Today on The Distribution Desk: An autonomous economic layer is rapidly crystallizing as AI agents begin executing operational tasks while blockchain protocols settle the underlying value. From the first agent-to-agent OTC markets to Salesforce's new commercial AI suite, the infrastructure for a non-human workforce is moving from theoretical frameworks to live production.
The foundational agentic payment rails we've been tracking are now facilitating entirely machine-to-machine economies. On Tuesday, reports confirmed the emergence of the first agent-to-agent Over-the-Counter (OTC) markets, where AIs autonomously discover counterparties, negotiate terms, and settle payments in stablecoins using high-frequency protocols like x402 and Circle's nanopayments. The trend is underpinned by recent labor reports confirming rapid AI-driven displacement of routine tasks, creating a clear use case for a new financial infrastructure that legacy banking cannot provide.
Why it matters
This convergence of AI labor and crypto settlement is not a speculative future; it's the beginning of a foundational economic shift. For builders, this creates a greenfield opportunity to create the core infrastructure—identity, reputation, legal, and financial services—for a non-human economy. The key insight is that AI's ability to 'do the work' is only half the equation; the other is a payments layer that matches its autonomy and speed. This will reshape capital flows, labor markets, and the very nature of what a 'company' is.
"We're witnessing the birth of an autonomous economic layer where AI agents handle operations and blockchain manages value transfer. This isn't just about efficiency; it's a fundamental restructuring of economic activity," one analysis notes. Another perspective emphasizes the urgency for new regulatory frameworks, stating, "Traditional financial regulations were not designed for a world where machines are the primary economic actors. We're in uncharted territory." The development highlights the opportunity for builders to create entirely new categories of services for this machine-to-machine economy.
Alchemy has officially rolled out its AgentCard integration with Visa Intelligent Commerce, which we noted on Sunday as part of the broader World ID 'AgentKit' launch. The service binds a verifiable digital identity to a Visa-backed virtual payment credential, allowing autonomous agents to make online purchases by tapping into their human user's existing credit lines and rewards programs while operating as distinct, identifiable actors.
Why it matters
This integration is a major step toward institutionalizing agentic commerce. By binding a verifiable digital identity to a globally accepted payment credential, it solves a key piece of the trust puzzle. For B2B commerce, this provides a model for how enterprises can provision agents with controlled purchasing power and clear audit trails. It moves the concept of 'Know Your Agent' (KYA) from a theoretical framework to a practical implementation on one of the world's largest payment networks.
One analyst stated, "This is the bridge between the nascent agent economy and the existing financial world. Giving an agent a Visa card, even a virtual one, makes it a real economic participant." Another view from a security perspective cautioned, "While this enables commerce, it also creates a massive new attack surface. The security of the agent's identity and the robustness of its spending controls are now paramount." The move is seen as accelerating the need for standardized agent identity protocols.
In a significant reversal, U.S. export controls on Anthropic's most advanced models, Fable 5 and Mythos 5, were lifted last week, restoring global access. Following this, Anthropic announced on Monday that its new 'Sonnet 5' model, noted for its strong agentic capabilities, will become the default for its API. The week's developments, curated by AI models themselves, also highlighted the launch of Claude Science, an internal drug discovery platform, and a White House proposal for top AI labs to give the U.S. government a 5% equity stake to align public and private interests.
Why it matters
The rapid succession of events—restored access to frontier models, the rollout of a highly agentic default model, and novel government proposals for profit sharing—signals an acceleration in both the deployment and the governance of advanced AI. The release of Sonnet 5 as the new default agent makes powerful agentic capabilities more accessible to builders, increasing the urgency for robust trust and safety infrastructure. The proposed government equity stake is a novel mechanism for public oversight, attempting to give the government a seat at the table in guiding the development of potentially transformative technology.
"The restoration of Fable 5 and Mythos 5 access is a tacit admission that fencing off these models geographically is futile," stated one TechCrunch report. Regarding Sonnet 5, an Anthropic post noted, "We believe making strong agentic reasoning the default will accelerate the development of helpful and safe AI applications." On the equity proposal, a Bloomberg analyst commented, "This is a paradigm shift. The government isn't just regulating from the outside; it's proposing to become a stakeholder, aligning its interests with the massive potential upside of AI."
