volume.
Why it matters
Brute-force outbound sequence automation has hit an economic ceiling due to mailbox provider enforcement and buyer fatigue. Modern GTM strategy requires treating prospect discovery as a real-time signal processing problem rather than a copywriting exercise. Revenue teams that anchor outbound on de-anonymized web traffic and first-party engagement protect their primary domain health while securing significantly higher meeting conversion rates.
RevOps strategists argue that replacing volume sequencing with intent-driven triggers is the only way to preserve domain deliverability and reach actual buying committees. Traditional sales leaders maintain that relying strictly on inbound intent signals narrows total TAM reach and misses cold, uneducated target accounts that require active market creation.
An operational breakdown published on Wednesday, October 7, detailed SaaStr AI's dual outbound architecture. SaaStr deploys four commercial AI SDR tools (Monaco, Artisan, Agentforce, Qualified) to handle 90% of cold top-of-funnel outreach. For named enterprise accounts and renewals, the team constructed an internal custom prospecting agent integrated with first-party Salesforce, Bizzabo, WordPress, and podcast consumption logs. The custom agent generates context-rich renewal decks via the Gamma API, enforcing mandatory human review before sending.
Why it matters
This dual setup provides a pragmatic blueprint for structuring sales technology stacks in the AI era. While off-the-shelf AI SDRs can process generic cold volume, they fail on high-value accounts because they lack access to deep, proprietary CRM engagement histories. Early-stage founders and RevOps leaders must separate generic list prospecting from custom internal agents that leverage proprietary data assets under human oversight.
SaaStr GTM engineers emphasize that custom internal agents accessing historical event and content data yield 4x higher meeting conversion rates than vendor SDRs. Third-party sales software vendors argue that building and maintaining bespoke internal agents introduces unnecessary engineering overhead compared to rapidly improving commercial GTM platforms.
Speaking on Thursday, October 8, StarkWare CEO Eli Ben-Sasson announced that Starknet is evaluating a strategic transition from an Ethereum Layer-2 rollup to an independent Layer-1 blockchain. The proposed architectural move is driven by a desire to independently control its cryptographic migration timeline against AI and quantum decryption risks. Utilizing ZK-STARKs with cryptographic agility, Starknet is targeting a post-quantum security deployment in 2027, cutting ahead of Ethereum mainnet's planned 2029 quantum-resistance roadmap.
Why it matters
Starknet's potential departure from the Ethereum rollup stack exposes a fundamental flaw in modular blockchain architecture: execution layers seeking rapid security updates are constrained by base-layer governance timelines. If scaling networks begin decoupling from Ethereum to enforce their own cryptographic parameters, the economic security and shared liquidity of the Layer-2 ecosystem will fragment. This decision highlights the trade-off between inherited L1 settlement trust and execution autonomy.
StarkWare leadership argues that sovereign control over protocol upgrades is required to deploy lattice-based and hash-based signatures before AI-accelerated cryptanalysis threatens user wallets. Ethereum core researchers contend that breaking L2 settlement alignment damages ecosystem composability and creates unvetted security assumptions on an isolated base layer.
On Thursday, October 8, Ethereum Name Service (ENS) co-founder Nick Johnson exercised his personal token holdings—representing approximately 50% of the active voting supply—to single-handedly block the renewal of the ENS Security Council. Johnson executed the veto to prevent unchecked executive centralization and force a structural overhaul of the DAO's $350 million treasury governance rules. The action leaves the protocol facing a tight deadline to draft a compromise framework before current security council multisig mandates expire.
Why it matters
The ENS standoff exposes the systemic vulnerability of naive token-weighted governance in major decentralized infrastructure protocols. When a single founder or early insider commands enough voting weight to unilaterally halt core administrative functions, the protocol's claim to decentralized neutrality dissolves. This governance failure highlights the urgent need for DAOs to transition toward bicameral voting systems and reputational checks.
Nick Johnson maintains that blocking the council vote was a necessary emergency measure to protect the $350 million treasury from aggressive multisig spending expansions. Community delegates and security committee members argue that exercising unilateral token dominance destabilizes operational security and sets a dangerous precedent for protocol governance.
