# Distribution Articoli collegati

Il Centro Notizie HTX fornisce gli articoli più recenti e le analisi più approfondite su "Distribution", coprendo tendenze di mercato, aggiornamenti sui progetti, sviluppi tecnologici e politiche normative nel settore crypto.

A New Player Enters at Third Place, Rothera Disrupts the Prediction Market Landscape

"Rothera Skyrockets to Third in Prediction Market Rankings, Disrupting Industry Landscape" Rothera, Robinhood's newly launched prediction market platform, has rapidly climbed to become the third-largest player in the sector by trading volume, trailing only giants Kalshi and Polymarket. Its growth is attributed not to attracting new users, but to migrating existing Robinhood user orders away from partner Kalshi. Previously, Robinhood served as a major distribution channel for Kalshi, accounting for an estimated 25%-35% of its volume. With the launch of Rothera, Robinhood now internally executes events like World Cup contracts, capturing revenue that was previously shared with Kalshi. Data shows Rothera's weekly trading volume surged from $21.9 million to $559 million within weeks, reaching nearly one-fifth of Polymarket's volume. Analysts estimate Robinhood's prediction market business could generate around $10 billion in annual revenue at this pace, potentially surpassing its historical crypto revenue peak. In response, Kalshi is reportedly exploring new distribution channels by engaging with investment banks for a potential IPO, requiring them to integrate their systems with Kalshi to access institutional clients. This shift highlights a new competitive focus in prediction markets: controlling user access and distribution channels rather than just product offerings.

marsbit06/22 09:07

A New Player Enters at Third Place, Rothera Disrupts the Prediction Market Landscape

marsbit06/22 09:07

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

Alliance Co-founder's Letter to Entrepreneurs: On Cursor's $60 Billion Sale Many aspiring founders see massive exits like Cursor's $60B sale and wonder why they can't achieve the same, often concluding opportunities are exhausted. But great companies aren't built in obvious, crowded spaces. Cursor, like Stripe, Figma, and Shopify before it, started with a non-consensus belief about the future. Before ChatGPT, they believed AI would transform knowledge work. They focused on a genuinely exciting domain, became their own customer, and obsessed over power users. Their journey involved years of "glass-chewing" effort before the market was ready. The pattern is consistent: identify a long-term technological shift, find a missed entry point, and execute for years before the trend becomes obvious. First-generation products (PayPal, Adobe, Amazon) prove a market exists. Second-generation winners (Stripe, Figma, Shopify) rebuild that market around new insights, technology, or changing customer behaviors. Founders must identify their phase in the cycle. Early entrants like Coinbase or Cursor focus on making new technology usable for power users. Later entrants find the "yin" to the established "yang"—the blind spots incumbents miss as they grow distant from individual users. The key is deep market immersion. Use every product in your space. Talk to users. Build an audience. Stop looking for ideas and start *seeing* them everywhere. Then, choose one. The idea must offer a 10x improvement or solve a "hair-on-fire" pain point—something severe enough that users are already crafting workarounds. When building, avoid feature bloat. Ask: why would someone switch? Great startups rarely force new behaviors; they improve familiar workflows with drastically lower friction (e.g., Cursor forked VS Code instead of creating a new editor). Distribution is the underestimated moat. Before product-market fit, achieve distribution-market fit. How do customers discover new tools? Founders like those at Airbnb, Stripe, and Cursor did unscalable, manual work to recruit early users. The final, unteachable ingredient is resilience. Cursor built for years pre-market, faced rejection, and persisted. So did Airbnb, Nvidia, and Rain (which launched post-FTX collapse). The lesson isn't that these founders were smarter, but that they stayed in the game long enough for their insights to compound. Framework: Spot technological cycles. Cultivate unique insight. Obsess over your market. Talk to customers. Find a hair-on-fire problem. Build the simplest wedge. Win your distribution channel. Above all, don't quit when it gets hard. Most people won't do these things consistently. The few who do build the next generation of great companies. Go build.

marsbit06/20 03:47

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

marsbit06/20 03:47

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

In this letter to entrepreneurs, Alliance reflects on the success of Cursor's $60 billion sale to Elon Musk, using it as a case study to counter the misconception that opportunities in crowded fields like AI or crypto are exhausted. The piece argues that great companies like Cursor, Stripe, Figma, and Shopify are not built by geniuses with perfect ideas, but by founders who start with a non-consensus belief about the future and build for years before that future becomes obvious to everyone. They identify long-term shifts, find overlooked entry points, and execute relentlessly. The framework for success involves: 1. **Identifying your place in the technology cycle**: Early-stage opportunities focus on making new tech usable for power users (e.g., Coinbase, Cursor). Later-stage opportunities involve finding the "yin" to an existing "yang"—the blind spots of first-generation players (e.g., Stripe vs. PayPal, Figma vs. Adobe). 2. **Cultivating unique insights**: Immerse yourself deeply in the market. Use every product, talk to users, and build an audience. Insights will emerge naturally from deep engagement. 3. **Finding a "hair-on-fire" problem**: Look for a 10x improvement or a severe, urgent pain point. The strongest signal is people already building clumsy workarounds. 4. **Building a focused MVP**: Don't just add features because you can. Ask why users would abandon their current tool for yours. The best startups rarely force new behaviors; they improve familiar workflows with drastically lower friction. 5. **Winning a distribution channel**: Distribution is often the moat. Before product-market fit, achieve channel-market fit. Find where your customers are and build an engine to reach them, even through unscalable, manual efforts initially. 6. **Persistence**: The final, unteachable ingredient is resilience. Success stories like Cursor, Airbnb, and Nvidia involved years of grinding, rejection, and perseverance when the path forward seemed unclear. The conclusion is that there is no secret. Most people fail to consistently execute these steps over the long term. The few who do build the companies that define the next era. The world is yours to create.