Following the launch of its 'Web4' infrastructure stack, Lithosphere has detailed the architecture's underlying audit capabilities. The system pairs deterministic execution on its 'Lithic' runtime with the 'PPAL' persistent identity layer, ensuring that every agent action—from initiation to settlement—leaves a built-in, tamper-proof record across the entire stack.
Why it matters
This addresses a fundamental requirement for enterprise adoption of agentic AI: deep and reliable auditability. While many solutions focus on policy enforcement, Lithosphere is building the underlying ledger for agent actions. In a B2B context where accountability is paramount, having a cryptographically secure, persistent record of an agent's entire decision-making process is critical for dispute resolution, compliance, and building trust between transacting parties. This is a structural approach to agent verification.
"Trust requires proof," a Lithosphere developer explained. "Our goal is to make an agent's history as verifiable as a blockchain transaction. You can't just trust the final output; you need to be able to audit the process." An analyst covering decentralized AI commented, "This is what 'verifiable computation' looks like when applied to agents. It's not just about identity, but about the integrity of the entire workflow history."
Salesforce announced on Monday the general availability of its 'Agentforce Commerce' suite, a major release featuring its 'Shopper Agent,' 'Buyer Agent,' and 'Merchant Agent.' These AI agents, now integrated with platforms like ChatGPT and Google Search, are designed to automate and personalize the entire commercial journey across B2C and B2B. The company cited data showing AI influenced 20% of global online sales in 2025, positioning this release as a foundational shift in its commerce strategy.
Why it matters
Salesforce's move signifies the mainstreaming of agentic AI within the core enterprise GTM stack. By providing agents for buyers, shoppers, and internal merchant teams, Salesforce is building the infrastructure to automate complex procurement and sales workflows. This puts pressure on competitors and highlights a critical challenge for all businesses: ensuring the underlying data and business logic are robust enough for agents to act upon reliably. For founders, it validates the shift toward building for an agent-driven customer journey.
A Salesforce executive stated, "This is about moving from conversational AI to transactional AI. Agents aren't just answering questions; they're completing tasks and driving revenue." An industry analyst commented, "The success of Agentforce will depend entirely on the quality of the 'digital twin' of a company's product catalog and business rules. Without clean, machine-readable data, these agents are flying blind." The release is seen as a key moment in the shift from human-driven e-commerce to automated agentic commerce.
A weekly recap of agentic AI news from last week highlights a major strategic shift by hyperscalers like AWS and Microsoft. Both companies are now making significant investments to embed their own AI engineers directly within customer companies. This 'forward-deployed' model aims to accelerate the adoption of their respective agentic AI platforms and infrastructure, effectively competing to become the default operating system for enterprise agents. The trend was reported alongside news of the first agentic ransomware attack and Square's integration of sellers into ChatGPT and Claude.
Why it matters
This isn't just customer support; it's a strategic land grab for the enterprise agentic layer. By embedding engineers, AWS and Microsoft are not just selling tools—they are shaping the customer's entire AI architecture from the inside, a powerful GTM motion that aims to create deep, structural lock-in. For founders and early-stage companies, this raises the competitive stakes, as they must now contend with incumbents who are essentially subsidizing the implementation of their own ecosystems.
"This is the cloud wars playbook adapted for the age of agents," commented one analyst for The Register. "The goal is to make your platform the indispensable 'brain' for the customer's AI workforce." A TechCrunch report added, "For enterprises, it's a tempting offer of free, high-end talent. But it comes with the hidden cost of deep vendor dependency and potential loss of architectural control."
A fundamental shift is occurring in B2B marketing, where the personal profiles of founders, executives, and key employees now generate significantly more engagement and attention than official corporate channels. An analysis on Monday highlights that platforms like LinkedIn, as well as AI-powered search and recommendation systems, increasingly prioritize authentic commentary and expertise from individuals over polished corporate messaging.
Why it matters
This trend represents a structural change in B2B distribution and social proof. For founders and early-stage companies, it validates the power of founder-led sales and marketing. The playbook is shifting from broadcasting through a corporate megaphone to cultivating a network of trusted individual voices. Investing in the personal brands of key team members is no longer a vanity project but a core GTM strategy for building credibility and reaching sophisticated buyers who trust people over logos.
"Your company page is a brochure, but your founder's profile is a conversation," notes one marketing strategist. "Buyers are tuning out brand-speak and tuning into authentic expertise." The analysis suggests this is driven by both human psychology and algorithmic amplification, as platforms reward content that sparks genuine discussion. "The most effective B2B brands of 2026 will be the ones that empower their people to be the face of the company."
