Holding 1 billion USD, Electric Capital analyzes 26 investment directions in the Web3 industry for 2026

Author: Electric Capital

Translation: Jiahui, ChainCatcher

Trust in institutions is collapsing worldwide. People have lost confidence in the entities that once formed the core of economic, political, and social life: governments, banks, media, and schools. This is not a short-term trend nor a reaction to a single event. It is a long-term shift in expectations. People no longer assume that institutions are neutral, reliable, or aligned with their interests.

Distributed systems and cryptography provide builders with new trustless tools. These technologies are designed to operate in adversarial environments: they assume participants may act maliciously, software must be verifiable, and systems should continue functioning even if counterparts go bankrupt.

AI makes this shift toward “minimized trust systems” more urgent and feasible than ever before. AI not only centralizes power but also reduces development costs. Now, an individual can build what previously required a team of months in just a few hours. This puts pressure on intermediaries, opens new possibilities for builders, and increases demand for infrastructure that “empowers users.”

Systems controlled by users are the only way to truly safeguard freedom. All user-owned systems minimize reliance on intermediaries by returning control to the users. These systems cannot be unilaterally altered. They enable people to build without permission. Ideally, if existing systems no longer serve users, they can freely opt out without losing access to functions or data.

This article outlines 26 key opportunities in critical areas by 2026.

These opportunities cover all user-owned systems, globally accessible markets, entertainment built on new financial primitives, and infrastructure for a world where AI is ubiquitous and deeply embedded. Yet, they share a common theme: exploring how power, access, and ownership should operate in an AI-embedded world.

These opportunities focus on six key domains:

2. Personal Software: AI enables the creation of tailored tools, not just SaaS built for general users. Private agents, encrypted collaboration, and locally running software are now feasible and increasingly necessary.

3. Agent-Oriented Infrastructure: As AI agents become primary builders of software, existing development stacks will be disrupted. New primitives are needed for testing, deployment, payments, data access, and coordination among agents.

4. Fintech and DeFi: Stablecoins allow over 4 billion people and millions of businesses to access USD. They now seek yields, equity exposure, insurance, and more. The demand for global, programmable, accessible financial infrastructure is accelerating.

5. Financial Entertainment: The younger generation views markets as entertainment. Trading is fast, social, and fun. This transforms financial products and opens doors to new markets.

6. Metaverse Revival: World models and generative AI drastically reduce the cost of building immersive, personalized environments. People will enter experiences shaped around them rather than passively consume content. There are huge opportunities in platforms that simplify world creation and empower users to control how their data is shared, stored, and monetized within these worlds.

7. New Cryptographic Primitives and Applications: Proof-of-stake and proof-of-work are maturing and leaving room for new consensus models. Zero-knowledge proofs and fully homomorphic encryption are becoming practical. These primitives unlock new design spaces: consensus tied to human or physical inputs, infrastructure with default privacy, and applications built on regulated entities, energy markets, or new jurisdictions.

Personal Software

For the first time, individuals can build customized software tailored precisely to their needs without relying on big companies’ products. As AI agents now handle complex workflows (like reading emails, scheduling meetings, and managing files), new demands for data privacy, ownership, and persistence arise. Encryption-enabled systems can make these tools private, durable, and support multi-party collaboration.

Specific ideas we want to invest in:

• Private AI Agents: People need to run AI on sensitive data securely.

  • What it might look like: An AI assistant that automatically manages your personal workflows and protects privacy. Connects to your health and financial records to provide insights. Runs in trusted execution environments or compute networks, with queries anonymized. Responds without enterprise providers or malicious actors seeing your data.

• Encrypted Collaboration Spaces: People need private collaboration with others (human or AI agents). Remember, “the cloud” is just someone else’s computer.

  • What it might look like: A shared workspace for friends, family, or small businesses. Financial data, documents, and tasks sync via peer-to-peer storage solutions. Selective disclosure allows agents to access specific data types. No accounts needed, no big companies reading, storing, or training on sensitive data, and offline work is supported.

• Desktop Agents: People need automation tools for their local computer data.

  • What it might look like: An agent running locally on your desktop to read emails, draft replies, create schedules, and organize your life. This idea could evolve into a new kind of desktop OS in an AI-first world.

• Privacy Payment Services: People need a way to pay for software services without identity verification.

  • What it might look like: Buying VPNs, games, cloud storage, or AI compute without accounts. Pay-as-you-go, measured by the service, settled with stablecoins via protocols like x402. The provider knows someone paid and how much but not their identity.

Agent-Oriented Infrastructure

Smart agents will write most of our code and perform much of our mental work. Key impacts include: (1) software tools need to be rebuilt from scratch because AI-generated code introduces new failure modes. (2) Development will shift inward as custom software becomes economically viable. (3) Agents need new pathways for mutual transactions. (4) Previously labor-constrained enterprises can suddenly scale through automation. These ideas capture the second-order effects and opportunities they bring.

