<div id="readability-page-1"><div><div><p>Source: Electric Capital; Compiled by: Jinse Finance</p><h2>Key Points</h2><ul><li>Globally, trust in institutions is collapsing.<h2>Key Points</h2><ul><li>Globally, trust in institutions is collapsing.</li><li>IV. Finance as Entertainment: The younger generation views the marketplace as entertainment. Transactions are fast, social, and fun. This is changing the landscape of financial products and giving rise to new markets.</li><li>V. The Metaverse Revival: World models and generative AI have significantly reduced the cost of building immersive, personalized environments. People will be immersed in experiences tailored to their needs, rather than passively consuming content. There is a huge opportunity to build platforms that simplify the world-creating process and empower users to control how their data is shared, stored, and monetized within these worlds.</li><li>VI. New Cryptographic Primitives and Applications: The maturation of Proof-of-Stake and Proof-of-Work mechanisms has opened up space for new consensus models. Zero-knowledge systems and fully homomorphic encryption are becoming feasible.</li><li> These primitives open up new design spaces: consensus related to human or physical input, infrastructure for default privacy, and applications built upon this foundation for regulated entities, energy markets, and even emerging jurisdictions. </li></ul><h2>I. Personal Software</h2>For the first time, individual users are able to build software fully tailored to their own needs, no longer limited to services provided by enterprises. As AI agents can now handle complex workflows such as reading emails, scheduling meetings, and managing documents, the demand for data privacy, data ownership, and data persistence is growing. Encryption enables these tools to be private, persistent, and collaborative with multiple users.Specific projects we want to invest in:1. Private AI Agents: People need to run AI on sensitive data in a secure manner.It might look like: An AI assistant that automates your personal workflows while protecting your privacy. Connect to your health and financial records to gain AI insights. The AI ​​model runs in a Trusted Execution Environment (TEE) or on a computing network, with all inbound queries anonymized.</li></ul><h2>I. Personal Software</h2><p>For the first time, individual users can build software that is fully tailored to their own needs, no longer limited to services provided by enterprises.</p><p> When the response is returned, neither the enterprise provider nor malicious actors can see your data. 2. Encrypted Collaboration Space: People need to collaborate privately with others (including humans and intelligent agents). Remember, the &#34;cloud&#34; is just someone else's computer. It might look like: a shared workspace for friends, family, or small businesses. Finances, documents, and tasks are synchronized through peer-to-peer storage solutions. Selective disclosure allows agents to access specific data types. No account creation is required, no company reads, stores, or trains sensitive data, and it can be used offline. 3. Desktop Agent: People need to automate the processing of data on their local computers. It might look like: an intelligent agent program installed on your desktop running locally, responsible for reading your emails, replying to messages, creating schedules, and managing your life. In an AI-first era, this concept can be extended to a new type of desktop operating system. 4. Privacy-Defined Payment Services: People need ways to pay for software services without revealing their identity. </p><p>It might look like this: You can purchase VPN, gaming, cloud storage, or AI computing services without registering an account. Pay-as-you-go pricing is metered by the service provider and settled in stablecoins via x402 or similar protocols. The service provider knows that the user has paid and the amount paid, but not the user's identity.</p><h2>II. Agent-Centric Infrastructure</h2><p>Agents will write most of our code and do most of our knowledge work. Key impacts include: (1) Software tools will need to be rebuilt from scratch because AI-generated code will introduce new failure modes. (2) Development will shift in-house as custom software is now more cost-effective. (3) New channels of interaction will be needed between agents. (4) Enterprises that were once limited by manpower can suddenly scale. These perspectives capture the opportunities presented by these secondary effects.</p><p>Specific projects we want to invest in:</p><p><strong>5. AI-Native Computing Infrastructure:</strong> Enterprises need to be able to test, isolate, and revert AI-generated changes at the infrastructure level.</p><p>It might look like: AWS or GCP rebuilt for intelligent agents. Agents write code in a sandbox, safely test with production data, and automatically roll back deployments if issues arise. The entire process assumes the code is written by an intelligent agent, not a human.