A MarketScale analysis from Tuesday argues that B2B technology lead generation in 2026 has fundamentally shifted from a volume problem to a timing problem. With buyers conducting 60-70% of their research independently and 83% using AI assistants before engaging sales, the key is no longer reaching the most people, but reaching the right people at the precise moment of need. Successful outbound strategies are now prioritizing specific intent data and multi-channel sequencing over broad, high-volume campaigns.
Why it matters
This analysis codifies a structural shift in B2B GTM that many founders are feeling intuitively. The decline of cold outreach effectiveness isn't just about noise; it's because the buyer journey has changed. For early-stage companies, this means that investing in signal intelligence and building a 'just-in-time' outreach motion is now more critical than simply scaling the number of emails sent. It's a direct challenge to the traditional sales playbook and demands a more data-driven, surgical approach to distribution.
"The spray-and-pray era is officially over," the report states. "Your ideal customer is out there, but they are only in-market for a brief window. Your entire GTM motion needs to be optimized to detect that window and act instantly." This shift also changes how success is measured, moving from reply rates to metrics like sales-qualified lead (SQL) conversion rates and customer acquisition cost (CAC) by channel.
Vitalik Buterin's 'Lean Ethereum' roadmap, which we noted last week for its shift toward quantum resistance and recursive STARKs, has triggered a fierce debate over its proposed 3-4 year timeline. Prominent figures like StarkWare's Eli Ben-Sasson and EF researcher Dankrad Feist are publicly criticizing the schedule as too slow, arguing that key components—especially quantum readiness—must be delivered within a year.
Why it matters
The alignment on the 'what' (a more robust, private, and scalable protocol) but fierce disagreement on the 'when' highlights a critical tension in Ethereum's development. While the long-term vision aims to solidify its role as a global settlement layer, the slow pace risks ceding ground to more agile competitors. This debate is central to Ethereum's ability to balance rigorous engineering with market urgency, directly impacting how and when builders can leverage these next-generation features and whether institutional momentum can be sustained.
Eli Ben-Sasson argued, "A four-year timeline for quantum safety is not taking the threat seriously. We have the tools to do this in one year." Dankrad Feist added, "We are moving too slowly on things that are ready to be implemented now." In his original post, Buterin framed the roadmap as a comprehensive effort to reduce long-term protocol risk, justifying the deliberate pace. The discussion is now focused on whether development can be parallelized or if AI-assisted coding can accelerate the process.
Ethereum Institutional, the new non-profit we've been tracking since its launch on July 1, has secured backing from major financial players, most notably Standard Chartered. The initiative, which also includes support from Bitwise and Aztec Labs, is designed to serve as a formal bridge between Ethereum and traditional financial institutions, focusing on improving communication and advocating for use cases like tokenized assets and on-chain settlement.
Why it matters
The explicit backing from a global bank like Standard Chartered provides significant validation for this new, structured approach to institutional engagement. It signals a maturation of the Ethereum ecosystem, moving beyond ad-hoc partnerships to a coordinated effort to address the specific needs and concerns of Wall Street. This formal 'front door' could accelerate adoption by providing a clear point of contact for compliance, technical integration, and roadmap discussions, helping to manage the risks of institutional capture by shaping the conversation proactively.
A representative from Etherealize, a supporter of the initiative, stated, "For too long, the gap between Ethereum's developers and Wall Street's decision-makers has been too wide. Ethereum Institutional aims to close that gap." An analyst at Oracore noted, "This isn't about just another bank doing a pilot. This is about building the permanent social and organizational layer for institutional DeFi on Ethereum."
The Harvard and INSEAD study on AI-native team structures we covered yesterday has yielded hard percentages: these firms operate with 25% fewer workers, 15% fewer entry-level employees, and 15% fewer managers than traditional peers. By embedding AI directly into their core products and maintaining a higher proportion of senior engineers, these startups are scaling knowledge work without scaling headcount, while still achieving comparable funding and valuations.
Why it matters
This study provides quantitative evidence for a fundamental shift in company building. It's a counterintuitive finding for founders, suggesting that traditional metrics for startup growth (like headcount) are becoming obsolete. The ability to achieve venture-scale outcomes with a leaner, flatter, and more technical team has profound implications for founder strategy, hiring priorities, and capital efficiency. It validates the thesis that AI isn't just a tool but an organizational principle.
