Electric Capital: When AI Removes Development Barriers, Here Are 26 Web3 Sectors We Want to Invest In
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Electric Capital: When AI Removes Development Barriers, Here Are 26 Web3 Sectors We Want to Invest In
In a world where AI is ubiquitous and deeply embedded, how should power, access, and ownership operate?
Navigating Web3 tides with focused insightsAuthors: Avichal Garg, Curtis Spencer, Ken Deeter, Maria Shen, Ren
Compiled by: TechFlow
TechFlow Editorial: Electric Capital’s 2026 investment blueprint marks a turning point where “user sovereignty” transitions from concept to mass adoption.
The authors profoundly argue that amid global institutional distrust and AI-driven power concentration, cryptographic technology is not merely a financial tool but a core infrastructure for defending individual sovereignty. From private AI agents running locally on desktops to stablecoin finance enabling 4 billion people to access dollar-denominated yields, the article outlines 26 specific investment opportunities across six key domains.
Full text below:
The conditions for user-owned technology are now ripe.
A global collapse of trust in institutions is underway. People have lost faith in institutions that were once central to economic, political, and social life—governments, banks, media, and schools. This is not a short-term trend or reaction to a single event, but a long-term shift in expectations. People no longer assume institutions are neutral, reliable, or aligned with their interests.
Distributed systems and cryptography provide developers with new tools that operate without requiring trust. These technologies are designed to function in adversarial environments: they assume participants may be malicious, software must be verifiable, and systems should continue operating even when adversaries fail.
AI makes this shift toward “minimal-trust systems” more urgent and feasible than ever before. AI not only concentrates power but also drastically lowers development costs. Now, one person can build in hours what used to take teams months. This pressures intermediaries, opens new possibilities for developers, and increases demand for infrastructure “owned by users.”
User-owned systems defend freedom. By returning control to individuals, these systems minimize reliance on trust. They cannot be unilaterally altered. They allow people to build without seeking permission. When well-designed, they let users exit systems that no longer serve them—without losing functionality.
Electric Capital invests $1M–$20M in user-owned technology, empowering individuals with control, privacy, and access.
Since 2018, we’ve focused on investing in systems that reduce dependence on intermediaries. We started with programmable money. Today, the same principles and technologies are being applied to software, data, markets, and beyond.
If you’re building in these areas, we want to back your idea. For deeper context on our thesis, read our 2018 essays on reimagining trusted intermediaries and programmable money.
This report outlines 26 opportunities across critical domains in 2026.
These opportunities span user-owned systems, globally accessible markets, entertainment built on novel financial primitives, and infrastructure prepared for an AI-software world. But they share one common thread: they explore how power, access, and ownership should function in a world saturated with deeply embedded AI.
These opportunities fall into six core areas:
Personal Software: AI enables tools tailored to your life—not generic SaaS built for average users. Private agents, encrypted collaboration, and locally-run software are now not just possible, but increasingly necessary.
Agent-Focused Infrastructure: As AI agents become the primary builders of software, existing development stacks will break. New primitives are needed for testing, deployment, payments, data access, and agent-to-agent collaboration.
Fintech & DeFi: Stablecoins give over 4 billion people access to the US dollar. Now, they need yield, equity exposure, insurance, and more. Demand for global, programmable, and accessible financial infrastructure is accelerating.
Finance as Entertainment: Younger generations treat markets as entertainment. Trading is fast, social, and fun. This reshapes financial products and unlocks new kinds of markets.
Metaverse Revival: World models and generative AI have dramatically reduced the cost of creating immersive, personalized environments. People will enter experiences built around them—not passively consume content. Opportunities exist in platforms that simplify world creation and give users control over data sharing, storage, and monetization within these worlds.
New Crypto Primitives and Applications: Proof-of-Stake (PoS) and Proof-of-Work (PoW) are maturing, making space for new consensus models. Zero-knowledge (ZK) systems and fully homomorphic encryption (FHE) are becoming practical. These primitives unlock new design spaces: consensus tied to human or physical inputs, infrastructure with default privacy, and applications for regulated entities, energy markets, and even new jurisdictions.
If you're building in any of these areas, reach out to us at info@electriccapital.com.