</p><p><strong>6. End-to-End Product Development Tools:</strong> Non-technical staff need to turn ideas into working software.</p><p>It might look like: A platform where users can specify business goals, data sources, and expected results. The system automatically generates plans, designs, code, and working products. This system requires no technical translation, enabling non-technical users to turn &#34;ideas&#34; into &#34;deployed products&#34; in hours (not months).</p><p><strong>7. Intelligent Agent-Enabled Commerce:</strong> Intelligent agents need to buy and sell autonomously, without human identity or bank accounts.</p><p>It might look like: An API marketplace where agents can purchase services from other agents. Service discovery, negotiation, and pay-per-use all use protocols like x402 and are settled instantly in stablecoins.</p><p> 8. Data Networks and Marketplaces: Artificial intelligence needs data infrastructure to compensate contributors and empower them with access. It could look like a network where users can share medical records, spending patterns, investment behavior, or creative work for AI training. Contributors can set permissions and be paid as their data improves models. AI companies can obtain the necessary and clearly sourced financial data. 9. Expanding Professional Services: Service businesses need AI-native operations to achieve scalability beyond human capabilities. It could look like a law firm where each lawyer has an AI assistant for research, drafting, and document review. A firm that once served 1,000 clients now serves 100,000. Any client service industry—lawyers, architects, marketers, accountants, financial advisors—can be reshaped with AI at its core. </p><h2>III. Fintech and DeFi</h2><p>Over 4 billion individuals and millions of businesses facing currency risk are actively seeking access to US dollars through stablecoins, representing the largest expansion of the dollar network effect in decades. As stablecoins provide global individuals with access to US dollars—growing from $3 billion in 2019 to over $300 billion today—millions of new dollar holders need more than just digital cash. They need yields, investment opportunities, and financial services. The space for financial products that empower users with ownership and global access holds increasing opportunities.</p><p>Specific projects we want to invest in:</p><p><strong>10. Cryptocurrency-agnostic yields:</strong> Stablecoin holders need yields that don't decline with the price of Bitcoin.</p><p>It might look like: A platform that delivers real infrastructure yields to stablecoin holders. Yields could come from data center project bonds, solar installations, and electric vehicle charging networks—projects with predictable cash flows that are agnostic to cryptocurrencies.</p><p> 11. Globally Accessible Equities: Global investors need direct access to overseas investment opportunities with low friction and low cost. It could look like: a financial product that simulates equity ownership, provides price exposure, has no financing rates, and no maturity date. A Filipino trader built a US technology portfolio. A Canadian trader built a South Korean semiconductor portfolio. 12. New Types of Insurance: Businesses need fast, transparent insurance to address operational risks that traditional insurance cannot provide. It could look like: a platform that uses prediction markets to create new insurance products. For example, a hotel chain could purchase hurricane insurance for its properties in Florida. A ski resort could hedge against the risk of a mild winter. Funding providers offer liquidity in exchange for market-independent returns. 13. On-Chain Commodity Markets: Commodities need markets that offer 24/7 trading, instant settlement, and global access. It could look like: an energy storage capacity trading market. Battery storage capacity is a potential entry point because data centers require a reliable power supply and are investing in energy storage to reduce their reliance on the grid and integrate renewable energy. Data centers with excess storage capacity can sell it to nearby facilities during peak electricity demand. Grid operators can trade capacity based on seasonal demand. </p><p><strong>14. Protected DeFi Assets:</strong> Institutions need to deploy assets in DeFi to ensure their safety even in the event of a hack. </p><p>It might look like: a wrapped version of Ethereum that can be rolled back if the protocol is attacked (GuardedETH). A trusted committee reviews the vulnerability and can roll back GuardedETH without affecting the underlying Ethereum. Legitimate transactions continue as usual.</p><h2>IV. Finance as Entertainment</h2><p>The younger generation sees financial markets as an elitist alternative to traditional paths. They participate in the market, reimagine its form, and transform it into entertainment. They trade like they're playing a game: seeking quick feedback and exciting trades in markets that are easy to learn and participate in.