One of the researchers explained, "AI-native firms aren't just using AI; they are architected around it. This allows them to substitute capital for labor in knowledge-based tasks that were previously un-automatable." A venture capitalist commented, "We're recalibrating our models. A 10-person AI-native team might have the output and valuation potential of a 50-person SaaS company from five years ago. It changes how we evaluate early-stage opportunities."
Prominent AI leader Andrew Ng is championing a new organizational model for software development that relies on small, highly empowered teams of 1-10 'generalists.' In a post on Monday, he argues that in the AI era, these high-context pods can move much faster than traditional, larger teams of specialists. By leveraging AI to handle tasks across functions like front-end, back-end, and UX, these generalist teams can eliminate the handoffs and communication overhead that create bottlenecks.
Why it matters
This is a counterintuitive and potentially radical playbook for founder strategy and team composition. It challenges the conventional wisdom of hiring narrow specialists to scale a startup. Ng's model suggests that the highest-leverage organizational design for an AI-native company is not a traditional hierarchy but a collection of autonomous, cross-functional pods. For founders, this offers a path to faster iteration and greater capital efficiency by fundamentally rethinking team structure and the role of specialization.
Andrew Ng stated, "The bottleneck is no longer coding; it's the latency between decisions. A small team of generalists who share deep context can make and execute decisions in hours, while a traditional team takes weeks." A startup founder experimenting with the model commented, "We replaced our 'product, design, front-end, back-end' cycle with a single pod. Our shipping velocity has 10x'd." Critics question whether this model can scale for highly complex, regulated products that require deep domain expertise.
A guide published on Monday provides a detailed playbook for founders navigating the treacherous growth phase from $1 million to $10 million in annual recurring revenue. The framework emphasizes the necessary shifts in operations, focus on unit economics, and strategic hiring. Key advice includes transitioning from founder-led sales to a scalable sales process, hiring a leadership team (Head of Sales, COO, VP Marketing), and avoiding the common pitfall where a founder's 'hustle' becomes a bottleneck rather than an asset.
Why it matters
This stage is where many promising startups stall due to an inability to evolve beyond their initial success formula. The article provides a valuable structural analysis, offering concrete benchmarks for when to make key leadership hires and how to shift from a product-centric to a company-building mindset. For founders in the $0-10M stage, this is a practical, non-anecdotal guide to building the systems and team required for the next phase of growth.
The author states, "What got you to $1M will not get you to $10M. The skills are different. The systems are different. Most importantly, the founder's role must change from 'doer' to 'builder of a team of doers'." The guide includes specific advice, such as, "Don't hire a VP of Sales until you have a repeatable playbook they can scale. Hire a player-coach first." It also warns against premature scaling and chasing vanity metrics over profitable growth.
Two traders have filed a lawsuit against prediction market Polymarket, its CEO Shayne Coplan, and its CMO in New York, alleging breach of contract and deceptive practices. The lawsuit, filed last Friday, claims the platform retroactively changed the resolution criteria for a market concerning whether the company Strategy sold Bitcoin. According to the plaintiffs, Strategy did sell Bitcoin within the specified timeframe, but because the disclosure was made a day late, Polymarket resolved the market to 'No,' causing 'Yes' token holders to lose their funds.
Why it matters
This lawsuit strikes at the core of a prediction market's value proposition: objective, transparent, and rule-based resolution. The allegation that Polymarket altered terms post-event to favor a specific outcome—whether true or not—corrodes user trust and exposes the platform to significant legal and reputational risk. It highlights a critical failure mode where motivated reasoning or ambiguous rules can corrupt the forecasting mechanism, a key area of interest for observers of epistemic systems. The outcome could force significant changes to how markets are designed and how disputes are handled.
The lawsuit argues, "Polymarket held itself out as a neutral arbiter of truth, but when the facts were inconvenient, they changed the rules." In a statement, Polymarket has previously defended its use of UMA as a decentralized oracle for resolving ambiguous markets. A legal analyst noted, "This case will test the enforceability of a platform's terms of service against claims of deceptive practices, especially in the lightly regulated crypto space. It's a direct challenge to the 'code is law' ethos."