Personal Software
For the first time, individuals can build software tailored precisely to their needs, rather than being limited to corporate offerings. As AI agents now handle complex workflows—reading emails, scheduling meetings, managing files—new demands arise for data privacy, ownership, and persistence. Cryptographic systems can make these tools private, persistent, and capable of multi-user collaboration.
Ideas we want to fund:
Private AI Agents: People need secure ways to run AI on sensitive data.
Possible forms: An AI assistant that automates personal workflows while preserving privacy. Connects to health and financial records to deliver AI insights. Models run in trusted execution environments (TEE) or compute networks; incoming queries are anonymized. Providers or attackers cannot see your data when responses return.
Encrypted Collaboration Spaces: People need private collaboration with others—including humans and agents. Remember: “the cloud” is just someone else’s computer.
Possible forms: Shared workspaces for friends, families, or small businesses. Financials, documents, and tasks sync via peer-to-peer (P2P) storage. Selective disclosure allows agents access to specific data types. No account creation required. No company can read, store, or train on sensitive data. Works offline.
Desktop Agent: People need automation for data on their local machines.
Possible forms: An agent running locally on your desktop that reads emails, drafts replies, creates agendas, and manages your life. Could evolve into a new kind of desktop OS for an AI-first world.
Private Payment for Services: People need ways to pay for software services without identity disclosure.
Possible forms: Buy VPNs, games, cloud storage, or AI compute without accounts. Pay per usage, metered by the service, settled in stablecoins via x402 or similar protocols. The service knows someone paid and how much—but not who.
Agent-Focused Infrastructure
Agents will write most of our code and perform most knowledge work. Key implications: (1) Software tools must be rebuilt from scratch—AI-generated code introduces new failure modes. (2) Development shifts inward, as custom software becomes economically viable. (3) Agents need new rails to transact with each other. (4) Labor-constrained businesses can suddenly scale. These ideas capture second-order opportunities from these shifts.
Ideas we want to fund:
AI-Native Compute Infrastructure: Companies need infrastructure-level capabilities to test, isolate, and roll back AI-generated changes.
Possible forms: AWS or GCP rebuilt for agents. Agents write code in sandboxes, safely test against production data, and deploy with automatic rollback if issues arise. The entire pipeline assumes code originates from agents, not humans.
End-to-End Product Development Tools: Non-technical employees need to go from idea to working software.
Possible forms: A platform where users specify business goals, data sources, and desired outcomes. The system generates plans, designs, code, and runnable products. Eliminates need for technical translation—non-technical users go from “idea” to “deployed product” in hours, not months.
Agent-Enabled Commerce: Agents need to autonomously buy and sell without human identities or bank accounts.
Possible forms: An API marketplace where agents purchase services from other agents. Discovery, negotiation, and pay-per-call use protocols like x402, settled instantly in stablecoins.
Data Networks and Marketplaces: AI needs data infrastructure that compensates contributors and gives them control over usage rights.
Possible forms: A network where users share medical records, spending patterns, investment behavior, or creative works for AI training. Contributors set permissions and earn when their data improves models. AI companies get clean, traceable financial data.
Scaling Professional Services: Service businesses need AI-native operations to scale beyond labor constraints.
Possible forms: A law firm where every lawyer has an AI assistant for research, drafting, and document review. A firm serving 1,000 clients can now serve 100,000. Any client-facing profession—lawyers, architects, marketers, accountants, financial advisors—can be restructured around AI.
Fintech & DeFi
Over 4 billion people and millions of businesses facing currency risk are actively using stablecoins to access the US dollar—representing the largest expansion of dollar network effects in decades. As stablecoins grant global individuals dollar access—growing from $3B in 2019 to over $300B today—millions of new dollar holders need more than digital cash. They need yield, investment opportunities, and financial services. Growing opportunities exist in financial products that give users ownership and global access.
Ideas we want to fund:
Non-Crypto Correlated Yield: Stablecoin holders need yield that doesn’t drop when Bitcoin (BTC) price falls.
Possible forms: A platform bringing real-world infrastructure yield to stablecoin holders. Returns could come from data center project bonds, solar installations, or EV charging networks—predictable cash flows uncorrelated with crypto markets.