Specific ideas we want to invest in:

• AI-Native Computing Infrastructure: Companies need to test, isolate, and rollback AI-generated changes at the infrastructure level.

  • What it might look like: An AWS or GCP rebuilt for agents. Agents code in sandboxed environments, safely test against production data, and deploy with automatic rollbacks if issues arise. Entire workflows assume code is from agents, not humans.

• End-to-End Product Development Tools: Non-technical staff need to go from idea to working software.

  • What it might look like: A platform where users specify business goals, data sources, and desired outcomes. The system generates plans, designs, code, and a working product. It eliminates the need for technical translation, enabling non-technical users to go from “idea” to “deployed product” in hours instead of months.

• Agent-Enabled Commerce: Agents need to buy and sell autonomously without human identities or bank accounts.

  • What it might look like: An API marketplace where agents purchase services from other agents. Discovery, negotiation, and pay-per-use protocols like x402 settle instantly with stablecoins.

• Data Networks and Markets: AI needs infrastructure to compensate contributors and give them control over their data.

  • What it might look like: A network where users share medical records, consumption patterns, investment behaviors, or creative works for AI training. Contributors set permissions and get paid when their data improves models. AI companies access high-quality, provenance-verified data.

• Scalable Professional Services: Service firms need AI-native operations to surpass human labor limits.

  • What it might look like: A law firm where each lawyer has an AI assistant for research, drafting, and review. A firm that once served 1,000 clients now serves 100,000. Any professional—lawyer, architect, marketer, accountant, financial advisor—can be restructured around AI.

Fintech and DeFi

Over 4 billion people and millions of businesses facing currency risk are actively seeking USD access via stablecoins, representing the largest expansion of the USD network effect in decades. As stablecoins provide USD access worldwide—from $3 billion in 2019 to over $300 billion today—millions of new USD holders need more than digital cash. They want yields, investments, and financial services. Opportunities are growing in financial products that give users ownership and global access.

Specific ideas we want to invest in:

• Yield Unrelated to Crypto: Stablecoin holders need yields that don’t decline when Bitcoin’s price drops.

  • What it might look like: A platform that brings real-world infrastructure yields to stablecoin holders. Yields could come from bonds of data center projects, solar farms, and EV charging networks with predictable cash flows and no crypto correlation.

• Global Accessible Equity: Investors worldwide need low-friction, low-cost direct ownership of foreign opportunities.

  • What it might look like: Financial products replicating equity ownership with price exposure, no funding rate, and no expiration. Traders in the Philippines build portfolios of US tech stocks; Canadians build Korean semiconductor exposure.

• New Insurance: Businesses need fast, transparent underwriting for operational risks that traditional insurance can’t cover.

  • What it might look like: A platform creating new insurance products via prediction markets. Chain hotels buy hurricane coverage for Florida properties. Ski resorts hedge against warm winters. Capital providers supply liquidity in exchange for uncorrelated yields.

• On-Chain Commodities Markets: Commodities need markets with 24/7 trading, instant settlement, and global access.

  • What it might look like: A marketplace for trading energy storage capacity. Battery storage is a potential starting point, as data centers need reliable power and are investing in storage to reduce grid reliance and integrate renewables. Excess capacity can be sold during peak demand. Grid operators can trade capacity seasonally.

• Protected DeFi Assets: Institutions need to deploy assets into DeFi securely, even in the event of hacks.

  • What it might look like: Wrapped ETH that can be rolled back if a protocol is hacked. A trusted committee reviews exploits and can reverse GuardedETH without moving the underlying ETH. Legitimate transactions proceed normally.

Financial Entertainment

The younger generation views financial markets as a meritocratic alternative outside traditional paths. When they participate, they reimagine markets as entertainment. They trade like playing games: seeking high-adrenaline, quick-feedback, accessible markets. Fast-turnover products like 0DTE options, settling in hours, now account for over 55% of S&P 500 options volume. Prediction markets, where anyone can bet on headlines, are projected to reach $44 billion in trading volume by 2025, a fivefold increase from the previous year. They turn their trades into content: live discussions on Discord, sharing wins and losses on TikTok, reviewing portfolios on Twitch. When markets become entertainment, new platforms can emerge that treat financial data as engaging, participatory content.

Specific ideas we want to invest in:

• Audience Capital: Live viewers need ways to financially participate in outcomes.

  • What it might look like: A platform allowing viewers to stake on live content. Participation makes viewing more engaging, currently limited to tips and subscriptions. The platform lets viewers bet on who will be eliminated or copy trades when streamers share their positions.

• Opinion Markets: Prediction platforms need markets that settle based on collective beliefs, not just event outcomes.