The CFTC has officially sued Minnesota Governor Tim Walz in federal court to block SF 4760, the state-level prediction market ban we've been tracking, before it takes effect on August 1. Building on its recent legal maneuvering in Wisconsin, the CFTC is aggressively asserting its exclusive federal jurisdiction over event contracts. Andreessen Horowitz (a16z) has publicly backed the agency's stance in a new comment letter, warning that a patchwork of state-level gaming laws will stifle innovation.
Why it matters
This lawsuit marks a major escalation in the federal-versus-state jurisdictional war over prediction markets. The CFTC is moving from defense to offense, actively suing a state to assert its authority. The outcome of this case will set a crucial precedent, potentially invalidating state-level bans and solidifying a single, federal regulatory framework for the industry. A16z's vocal support adds significant institutional weight, framing this not just as a legal squabble but as a critical issue for market structure and innovation.
The CFTC's complaint argues, "Congress granted the CFTC exclusive jurisdiction over swaps and commodity options, and event contracts fall squarely within these definitions." A16z's letter stated, "Allowing fifty different states to regulate these markets under disparate gaming laws would kill a nascent market that has proven valuable for information discovery." A representative for Governor Walz's office has not yet commented on the litigation.
South Korea's media and communications regulatory body is officially reviewing Polymarket's operational model for potential conflicts with national gambling laws. An official from the committee stated on Monday that they will allow Polymarket to submit its position before making a final decision on corrective action. The move marks a shift in focus from individual users to the platform itself, potentially threatening Polymarket's legal status and access in the country.
Why it matters
This action from a major Asian economy adds to the mounting global regulatory pressure on prediction markets. It underscores the persistent ambiguity of whether these platforms are considered financial information tools or gambling services. A negative ruling in South Korea could create a domino effect, influencing other regulators in the Asia-Pacific region and further complicating the international operating environment for platforms like Polymarket.
"We are actively considering a corrective request against Polymarket's gambling-related information," a regulatory official told The Currency Analytics. A representative from Polymarket has stated they will cooperate with the review. A local legal expert commented, "The core issue is whether betting on real-world events with real money constitutes a financial derivative, as some argue, or a game of chance, as the law currently sees it. This case could force a clarification."
An analysis published Tuesday dissects the consistent, recurring pattern of 'platform extraction' in the creator economy. The cycle begins with a platform attracting creators using generous terms, open APIs, and high organic reach. Once the platform achieves network effects, it systematically shifts leverage by restricting APIs, changing revenue shares, reducing reach, and prioritizing its own monetized formats. The article cites Twitter, Medium, and Facebook as historical examples, arguing this mechanic is a feature, not a bug, of platform business models.
Why it matters
This provides a critical mental model for any founder or operator building in the creator economy. Understanding this predictable cycle is essential for developing a sustainable distribution and monetization strategy that isn't wholly dependent on a single platform's benevolence. It underscores the strategic necessity of owning the audience relationship through tools like newsletters and building direct monetization channels. For anyone using platforms like Paragraph, recognizing this dynamic is key to long-term planning and mitigating platform risk.
The author writes, "Platform generosity is a customer acquisition strategy, not a long-term promise. Creators are not the customer; they are part of the product." A seasoned creator commented, "Every platform eventually has to answer to its shareholders. That's the moment the screws start to tighten on creators. Your only defense is a direct line to your audience." The analysis urges creators to view platforms as channels for discovery, not as a permanent home for their business.
Cirrden, a Nigerian startup founded in 2024, is providing a full-stack monetization platform for African creators to earn directly from their audiences. The platform addresses the friction of international services like Patreon and low ad-revenue rates for African viewership by offering paid videos, subscriptions, and private communities with integrated local payment options. The bootstrapped company has grown to nearly 8,000 users and is now raising a pre-seed round to expand into Kenya, Ghana, South Africa, and the US diaspora.
Why it matters
Cirrden's traction demonstrates a significant, underserved market within the global creator economy. Its success highlights a key distribution and monetization mechanic: building localized infrastructure that solves specific regional problems (like payment processing and audience relevance) that global platforms overlook. This is a powerful playbook for builders looking to serve creator communities outside the dominant Western markets, showing that 'niche' can be massive when defined geographically.
Founder Goodness Ezeokafor stated, "We realized that for African creators, the existing tools were broken. You couldn't easily get paid, and the platforms didn't understand the local context. We built Cirrden to solve our own problem." The company's fee structure, which decreases as a creator's earnings grow, is designed to align the platform's success with its users'. An investor in the African tech scene commented, "This is the kind of targeted, infrastructure-level solution that unlocks huge potential."