</p><p> For example, fast-settlement products like zero-day options account for over 55% of S&amp;P 500 options trading volume, with settlements completed within hours. Markets like prediction markets, where anyone can invest in news, are expected to reach $44 billion in trading volume by 2025, a fivefold increase from the previous year. They are also turning trading into content: discussing positions in real-time on Discord, sharing profits and losses on TikTok, and reviewing portfolios on Twitch. When markets become a form of entertainment, it creates opportunities for new platforms that treat financial data like users—as interesting and engaging content. </p><p>Specific projects we want to invest in:</p><p><strong>15. Audience Participation Capital:</strong> Live viewers need ways to participate economically in the outcomes.</p><p>What it could look like: A platform that allows viewers to bet on live content. Participation makes the viewing experience more engaging, but currently viewers can only tip and subscribe. This platform could allow reality TV viewers to predict who will be eliminated, or to copy trades following the streamer's trading process.</p><p> 16. Opinion Market: Prediction market platforms need markets based on collective beliefs rather than events. It might look like: a platform that generates market ranking lists. Users can bet on how they think others will rank these items. The platform would create lists such as the best pizza in New York, the best wine under $20, the most influential movie of the past decade, or the best AI development tool, all ranked by the market. The lists are adjusted weekly based on user betting weights. 17. TV Series Production Platform: Today, independent writers can produce TV series much cheaper than studios, so they need funding and distribution platforms. It might look like: a user-generated content (UGC) platform for short-form dramas. Creators use AI video tools to create series: gangster boyfriend saga, billionaire secrets revealed, revenge thrillers, and more. Fans can unlock series with tokens and directly tip creators. Creators' income depends on viewership. ReelShort generated over $700 million in revenue in the first quarter of 2025 with its low-cost, studio-produced series. The platform combines YouTube's user-generated content with ReelShort's video format. </p><h2>V. The Metaverse Revival</h2><p>Building immersive digital worlds is now economically viable. Over the past two years, AI models for images, videos, and simulations have advanced rapidly, significantly reducing the cost of creating assets and environments. Individual creators can now produce content that previously required an entire game studio. Simultaneously, the demand for personalized, interactive content is accelerating: Dispatch, an interactive TV/game hybrid that allows users to choose their own storyline, sold 3.3 million copies in just three months, generating $85 million in revenue with a 98% positive review rate. Roblox saw a 70% year-over-year increase in daily active users and paid creators $428 million in the third quarter of 2025 alone. Personalized, AI-driven character chat applications like Character AI are also showing strong early demand, meeting users' needs for personalized entertainment. These new environments not only entertain users but also generate rich, structured interactive data for world models and robotics. Specific projects we want to invest in: 18. World Compiler: Independent creators without specialized skills need tools that can translate natural language into fully interactive 3D environments. It might look like: A platform that translates natural language into fully interactive 3D worlds. Building 3D environments still requires specialized skills in modeling, physics, and NPC behavior. Artificial intelligence can break down this barrier. Creators only need to describe a world, and the system can build it. Resources, physics, NPC logic, and memory are all handled automatically by the system. Creators can deliver a rich virtual environment in just a few days, instead of years. 19. Procedural Narrative Engine: Players need stories that adapt to them and are endless. It might look like: A platform that can generate player-specific stories in real time. Linear stories have endings, but players want a game experience that adapts to their needs and continues to evolve. Users enter a detective world where each case is unique. Characters remember past interactions, plot twists change based on player choices, and the story never ends. 20. World as Dataset Platform: World models and robot systems require diverse interaction data. Immersive consumer environments constantly generate this data, but currently no one is collecting it. It might look like this: A virtual reality game where every player interaction is recorded. How users move around the room, pick up items, and interact with characters becomes data for robot