On Wednesday, October 7, Europol published two security reports advising law enforcement agencies and cryptocurrency custodians to implement crypto-agility against post-quantum threats. The guidance highlights two distinct risk profiles: wallet public-key signature exposure and 'harvest now, decrypt later' (HNDL) passive interception affecting stored TLS and SSH traffic. The reports note that while hybrid ML-KEM key exchanges are already default in OpenSSH 10 and OpenSSL 3.5, financial institutions must immediately audit legacy endpoints.
Why it matters
Europol's formal intervention converts post-quantum migration from an abstract research discussion into an immediate operational compliance requirement for digital asset custodians. Because adversary state actors are actively recording encrypted network traffic to decrypt once fault-tolerant quantum hardware arrives, institutions handling financial data must upgrade transit layer encryption immediately. This accelerates the adoption of hybrid post-quantum key exchange standards across Web3 infrastructure.
Europol security directors urge immediate audits of legacy encrypted data stores to prevent catastrophic retroactive decryption of institutional records. Web3 infrastructure engineers argue that wallet signature schemes are adequately protected in the near term, warning against hasty wallet migrations that could introduce unvetted smart contract bugs.
On Thursday, October 8, institution-focused startup Etherealize announced a $40 million Series A funding round alongside a grant from Vitalik Buterin and the Ethereum Foundation. CEO Vivek Raman issued a public warning against the rise of permissioned enterprise consortium chains—such as Canton Network, Circle ARC, and Stripe's Tempo—describing them as a 'race to the bottom' that recreates siloed financial legacy systems. Etherealize is building middleware enabling institutional banks to deploy compliant, privacy-preserving asset pools directly on public Ethereum mainnet.
Why it matters
A critical battle is unfolding between closed, corporate-controlled permissioned ledgers and public, permissionless base layers for institutional asset tokenization. Private consortium chains appeal to risk-averse bank compliance officers but destroy global liquidity composability by fragmenting assets across isolated networks. Convincing institutional capital to settle on public Ethereum requires robust zero-knowledge privacy layers that preserve institutional compliance without sacrificing open interoperability.
Etherealize leadership argues that walled-garden consortium networks ultimately fail because institutions will demand access to public mainnet liquidity and decentralized cross-margining. Enterprise consortium operators contend that permissioned ledgers are necessary to satisfy strict banking secrecy laws and regulatory settlement finality mandates.
Yesterday we covered the cease-and-desist orders issued by Ohio regulators against Kalshi and Polymarket; today, the legal battle escalated as Ohio led a coalition of 39 states asking the U.S. Supreme Court to hear New Jersey's case against Kalshi. The petition argues that federal commodities law does not displace state sports-gambling authority, deepening the circuit split across the Third, Sixth, and Ninth Circuits. Simultaneously, the Cabazon Band filed an amicus brief asserting that federal event contract approvals infringe on tribal gaming sovereignty under IGRA, even as Kalshi negotiates a private round valuing the firm near $40 billion.
Why it matters
A Supreme Court review of Commodity Exchange Act preemption poses an existential threat to prediction market distribution in the United States. If the court upholds state gambling jurisdiction, operators will be forced to secure licenses across 50 separate state gaming boards, fragmenting national liquidity pools and imposing local wagering taxes. For platforms building institutional order books, this legal friction undermines the regulatory certainty required for public market listings.
State attorneys general argue that allowing federal commodities regulators to preempt local laws creates an illegal backdoor for unregulated sports betting and tax avoidance. Kalshi and industry trade groups maintain that uniform federal CFTC oversight is explicitly authorized by Congress to maintain transparent, nationwide risk-hedging venues.
While Polymarket navigates the state-level cease-and-desists and CFTC scrutiny we've been tracking, the platform unveiled Protocol V2 on Wednesday, October 7, replacing its legacy 2019 Gnosis Conditional Tokens Framework. The updated smart contract architecture introduces pUSD—a native 1:1 USDC-backed collateral standard—alongside upgradeable router contracts and an OracleAggregator integrating UMA and Chainlink feeds. Public contract testing runs through October 30 ahead of a planned November 2 mainnet launch for new markets, while existing open positions remain anchored to Protocol V1.