Silicon Gardens, a founders-for-founders VC fund with €33 million under management, detailed its investment criteria for pre-seed and seed-stage companies on Tuesday. Partner Vuk Lau stated the fund prioritizes four key factors: the caliber of the founding team, a large market size, rapid execution speed, and, most critically, an 'obsession with distribution.' The fund invests in early-stage startups across Europe and the U.S.
Why it matters
This provides a clear window into the thinking of an active early-stage fund, revealing that a sophisticated GTM and distribution strategy is no longer a 'nice-to-have' but a core investment criterion from day one. For founders, Lau's emphasis on a 'distribution-obsessed' mindset is a powerful signal. It confirms that in a world where AI has commoditized building, the ability to acquire customers is the primary differentiator and a key determinant of which companies get funded.
Vuk Lau explained, "We see countless great products that fail because the founders don't have a clear and obsessive plan for how to get it into the hands of users. Distribution isn't something you figure out later; it has to be in the company's DNA." Another partner added, "We back founders who are thinking about their GTM motion with the same rigor they apply to their tech stack. That's the ambition we look for."
An analysis of H1 2026 trends by ARGOS Identity, released Tuesday, concludes that identity verification has evolved from a security feature into core operational infrastructure. The report highlights its critical role in diverse sectors, including verifying human users on AI platforms, preventing fraud in ticketing and remittance, and automating compliance in franchise management. This shift is driven by the need to establish trust and accountability in an increasingly digital, AI-driven economy.
Why it matters
This analysis confirms that verifiable identity is no longer a peripheral concern but a foundational layer for modern business, especially in the context of agentic AI. As AI agents begin to act on behalf of users and businesses, the ability to cryptographically verify the identity and authority of all actors—human and non-human—becomes essential for commerce and liability. This trend validates the strategic importance of building robust identity and credentialing systems as a prerequisite for a trusted agent economy.
"We're seeing a fundamental mindset shift," the ARGOS report states. "Companies used to ask, 'How do we secure our app?' Now they ask, 'How do we verify every interaction in our ecosystem?' Identity is the answer." The report notes that regulatory pressures and the rise of sophisticated AI-driven fraud have accelerated this transition, making proactive identity infrastructure a competitive advantage.
AI Does the Work, Blockchain Moves the Value A new, autonomous economic layer is solidifying where AI agents perform operational tasks and blockchain-based rails using stablecoins handle the financial settlement. This convergence is visible in new agent-to-agent OTC markets and the integration of Visa credentials into agent identity systems, forcing a rethink of the entire financial and commercial stack.
The Startup Playbook Is Being Rewritten by AI Data from Harvard shows AI-native startups are 25% smaller and flatter, while founders like Andrew Ng are championing small, generalist pods over specialized teams. This structural shift, enabled by AI's ability to automate complex work, is altering founder strategy around hiring, team composition, and capital efficiency.
Prediction Markets Face a Two-Front War of Regulation and Integrity While prediction market volume soars, the industry faces intensifying pressure. South Korea is now reviewing Polymarket for gambling violations, and a new lawsuit challenges the platform's market resolution integrity. Simultaneously, the federal-versus-state regulatory battle in the U.S. continues to escalate.
B2B GTM Shifts to Signal-Based, Founder-Led Outreach The playbook for B2B sales is moving away from volume-based cold outreach. New frameworks emphasize timing and relevance, using data-driven signals to engage prospects. Concurrently, personal profiles of founders and executives are outperforming corporate channels, making founder-led sales and authentic employee voices a primary distribution channel.
The 'Platform Extraction' Cycle Defines Creator Economy Strategy A recurring pattern is becoming clear: platforms attract creators with favorable terms, then gradually extract value by changing algorithms and revenue shares. This mechanic forces creators to focus on owning their audiences and building independent business infrastructure, a trend highlighted by the rise of localized monetization tools and a shift toward sustainable, direct-to-audience business models.
What to Expect
2026-07-08—WeAreDevelopers World Congress begins in Berlin, with a major focus on AI-assisted development.
2026-07-09—CEPR conference on 'The Economics of Longevity and Ageing' begins at the University of Cambridge.
2026-07-10—DAZN will stream the Spain vs. Belgium World Cup match with integrated blockchain-based prediction markets.
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