Globally Accessible Equities: Global investors need low-friction, low-cost direct access to overseas opportunities.
Possible forms: A financial product replicating equity ownership with price exposure, no funding rate, and no expiry. A trader in the Philippines can build a portfolio of U.S. tech stocks; a Canadian can gain exposure to Korean semiconductors.
New Forms of Insurance: Businesses need fast, transparent coverage for operational risks not served by traditional insurance.
Possible forms: A platform using prediction markets to create new insurance products. A hotel chain can buy hurricane protection for its Florida properties; a ski resort can hedge against warm winters. Capital providers supply liquidity in exchange for uncorrelated returns.
On-Chain Commodities Markets: Commodities need markets with 24/7 trading, instant settlement, and global access.
Possible forms: A market for trading energy storage capacity. Battery storage is a natural entry point—data centers need reliable power and are investing in storage to reduce grid dependence and integrate renewables. Data centers with excess storage can sell it to neighboring facilities during peak demand. Grid operators can trade capacity based on seasonal needs.
Protected DeFi Assets: Institutions need to deploy assets into DeFi that remain secure even if hacked.
Possible forms: A wrapped version of ETH that can be revoked if the protocol is exploited (e.g., GuardedETH). A trusted committee reviews exploits and can reverse GuardedETH transactions while underlying ETH remains unmoved. Legitimate transactions proceed normally.
Finance as Entertainment
Younger generations see financial markets as a meritocratic alternative outside traditional paths. When they engage, they reimagine markets as entertainment. They trade like playing games: fast feedback loops, high adrenaline, in easy-to-access markets. Fast-turnover products like zero-days-to-expiration options (0DTE), which settle within hours, now exceed 55% of S&P 500 index option volume. Prediction markets—where anyone can bet on headlines—reached $44B in volume in 2025, up 5x year-over-year. They also turn trading into content: positions discussed in real-time on Discord, P&L shared on TikTok, portfolios reviewed on Twitch. When markets become entertainment, huge opportunities emerge for platforms that treat financial data as engaging, participatory content—for users, by users.
Ideas we want to fund:
Spectator Capital: Live audiences need economically meaningful ways to participate in outcomes.
Possible forms: A platform letting viewers stake on live content. Engagement becomes more exciting, but currently viewers are limited to tipping and subscriptions. This platform lets reality show watchers stake on who gets eliminated—or follow along with a streamer’s trades via copytrading.
Opinion Markets: Prediction markets need venues that settle based on collective belief, not just events.
Possible forms: A platform generating ranked lists through markets. Users take positions on how others will rank items. The platform creates lists like “Best pizza in NYC,” “Top wines under $20,” “Most influential movies of the last decade,” or “Best AI dev tools”—all market-ranked. Lists settle weekly based on staking weight.
Drama Launchpads: Since individual storytellers can produce episodes cheaper than studios, they need funding and distribution.
Possible forms: A user-generated content (UGC) platform for short dramas. Creators use AI video tools to make series: mafia boyfriend sagas, secret billionaire exposés, revenge thrillers. Fans unlock episodes and tip creators directly with tokens. Creators earn based on views. ReelShort generated over $700M in Q1 2025 with low-budget studio-style productions. This platform combines YouTube’s UGC model with ReelShort’s video format.
Metaverse Revival
Building immersive digital worlds is now economically viable. In the past two years, AI models for images, video, and simulation have advanced rapidly, slashing asset and environment creation costs. Individual creators can now build what once required full game studios. At the same time, demand for personalized, interactive content is surging: Dispatch—a “choose-your-own-path” TV/game hybrid—sold 3.3 million copies in 3 months, earning $85M with a 98% approval rating. Roblox’s daily active users grew 70% YoY, paying creators $428M in Q3 2025 alone. Personalized, AI-driven character chat apps like Character AI show strong early demand for individualized entertainment. These new environments won’t just entertain—they’ll generate rich, structured interaction data for world models and robotics.
Ideas we want to fund:
World Compiler: Individual creators without technical skills need tools to turn natural language into fully interactive 3D environments.
