AI Agents Beyond Trading: The Untapped Potential of Web3 Community Assistants

Most AI tools in Web3 today are built for one thing: trading.

Blake Minho Kim

Co-Founder

Most AI tools in Web3 today are built for one thing: trading.

You’ve got bots that track token prices, manage liquidity, or pump out memes on Twitter. That’s what everyone’s focused on. And sure, those bots have value. But they don’t help users actually use Web3.

They don’t help someone new understand how a DAO works.

They don’t help a community member find the latest proposal or get involved.

They don’t guide a builder through joining an ecosystem.

And that’s where I see the real opportunity.

AI in Web3 Today is Too Narrow in Scope

Web3 is growing into something way bigger. DAOs, community-led ecosystems, decentralized platforms—it’s not just about finance anymore. But AI hasn’t caught up. It’s still built for markets, not people.

Right now, AI in Web3 is one-dimensional. It automates trades and maybe helps with market-making. But it doesn’t solve the real friction points I see every day:

  • People don’t know how to get started.

  • Governance is confusing, so they don’t vote.

  • Communities rely on moderators answering the same questions over and over.

And yet, Web3 is expected to grow from [$4.6B in 2025 to nearly $100B by 2034](https://www.precedenceresearch.com/web-3-0-market#:~:text=The global web 3.0 market size is calculated at USD 4.62 billion in 2025 and is forecasted to reach around USD 99.75 billion by 2034%2C accelerating at a CAGR of 41.18%25 from 2025 to 2034.). That kind of growth won’t happen if people can’t figure out how to engage.

So the question is: how do we fix that?

AI Agents That Support Community

When I talk about AI agents, I don’t mean a chatbot that answers three questions and loops you back to the docs.

We’re thinking about something more useful, like a real community assistant. Something that helps people understand what a project is, what it’s trying to do, and how to get involved.

There are people trying to join, but they don’t know where to go, what to read, or who to ask. That’s a problem.

So here’s what this agent needs to do:

  • Guide new users through onboarding

  • Explain how governance works in plain terms

  • Point people to the right resources

  • Flag when it’s time to vote or participate

  • Help communities stay organized and active

It’s here to support the people already doing the work—the community leads, contributors, and DAO members who keep everything running.

We’ve already been thinking about this internally at Myosin. It’s been on our roadmap for a while. And in my view, this is the kind of tool that Web3 needs if we’re serious about scaling participation.

What These Agents Actually Solve

The vision I have for AI agents comes straight from what I’ve seen over and over again inside Web3 communities. These are the pain points we run into every day.

People want to be involved—they just don’t know how. Community AI agents can step in by helping with:

  1. Onboarding: People are interested in Web3 but get stuck on the first step. AI can guide them through setup, joining a DAO, or claiming their first token.

  2. Governance: Voter turnout is low because proposals are complex and hard to follow. AI can summarize, highlight important discussions, and notify users when their input is needed.

  3. Engagement: AI can automate interactive experiences, surface relevant content, automate updates, and even help with reward systems like airdrops or reputation points.

  4. Moderation: Communities burn out when moderation is manual. AI can take on routine filtering, flag issues, and help keep things constructive.

None of this replaces people. It supports them.

What We Need to Build

If we want AI agents to help Web3 communities, they need to be more than simple bots. They need to work inside the systems we’re building—not just talk about them.

Here’s what a community agent should be able to do:

  • Know the basics: wallets, staking, DAOs, and governance. It should speak the language users use.

  • Vote, submit proposals, interact with smart contracts, and help users do the same.

  • Show where users are getting stuck or dropping off, and help teams improve the experience.

  • Stay transparent. Every action it takes should be logged on-chain so anyone in the community can see it.

  • Be interoperable. These agents should work across Ethereum, Solana, Cosmos—whatever your stack is.

This is how we stop building tools that just sit on the surface. We need AI that’s built into how communities run—so people can actually use Web3 without getting lost.

What This Changes for Users and Teams

The impact of AI-powered community agents will be immediate and transformative:

  1. Onboarding becomes simple. No more ten-step guides just to join a community.

  2. Governance gets easier. More voters, more participation, better outcomes.

  3. Community can grow with less friction. AI handles the noise so moderators and core contributors can focus.

  4. Users stick around longer. Because they’re not lost—they’re supported.

We’ve already seen what doesn’t work. Now it’s time to build what does.

Now’s the Time to Build Smarter Tools for Web3

I’ve been saying this for a while—we’re just getting started.

AI that helps people navigate Web3 will be more valuable than AI that helps them trade it.

Trading bots are fine, but the real shift will come when AI is embedded in the user journey. Helping people learn, participate, contribute, and stay involved.

This is what we’ve been thinking about at Myosin.

This is where I think the space is headed.

And this is what I’m excited to build next.

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