Why it matters
Upgrading core smart contract architecture allows Polymarket to retire legacy bridging code and prepare for multi-chain expansion beyond Polygon. Standardizing on pUSD native collateral streamlines execution speed and reduces third-party dependency during volatile event settlements. However, operating a dual-version exchange infrastructure while running multi-billion-dollar order books demands flawless execution to avoid oracle dispute failures.
Polymarket protocol architects state that Protocol V2's modular router and native pUSD collateral are essential to handle institutional transaction concurrency and multi-chain liquidity routing. DeFi security researchers caution that introducing upgradeable contracts and multi-oracle aggregators increases smart contract attack surfaces and centralizes administrative pause controls.
Following up on the Q3 venture data we tracked yesterday showing AI capturing 64% of the $159 billion deployed globally, new PitchBook-NVCA and Crunchbase reports detail extreme capital skewness. Just 27 companies raising mega-rounds of $1 billion or more absorbed $53 billion of that quarterly total. Year-to-date, U.S. venture deal value reached $515.8 billion, with AI representing 82.7% of that capital. Meanwhile, the public exit market remains frozen across 992 active unicorns valued at $5.7 trillion (updating the $5.34 trillion a16z estimate we noted earlier this week), driving secondary acquisition markdowns of up to 60% for non-AI SaaS scaleups.
Why it matters
This extreme capital skewness demonstrates that venture capital has ceased to function as a broad asset class for software innovation, morphing instead into a capital-intensive utility layer for frontier AI compute. Late-stage startups without foundational AI positioning face a prolonged liquidity freeze, as traditional IPO exits remain blocked and secondary buyers demand steep haircuts. For founders, this structural squeeze mandates pivoting to immediate unit-economic profitability rather than expecting growth-stage follow-on rounds.
Institutional LPs emphasize that record paper valuations across 992 paper unicorns are meaningless without realized cash distributions, forcing them to concentrate new fund commitments into top-tier incumbents. Growth investors counter that massive infrastructure check sizes reflect the genuine physical capital costs required to construct data centers and secure energy rights for next-generation models.
Yesterday we covered Authors First emerging from stealth with a $10 million Seed round; today, further details confirm their debut project is an adaptation of Conn Iggulden’s 'Genghis: Birth of an Empire.' The studio integrates generative production tools like Seedance 2.5 and Blender with veteran Hollywood talent, bypassing traditional distribution to sell the completed series directly to fans via Filmhub for $14.99.
Why it matters
Combining AI production pipelines with direct-to-consumer digital storefronts allows niche literary IP to bypass traditional Hollywood studio gatekeepers. By dramatically reducing physical shoot and visual effects costs, the model enables profitable screen adaptations for mid-tier book franchises with dedicated fanbases. For independent creators, this establishes a repeatable distribution template that retains IP ownership and creative control.
Authors First founders contend that low-cost AI production tools finally give authors the leverage to demand final-cut authority and bypass predatory studio options. Traditional film executives argue that direct-to-consumer releases without major theatrical or streaming marketing budgets will struggle to break out beyond existing book reader lists.
Startup marketplace Cherub announced a $4.5 million pre-seed round on Wednesday, October 7, while releasing a standardized legal framework called the 'Creator Equity Agreement.' Designed alongside creator-investors including Maggie Sellers Reum and Valeria Lipovetsky, the contract standardizes advisory sweat-equity grants—typically 0.25% to 0.5% vesting over four years—to replace informal promotion agreements while ensuring compliance with FTC disclosure rules and SEC accredited investor thresholds.
Why it matters
As distribution leverage shifts from paid ad networks to influential founder-creators, early-stage startups are increasingly offering cap table equity in exchange for ongoing promotional distribution. However, informal sweat-equity deals frequently break down over unclear deliverable expectations and regulatory non-compliance. Standardizing legal agreements for creator advisory stakes professionalizes this channel, turning creator distribution into an institutionalized cap table asset class.
