Original Title: The Rise of Web3 AI Apps
Author: 0xJeff, head of Steak Studio; compiled by 0xjs@Golden Finance.
The AI agent industry has come a long way since its initial focus on personality-driven agents. Initially, we were drawn to those that could entertain us, joke, or just 'vibe' on CT. These agents captured attention and generated hype, but as the market matured, one thing became clear: value and practicality far outweigh personality.
We have seen countless personalized agents being heavily marketed upon launch, only to become irrelevant as they failed to provide any engagement beyond the surface level. This trend highlights an important lesson — Web3 prioritizes substance over spectacle, practicality over novelty.
This evolution reflects a similar shift happening in Web2 AI. Specialized LLMs are increasingly being developed to handle niche use cases from finance to law, real estate, and more. These models emphasize accuracy and reliability, addressing the shortcomings of general AI.
The challenge for general AI is that it often can only provide 'good enough' answers, which is not always acceptable. For instance, a popular model might be correct 70% of the time on specific niche questions. This is fine for everyday use, but in high-stakes scenarios, like whether you won a lawsuit or lost millions in financial decisions, it’s problematic. That’s why specialized large language models (LLMs) fine-tuned for 98-99% accuracy become crucial.
This brings us to a key question: Why Web3? Why not let Web2 dominate the professional AI space?
Web3 offers several advantages that traditional Web2 AI struggles to match:
1. Global liquidity
Web3 allows teams to raise funds more efficiently. Through token issuance, AI projects can gain global liquidity without months of VC meetings and negotiations. It democratizes financing and provides developers with the resources they need to build faster.
2. Accumulate value through token economics
Token economics allows teams to reward early adopters, incentivize holders, and sustain their ecosystem. For example, Virtuals allocates 1% of transaction fees to cover reasoning costs, ensuring its agents remain functional and competitive without relying on external funding.
3. DeAI Infrastructure
Web3 provides a collaborative and cost-effective foundation with open-source models, decentralized computing (from participants like Hyperbolic and Aethir), and access to large open data pipelines (cookie.fun, Vana) that are difficult to replicate in Web2.
More importantly, it fosters a passionate developer community that drives innovation.
Web3 AI Ecosystem
In the realm of Web3 AI agents, we are beginning to see ecosystems enhance their capabilities through integration, unlocking entirely new use cases. From Bittensor Subnets to Olas, Pond, and Flock, ecosystems are creating more interoperable and powerful agents. Meanwhile, user-friendly tools are emerging to enhance functionality, such as SendAI's Solana Agent Kit or Coinbase's CDP development toolkit.
The following ecosystems are building utility-first AI applications:
Alchemist AI: A no-code builder for AI applications.
Myshell: An AI application store focused on image generation, visual novels, and waifu simulators.
Questflow: A multi-agent orchestration protocol (MAOP) that enables productivity-enhancing use cases. The integration of Questflow with Virtuals creates Santa Claus agents that gamify airdrops and manage incentives.
0xCapx: A utility-first AI application store on Telegram.
Individual agents focused on real-world use cases
Beyond ecosystems, individual agents are becoming specialists in specific domains:
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 'specialized experts sharing insights' will continue.
The future of AI agents is not random chatbots chattering on CT, but specialized experts in their respective fields providing value and insights in engaging ways. These agents will continue to create share of mind and guide users towards practical products — be it trading terminals, tax calculators, or productivity tools.
Where will the value accumulate?
The biggest beneficiaries will be Agentic L1s and coordination layers.
Agentic L1s: Platforms like Virtuals and ai16z are raising the bar, ensuring their ecosystems prioritize quality. Virtuals remains the preferred L1 for agents, and soon, ai16z's launchpad will join the competition. Agents with only personality are fading away, leaving behind useful and attractive agents.
Coordination layers: These layers, like Theoriq, will coordinate numerous agents, combining their strengths to provide users with seamless, powerful outcomes. Imagine bundling agents like aixbt, gekko, and CPA together to gather alpha, execute trades, and handle taxes within a cohesive workflow. Theoriq's task-based discovery framework is a step towards unlocking this collective intelligence.
Final Thoughts
The story of utility-first AI applications is just beginning. 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.
By 2025, we will witness a transition from chatbots to co-pilots as specialized LLMs and multi-agent orchestration redefine our perception of AI. Web2 and Web3 will converge, but the open, collaborative nature of Web3 will lay the groundwork for some of the most innovative breakthroughs.
It's no longer about 'AI agents with personalities,' but about agents providing utility and creating meaningful impact.
Keep a close eye on Agentic L1s, coordination layers, and emerging AI applications.
The era of agents has arrived, and it's just beginning.