  • What it might look like: A platform generating ranked lists based on market consensus. Users stake on how they think others will rank items. It creates lists like “Best Pizza in New York,” “Top Wines Under $20,” “Most Influential Movies of the Last Decade,” or “Best AI Developer Tools,” all ranked by market. Rankings are settled weekly based on weighted stakes.

• Short-Form Content Platforms: Since individual creators can produce shows more cheaply than studios, they need funding and distribution.

  • What it might look like: A short-form UGC (user-generated content) platform. Creators produce series using AI video tools: “Mafia Boyfriend,” “Secret Billionaire Exposed,” “Revenge Thriller.” Fans unlock episodes and tip creators with tokens. Creators earn revenue based on viewership. ReelShort generated over $700 million in Q1 2025 with low-budget, studio-quality short series. The platform combines YouTube-style UGC with ReelShort’s video format.

Metaverse Revival

Immersive digital worlds are now economically feasible to build. Over the past two years, AI models for images, videos, and simulations have advanced rapidly, drastically lowering asset and environment creation costs. Individual creators can now build what once required entire game studios. Meanwhile, demand for personalized, interactive content is accelerating: Dispatch, a “choose-your-own-adventure” TV/game hybrid, sold 3.3 million copies in three months, earning $85 million with a 98% positive rating. In Q3 2025 alone, Roblox’s daily active users grew 70% year-over-year, paying out $428 million to creators. Personalized, AI-driven character chat apps like Character AI also show strong early demand for personalized entertainment. These new environments not only entertain users but will generate rich structured interaction data for world models and robotics.

Specific ideas we want to invest in:

• World Compiler: Individual creators without professional skills need tools to convert natural language into fully interactive 3D environments.

  • What it might look like: A platform translating natural language into fully interactive 3D worlds. Building environments still requires modeling, physics, and NPC logic skills. AI can remove these barriers. Creators describe a world, and the system constructs it. Assets, physics, NPC logic, and memory are handled automatically. Creators can publish rich virtual environments in days instead of years.

• Procedural Narrative Engine: Players need stories that adapt to them and never end.

  • What it might look like: A platform generating real-time, personalized stories. Linear stories have endings. Players want experiences that adapt and continue. For example, a detective universe where each case is unique, characters remember past interactions, and plot twists respond to choices. The story never exhausts.

• “World as Data Set” Platform: World models and robotics need diverse interaction data. Immersive consumer environments generate this data continuously, but no one captures it.

  • What it might look like: A VR game where every player interaction is instrumented and recorded. How users move through rooms, pick up objects, and interact with characters becomes training data for robots. Users opt in, set sharing permissions, and get compensated. AI companies gain access to real human behavior data that can’t be synthetically generated.

New Cryptographic Primitives and Applications

Cryptographic primitives are no longer just theoretical. Proof-of-stake and proof-of-work have proven resilient at scale. Zero-knowledge proofs are moving from research to production. Fully homomorphic encryption is becoming faster and more practical. As these foundational technologies mature, they unlock new opportunities: systems that prioritize privacy, embed real-world inputs into consensus, and coordinate legacy systems like energy markets or governments.

Specific ideas we want to invest in:

• Human Effort as Consensus: Blockchain networks need consensus mechanisms anchored in human effort, not just capital.

  • What it might look like: Proof of useful work, where consensus requires completing externally valuable tasks like data labeling or verifying real-world events. Participation rights derive from proven ability, not staking.

• Physical Resource Networks: Small-scale infrastructure operators need systems to make their contributions economically rational.

  • What it might look like: Energy networks where production or storage serve as consensus weights, combining grid stability with security. Sensors measuring physical parameters—weather, water, infrastructure—anchor the network.

• Privacy-Native L1: Healthcare, enterprise, regulated finance, and many other sectors need blockchains with default privacy.

  • What it might look like: Confidential state machines that compute on encrypted data by default. Current chains are transparent, but many entities legally cannot operate on transparent ledgers. Validators use ZK-native architectures or FHE-based execution to verify transactions without viewing content.

• Application-Specific Fully Homomorphic Encryption: Institutions often need to collaborate on data without revealing it.

  • What it might look like: Banks detecting suspicious activity across institutions without sharing customer data. Each bank runs FHE queries on encrypted data from others. They can identify accounts involved with the same suspicious entity without revealing customer lists.

• Energy Contract Settlement: Traditional markets need encrypted channels for 24/7 settlement between parties. Deregulated energy markets are a good starting point, as they are outdated and under increasing strain from AI-driven energy demand.

  • What it might look like: A shared settlement layer for energy contracts in deregulated markets. Delivery data triggers automatic payments. Suppliers see cash flows in real time. Brokers get instant commissions. No single party controls the ledger.

• Crypto-Native Jurisdictions: Special economic zones and frontier jurisdictions need new governance and financial infrastructure models.

  • What it might look like: A new jurisdiction adopting crypto from day one. On-chain identities, programmable courts, tokenized capital markets, and smart contract-based regulation.