链捕手06/20 03:37

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

链捕手06/20 03:37

The Value Distribution of Stablecoins

The Value Distribution of Stablecoins The article argues that stablecoins are evolving from a mere trading tool into a broad "dollar channel." It analyzes the industry's value chain through four layers: 1. **Issuance Layer (e.g., Tether, Circle):** The top layer that mints stablecoins, holds reserve assets, and captures the thickest interest rate spread. 2. **Infrastructure Layer (e.g., Bridge, BVNK):** Connects stablecoins to the traditional financial system, handling critical but complex "dirty work" like fiat on/off-ramps, banking integration, compliance (KYC/AML), and cross-border settlement. 3. **Acquiring/Distribution Layer (e.g., Stripe, Coinbase):** Embeds stablecoins into merchant systems, manages payment flows, and integrates with enterprise software. 4. **Application Layer:** End-users and businesses that ultimately use stablecoins for payments, settlement, or storing value. The author posits that while the issuance layer currently captures the most profit, the most overlooked and potentially critical layer is infrastructure. The core challenge for stablecoin adoption isn't the on-chain transfer (which is simple), but bridging the gap between blockchain and the real-world financial system. This involves solving practical problems for businesses: fiat conversion, reconciliation, tax handling, and user onboarding. Infrastructure companies are currently in a difficult "land-grab" phase—building networks, securing banking relationships, and achieving compliance country-by-country. They face pressure from both the profitable issuance layer above and distribution platforms below. However, the author suggests this layer is building a crucial moat. Once stablecoins become a default business rail, the infrastructure players who have done the hard work of integration may gain significant, durable value and pricing power.

链捕手06/15 14:36

The Value Distribution of Stablecoins

链捕手06/15 14:36

The First Prediction Market Stock Has Emerged!

"Prediction Market Unicorn Emerges!" While the World Cup drives record trading volumes in prediction markets, the industry leader Kalshi faces a new threat from a former key ally. In March 2025, Kalshi partnered with online broker Robinhood to offer prediction market services, allowing users to bet on events. This deal was mutually beneficial: Kalshi gained access to Robinhood's massive retail user base, with an estimated 25-35% of its volume coming through this channel, while Robinhood earned significant fees, reporting a 320% year-over-year increase in "other transaction revenue" to $147 million in Q1 2026, largely fueled by prediction markets. However, Robinhood's ambitions have grown. Recognizing that its user base and distribution power are the scarcest resources, it initiated a plan to bring operations in-house. In late 2025, Robinhood partnered with Susquehanna to acquire CFTC-regulated exchange MIAXdx, renaming it Rothera Exchange. By June 2026, Robinhood launched its own prediction market product on Rothera, strategically using the World Cup as a launchpad. Initial data shows Rothera processing tens of millions of contracts within days, directly siphoning volume away from Kalshi. This shift marks a pivotal moment: control is moving from the market infrastructure provider (Kalshi) to the entity controlling user distribution (Robinhood). The story illustrates a recurring internet era dynamic: "He who controls distribution controls everything." As more platforms with large user bases recognize the value of prediction markets, the industry's future competition may center less on which platform has the best market technology and more on which one owns the user gateway.

marsbit06/15 09:28

The First Prediction Market Stock Has Emerged!

marsbit06/15 09:28

To C, To B, and the Next Big Thing Called To A

After To C and To B, the Next Wave is To A: Serving AI Agents In a recent quarterly earnings call, Meituan's Wang Xing introduced a new concept: To A (To Agent), signifying that future business services will increasingly target AI Agents as primary clients, not just consumers or merchants. This shift implies that internet giants must now consider how to make their services more appealing for AI Agents to recommend, fundamentally altering traditional distribution logic. This "To A era" is prompting an unusual trend of alliances among major tech companies. Unlike previous competitive battles, firms like Meituan, Tencent, JD.com, Huawei, OPPO, and OpenAI are rapidly forming partnerships. The reason is strategic: as AI Agents become the primary user interface, handling tasks from a single command (e.g., "Book a Japanese restaurant for tomorrow"), the risk for platforms is being bypassed entirely. Companies are positioning themselves within this new value chain. Three primary strategies are emerging: 1. **Super-Entry Points + Service Providers:** Platforms like Tencent's Yuanbao, WeChat, and ChatGPT aim to be the first-stop Agent, integrating various services (food delivery, shopping, travel) from partners like Meituan and JD.com. 2. **Apps as Callable Services:** Companies like Meituan, JD.com, and Uber are ensuring their core services remain accessible and callable by external Agents, shifting from front-end apps to back-end capabilities. 3. **System-Level Agent Entry Points:** Smartphone makers (Huawei, Honor, OPPO) are leveraging their OS-level AI assistants to control the initial user command, redistributing it to relevant service apps. While alliances offer mutual benefit—entry points gain service capabilities, and service providers gain traffic—inherent conflicts of interest exist. A dominant Agent platform could eventually attempt to connect directly with suppliers (restaurants, hotels), bypassing current aggregators like Meituan or Ctrip. Other unresolved challenges include the potential for Agent recommendations to become a new form of paid ranking and unclear accountability for faulty recommendations. The current rush to form alliances is a defensive move by service providers to secure their position before the landscape solidifies. In this To A-driven restructuring, the greatest risk is not losing the race but failing to hear the starting gun.

marsbit06/09 06:08

To C, To B, and the Next Big Thing Called To A

marsbit06/09 06:08

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