Possible forms: A platform that converts natural language into complete interactive 3D worlds. Building 3D environments still requires expertise in modeling, physics, and NPC behavior—AI can remove this barrier. A creator describes a world, and the system builds it. Assets, physics, NPC logic, and memory are all handled automatically. Individuals deliver rich virtual worlds in days, not years.
Procedural Narrative Engine: Players need stories that adapt to them and never end.
Possible forms: A platform that generates real-time, personalized storylines. Linear stories always end, but players want experiences that evolve with them. A user enters a detective universe where every case is unique. Characters remember past interactions, plot twists respond to choices, and stories never run dry.
World-as-Dataset Platform: World models and robotics systems need diverse interaction data. Consumer-grade immersive environments generate this data continuously—but no one is capturing it yet.
Possible forms: A VR game where every player interaction is instrumented. How users move through rooms, pick up objects, and interact with characters becomes training data for robots. Users opt in, set data-sharing permissions, and get compensated. AI companies gain real human behavior data they can’t synthesize.
New Crypto Primitives & Applications
Crypto primitives are no longer theoretical. Proof-of-Stake (PoS) and Proof-of-Work (PoW) have proven resilient at scale. Zero-knowledge (ZK) proofs are moving from research to production. Fully Homomorphic Encryption (FHE) is becoming faster and easier to use. As these foundational technologies mature, they open new possibilities for developers to build systems that prioritize privacy, embed real-world inputs into consensus, and support collaboration for legacy systems like energy markets or governments.
Ideas we want to fund:
Human Time as Consensus: Blockchain networks need consensus mechanisms anchored in human effort—not just capital.
Possible forms: “Proof of Useful Work,” where consensus requires completing externally valuable tasks—like labeling data or verifying real-world events. Participation rights derive from demonstrated capability, not just staking.
Physical Resource Networks: Small infrastructure operators need coordination systems that make contributions economically viable.
Possible forms: An energy network where production or storage capacity determines consensus weight—aligning grid stability with network security. Sensor networks anchored in physical measurements like weather, water quality, or infrastructure monitoring.
Privacy-Native L1s: Healthcare, enterprises, regulated finance, and many industries need blockchains with default privacy.
Possible forms: Confidential state machines that compute on encrypted data by default. Most blockchains are transparent, but many entities—healthcare providers, corporations, regulated institutions—cannot legally operate on transparent chains. Validators verify transactions via ZK-native architectures or FHE-based execution environments—without seeing transaction contents.
Use-Case Specific FHE: Institutions often need to collaborate on data without revealing it to each other.
Possible forms: Banks detecting suspicious patterns across institutions without sharing customer data. Each bank runs FHE queries on encrypted data from others. They identify accounts linked to the same suspicious entity—without exposing their customer lists.
Energy Contract Settlement: Traditional markets need crypto rails for 24/7 settlement between parties. Deregulated energy markets are a strong entry point—as AI-driven energy demand exposes outdated, strained systems.
Possible forms: A shared settlement layer for energy contracts in deregulated markets. Delivery data triggers automatic payments. Suppliers see cash flow in real time. Brokers receive splits instantly. No single centralized party controls the ledger.
Crypto-Native Jurisdictions: Special economic zones and frontier regions need new thinking on governance and financial infrastructure.
Possible forms: A jurisdiction built from day one on crypto rails. Features include on-chain identity, programmable courts, tokenized capital markets, and regulation-by-smart-contract.
About Electric Capital
Electric Capital is an early-stage venture firm with six funds and $3B in assets under management. Founded in 2018 and led by engineers, we have deep expertise in cryptography, distributed systems, machine learning, incentive design, market dynamics, and privacy-preserving technologies. Over 30% of our team are former founders who launched eight companies (six acquired) and shipped products used by billions.
We’ve invested in over 50 startups with a combined market value exceeding $50B. At Electric, we are investors in leading companies including Anchorage, Aven, Bitnomial, Bitwise, EigenLayer, Ellipsis, Kraken, Monad, Re, SF Compute, Solana, and Spruce. Prior to joining Electric, our partners were early investors in Airtable, Boom Supersonic, Cruise, Figma, Notion, and Pulley.
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