Original title: The Rise of Web3 AI Apps

Author: 0xJeff, manager of Steak Studio; Compiler: 0xjs@金财经

The AI ​​​​agent industry has been characterized by personality since the beginning. Since its inception, AI has made great progress. Initially, we were attracted to agents that could entertain us, make jokes, or just "create the mood" on CT. These agents attracted attention and generated hype, but as the market grew, one thing became clear: value and utility mattered far more than personality.

We have seen countless personalized agents launched with much fanfare, only to become irrelevant because they failed to provide any engagement beyond surface level. This trend highlights an important lesson - Web3 prioritizes substance over spectacle, practicality over novelty.

This evolution mirrors a similar shift taking place in Web2 AI. Specialized LLMs are increasingly being developed to handle niche use cases ranging from finance to legal, real estate and more. These models focus on accuracy and reliability, making up for the shortcomings of general AI.

The challenge with general AI is that it can often only provide "good enough" answers, but this is not always acceptable. For example, a popular model might be correct 70% of the time on a specific segmentation problem. That's fine for day-to-day use, but terrible in high-stakes scenarios, like whether you win a lawsuit or lose millions on a financial decision. This is why professional large models (LLMs) fine-tuned to achieve 98-99% accuracy become crucial.

This brings us to a key question: Why Web3? Why not let Web2 dominate the professional AI space?

Web3 provides several advantages that traditional Web2 AI cannot match:

1. Global liquidity

Web3 allows teams to raise funds more efficiently. Through token issuance, AI projects can gain access to global liquidity without months of VC meetings and negotiations. It democratizes financing and gives developers the resources they need to build faster.

2. Accumulate value through token economics

Token economics enables the team to reward early adopters, incentivize holders and maintain its ecosystem. For example, Virtuals allocates 1% of transaction fees to cover inference costs, ensuring that its agents remain functional and competitive without relying on external funding.

3. DeAI infrastructure

Web3 provides open source models, decentralized computing (from the following players: Hyperbolic and Aethir) and access to a large number of open data pipelines (cookie.fun, Vana) provides a collaborative and cost-effective foundation that is difficult to replicate in Web2

More importantly, it fosters a passionate community of developers working together to drive innovation.

In the world of Web3 AI agents, we are starting to see ecosystems improve their capabilities through integration, unlocking entirely new use cases. From Bittensor Subnets to Olas, Pond, and Flock, the ecosystem is creating more interoperable and powerful agents. At the same time, easy-to-use tools are emerging to enhance functionality, such as SendAI’s Solana Agent Kit or Coinbase’s CDP Development Kit

The following ecosystems are building utility-first AI applications:

Alchemist AI: A no-code builder for AI applications.

Myshell: An AI app store focusing on image generation, visual novels and waifu emulators.

Questflow: A multi-agent orchestration protocol (MAOP) that enables productivity-enhancing use cases . Questflow’s integration with Virtuals creates a Santa agent that gamifies airdrops and manages incentives.

0xCapx: A practical-first AI app store on Telegram.

In addition to ecosystems, individual agents are becoming experts in specific fields:

Corporate Audit AI: A financial analyst AI agent that reviews reports and identifies market opportunities.

CPA Agent: Developed by @RealTjDunham, this agent calculates crypto taxes and generates reports for users.

This shift from “chatbots chattering on CT” to “professional experts sharing insights” is here to stay.

The future of AI agents is not random chatbots chattering on CT. Rather, they are expert experts in their field, delivering value and insights in an engaging way. These agents will continue to create mindshare and direct users to real products—whether it’s a trading terminal, a tax calculator, or a productivity tool.

The biggest beneficiaries will be Agentic L1 and the coordination layer.

Agentic L1s: Similar platforms Virtuals and ai16z are raising the bar and ensuring their ecosystem prioritizes quality. Virtuals are still smartL1 is the first choice for physical fitness, and soon, ai16z’s launchpad will join the competition. Agents with only personality are dying out, leaving behind agents that are both useful and engaging.

Coordination layers: These layers, like Theoriq, will coordinate large numbers of agents, combining their strengths to provide users with seamless, powerful results. Imagine bundling agents like aixbt, gekko, and CPA together to capture alpha, execute trades, and handle taxes in one cohesive workflow. Theoriq’s task-based discovery framework is a step toward unlocking this collective intelligence.

The story of utility-first AI applications has only just begun. Web3 has a unique opportunity to carve out a space where AI agents can not only entertain, but also solve real problems, automate complex tasks, and create value for users.

In 2025, we will witness a shift from chatbots to co-pilots, as professional LLM and multi-agent orchestration will redefine how we think about AI. Web2 and Web3 will converge, but the open, collaborative nature of Web3 will lay the foundation for some of the most innovative breakthroughs.

This is no longer about “AI agents with personalities” but about agents that provide utility and create meaningful impact.

Please pay close attention to Agentic L1, orchestration layer and emerging AI applications.

The era of intelligent agents has arrived and has just begun.