Cherub founders assert that standardized vesting contracts protect founders from ghosting creators while giving digital talent defensible equity ownership rather than short-term sponsorship fees. Early-stage venture lawyers caution that granting cap table equity to non-accredited creators creates messy cap tables and potential securities compliance liabilities during follow-on institutional rounds.
OpenMatter Network and Hashgraph Online (HOL) released a draft specification on Wednesday, October 7, titled 'Zero-Knowledge Boundary Compliance for Autonomous Agents.' Developed within the HOL AI Privacy & Security subcommittee alongside Vera Anchor, the standard outlines a cryptographic framework allowing autonomous AI agents to generate ZK proofs confirming adherence to corporate operational policies without revealing internal database records, system prompts, or customer data to external auditors.
Why it matters
As autonomous agents execute multi-step workflows across organizational perimeters, traditional API log audits become severe privacy liabilities. Enforcing policy adherence through zero-knowledge proofs enables enterprise verification without data leakage, creating a viable compliance mechanism for cross-company agent workflows. For software builders, implementing ZK boundary proofs provides a defensible trust primitive when deploying agents into regulated financial or healthcare environments.
OpenMatter standard co-authors assert that ZK boundary proofs offer the only mathematically verifiable way to enforce enterprise safety policies without exposing proprietary business logic. Independent security auditors note that zero-knowledge verification adds non-trivial computational overhead to split-second agent execution, potentially limiting its use to high-value transaction settlements.
The Cardano Foundation announced on Thursday, October 8, that it has officially spun out digital identity firm Veridian, issuing company shares as tokenized ledger securities under Switzerland's DLT Act via Cardano's CIP-0113 standard. Led by CEO Thomas A. Mayfield, Veridian develops decentralized identity infrastructure for governments and AI payment agents, having fully mapped Utah's state-endorsed digital identity (SEDI) framework while integrating open KERI and ACDC credential standards.
Why it matters
Veridian's spin-out demonstrates how decentralized identity stack development is shifting toward dual-purpose compliance architectures that verify both human citizens and autonomous software agents. By anchoring programmable credentials to Swiss regulatory frameworks, the project attempts to bridge public state identity requirements with machine-to-machine commerce. This hybrid model offers a blueprint for issuing legally binding credentials to autonomous sub-agents.
Veridian leadership asserts that binding verifiable credentials to open standards like KERI prevents central authority lock-in while satisfying strict state digital identity mandates. Identity security critics contend that deploying complex blockchain token standards for routine credential verification introduces unnecessary protocol dependencies compared to W3C-standard decentralized identifiers.
On Wednesday, October 7, the Chan Zuckerberg Biohub expanded its Virtual Biology Initiative into a $1.8 billion public-private coalition alongside the Department of Energy, the NIH, Google DeepMind, Meta, and Isomorphic Labs. The initiative combines $500 million in DOE exascale computing resources, $500 million in aligned NIH datasets, and $300 million from corporate partners to build standardized, AI-ready biological training data. The coalition aims to construct a predictive 'virtual cell' simulator within five years, though commercial financial backers secure a one-year exclusive access embargo before datasets enter the public domain.
Why it matters
This massive capital alignment marks a shift in computational biology from algorithmic model tuning to large-scale experimental data generation. By leveraging national laboratory supercomputers to standardize single-cell perturbation measurements, the initiative attempts to create a universal pre-trained foundation model for living tissue. However, the one-year commercial data embargo highlights the tension between public open-science goals and corporate data moats.
Biohub organizers and federal lab directors argue that public-private pooling is the only viable path to fund the trillions of standardized physical measurements needed to make cell biology predictive. Academic bioethicists warn that granting tech incumbents a 12-month exclusive preview on foundational biological corpora creates an anti-competitive advantage in therapeutic target discovery.
A governance study published on Thursday, October 8, analyzed the failures of IBM/Maersk's TradeLens and the Helium network to highlight the 'paradox of decentralization.' The paper details how both projects implemented distributed ledger architectures while succumbing to centralized governance capture—specifically token concentration among founding insiders, rigid protocol rules, and the lack of low-cost dispute resolution channels. The authors contrast top-down token governance with agent-centric design patterns that embed Elinor Ostrom's commons management principles.