training. Users can choose to join, set data-sharing permissions, and receive corresponding rewards. Artificial intelligence companies can obtain real human behavior data that they cannot generate synthetically. VI. New Cryptographic Primitives and Applications Cryptographic primitives are no longer just theoretical. Proof-of-Stake (PoS) and Proof-of-Work (PoW) have proven their robustness in large-scale applications. Zero-knowledge proofs (ZK) are moving from the research stage to production systems. Fully homomorphic encryption (FHE) is becoming increasingly faster and more available. As these foundational technologies mature, they create new opportunities for developers to build systems that prioritize privacy, embed real-world inputs into consensus mechanisms, and support coordination with traditional systems such as energy markets or governments. Specific projects we want to invest in: 21. Human-Time-Based Consensus: Blockchain networks need consensus mechanisms based on human effort, not just capital. It might look like this: Based on practical proof-of-work, consensus is achieved by completing tasks with external value, such as labeling data or verifying real-world events. Participation rights stem from demonstrated capabilities, not vested interests. 22. Physical Resource Networks: Small infrastructure operators need to coordinate systems to ensure their contributions are economically justified. It might look like this: In energy networks, the weights of production or storage are determined by consensus, thus aligning grid stability with network security. Sensor networks are closely integrated with physical measurement data such as weather, water quality, or infrastructure monitoring. 23. Privacy-Native L1: Healthcare, businesses, regulated finance, and many other industries require supply chains with privacy as the default setting. It might look like this: By default, computation is performed on encrypted data, forming a confidential state machine. Current blockchains are transparent by default, but many institutions, such as healthcare, businesses, and regulated financial institutions, cannot legally operate on transparent blockchains. Validators use a native zero-knowledge proof architecture or a fully homomorphic encryption-based execution method to verify transactions without viewing the transaction content. 24. FHE for Specific Use Cases: Institutions often need to collaborate on data processing without revealing their data to each other. It might look like this: Banks detect suspicious patterns between institutions without sharing customer data. Each bank runs fully homomorphic queries (FHE queries) on encrypted data from other banks. They identify accounts that have been in contact with the same suspicious entity without revealing their customer lists to each other. 25. Energy Contract Settlement: Traditional markets need cryptocurrency payment channels to enable 24/7 settlement between different participants. Unregulated energy markets are a good entry point because they are outdated and increasingly pressured by the growing energy demand driven by artificial intelligence. It could look like: A shared settlement layer for energy contracts in unregulated markets. Settlement data triggers automatic payments. Suppliers view cash flow in real time. Brokers receive commissions instantly. No single party controls the ledger. 26. Crypto-Native Jurisdictions: Special economic zones and frontier regions need new ways of thinking about governance and financial infrastructure. It could look like: A completely new jurisdiction that adopts crypto infrastructure from the outset. On-chain identity, programmable courts, tokenized capital markets, and regulatory logic based on smart contracts.</p></div></div></div>

<p>Electric Capital outlines 26 opportunities for 2026, highlighting a shift in trust towards institutions and the rise of finance as entertainment among younger generations. Key areas of focus include the metaverse, new cryptographic applications, and personal software tailored to individual needs. Investment opportunities include private AI agents, encrypted collaboration spaces, and AI-native computing infrastructure. The report emphasizes the need for privacy in transactions and the potential for intelligent agents to revolutionize commerce and software development.</p>

- Global trust in institutions is declining, prompting innovative shifts in finance, including the younger generation treating financial markets as entertainment.  
- The rise of personalized and immersive digital experiences through AI and the metaverse is enabling users to craft environments tailored to their preferences, alongside advanced cryptographic applications enhancing privacy and security.  
- Significant opportunities exist in creating private AI-driven services, decentralized finance products, and platforms that support seamless interactions in increasingly complex digital landscapes.

Electric Capital: 26 Opportunities in 2026