Why it matters
This research provides a sober counter-narrative to the assumption that deploying a distributed ledger automatically guarantees decentralized governance or community alignment. When protocol decision-making remains captured by founding corporate entities or concentrated token holders, the system replicates traditional centralized power dynamics under a distributed technical veneer. Builders of network cities and protocol DAOs must implement explicit institutional checks to prevent early insider capture.
Governance researchers argue that token-weighted voting inevitably degenerates into oligarchy unless protocols adopt polycentric governance mechanisms and localized dispute resolution. Decentralized infrastructure founders maintain that early token concentration is necessary to incentivize core development and fund capital-intensive physical hardware rollouts.
A working paper from Harvard Business School and INSEAD cited on Wednesday, October 7, shows that AI-native startups maintain core teams 25% to 34% smaller than traditional software peers while employing 20% more senior personnel and paying 36% higher professional salaries. Because generative AI tools absorb entry-level coding and research tasks, companies like presentation platform Gamma scaled to 70 million users with roughly 50 employees. The study notes startups are abandoning traditional job-board posting funnels in favor of proactive sourcing and front-loaded technical skills tests.
Why it matters
The traditional venture playbook of rapidly scaling junior engineering and SDR headcount post-Series A is obsolete for AI-native companies. Early-stage founders must restructure talent acquisition around hiring a dense core of high-agency senior individual contributors ('Super ICs') paired with automated workflows. This shift compresses team size while elevating average compensation, requiring founders to alter board reporting metrics and runway calculations.
Startup founders and researchers emphasize that lean teams of senior operators powered by AI agents eliminate management overhead and execute product iterations significantly faster. Tech labor economists warn that eliminating entry-level junior roles collapses the broader engineering talent pipeline, creating a severe shortage of future senior operators.
Protocol-Layer Tool Control Preempts Prompt Isolation Major infrastructure providers like Google Cloud and enterprise security researchers are shifting agent safety away from LLM prompt filtering toward native network and protocol parsing. By enforcing SPIFFE identities and inspecting Model Context Protocol messages directly within proxy gateways, platforms are isolating tool-call privileges before an agent's reasoning engine can execute an unauthorized action.
Outbound Engine Automation Collides with Deliverability Limits As B2B revenue teams deploy autonomous SDRs and multi-sender sequencers, mailbox providers are enforcing strict anti-spam ceilings that burn domain reputations. The market response is forcing a pivot away from brute-force list blasting toward first-party intent triggers, website de-anonymization, and GTM engineering setups that require human narrative sign-off.
State Sovereignty Coalitions Target Federal Event Preemption State attorneys general and tribal leaders are coordinating multi-jurisdictional legal challenges to roll back federal CFTC oversight of event contracts. By petitioning the Supreme Court, state authorities are attempting to reclassify prediction contracts as unlicensed sports gambling to preserve local tax revenues and regulatory control.
AI-Driven Cryptanalysis Accelerates Post-Quantum Timelines Machine-generated mathematical discoveries are pushing protocol architects to reconsider the safety margins of standard public-key schemes earlier than anticipated. Layer-2 networks like Starknet are now contemplating independent transitions to Layer-1 status specifically to implement post-quantum signatures ahead of base-layer Ethereum schedules.
Sovereign-Scale Compute Allocations Divert Growth Capital Venture deployment data reveals an unprecedented concentration where a handful of AI infrastructure and foundational model providers absorb over 80% of global capital. Early-stage non-AI startups and mid-market growth companies are facing severe liquidity bottlenecks as institutional LPs and tier-one funds pivot toward billion-dollar hardware debt packages.
What to Expect
2026-10-30—Polymarket Protocol V2 smart contract public testing period concludes ahead of mainnet deployment.
2026-11-02—Polymarket target launch date for new multi-chain event markets powered by Protocol V2.
2027-01-01—Greek national digital identity age-verification wallet mandate takes effect under ZK-proof rules.
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