The Gaps in Virtuals
Lessons from Its Users
Listening to the Frustration
Every bold idea starts with flaws. The Virtuals Protocol is no different. It introduced something transformative: a decentralized platform where anyone can create AI agents with token economies. But after analyzing over 12,000 messages from the Virtuals support group, one thing becomes clear—users are frustrated.
That frustration isn’t a failure; it’s a signal. It shows where Virtuals falls short and, more importantly, where there’s an opportunity for builders to create something better. By understanding these gaps, we can learn what the next generation of decentralized platforms needs to succeed.
1. Lack of Verification for Agents and Tokens
The Virtuals ecosystem is open, but that openness has a cost: anyone can create agents or tokens without verification. This creates a playground for scams and impersonations.
“How do I know this agent is legitimate? It looks like it’s pretending to be part of a well-known brand, but I can’t find any verification.”
“There are so many fake tokens here. Can’t Virtuals implement a way to check who’s behind these projects?”
Trust is the foundation of any economic system. Without it, users hesitate to engage, and legitimate creators are drowned out by bad actors. A verification framework isn’t optional—it’s essential.
2. Barriers for Non-Technical Users
Virtuals lowered the barrier to entry for creating agents, but not enough. Non-technical users still find the process intimidating, with confusing tools and steep learning curves.
“I’m not a developer, but I want to create an agent for my business. The instructions are confusing—can you simplify this?”
“I tried following the guide, but I got stuck on the part about training the agent. Are there tools for people like me who don’t code?”
Usability drives adoption. If the tools aren’t accessible to non-technical users, the ecosystem’s growth will be capped. The next iteration of this model needs simplicity at its core.
3. Scams and Exploitation of Token Launches
Without safeguards, token launches on Virtuals have become a target for sniper bots and rug pulls. These exploits leave users frustrated and disillusioned.
“A bot just sniped all the tokens from the launch I participated in. What’s the point if normal users can’t even buy?”
“I invested in a token that was hyped in the community, and now the creator disappeared. Is there no protection against rug pulls?”
Fairness isn’t just a nice-to-have; it’s essential for creating a sustainable ecosystem. Builders need to implement tools that ensure fair participation and discourage bad actors.
4. Fragmentation and Lack of Interoperability
Virtuals agents are siloed. They struggle to interact across platforms like Telegram, Discord, and Twitter, limiting their utility and scalability.
“Can I make my agent work on both Telegram and Discord? Right now, it seems like I need to create separate versions.”
“Why can’t agents share information across platforms? It’s frustrating that they feel so isolated.”
Interoperability isn’t just a technical challenge; it’s an economic one. Agents that can seamlessly operate across platforms create network effects, making the entire system more valuable.
5. Inadequate Support for Long-Term Projects
Virtuals currently incentivizes short-term speculation over sustainable growth. Builders who want to create meaningful, lasting projects often find themselves at a disadvantage.
“Why do short-term projects with no substance get so much attention? We need better ways to highlight serious developers.”
“Is there a way to encourage creators to stick around? So many agents are abandoned after they launch.”
Aligning incentives with long-term success will be crucial for future platforms. Systems that reward sustainability over hype will foster a healthier ecosystem.
6. Insufficient Tools for Agent Training
Training agents on Virtuals is difficult due to limited access to high-quality datasets and tools. This leads to underperforming agents and frustrated creators.
“What data can I use to train my agent? I don’t have access to good datasets, and it’s limiting what I can do.”
“Are there any tools to validate datasets before training? My agent is giving weird responses after I used a public dataset.”
Better training tools and marketplaces for curated datasets could drastically improve agent quality and user satisfaction.
7. Poor User Education and Onboarding
Many users struggle to get started with Virtuals because of insufficient guides and tutorials.
“I’ve just joined, but I can’t find a clear tutorial on how to get started. Where’s the step-by-step guide?”
“The documentation doesn’t explain how to troubleshoot issues. I’ve been stuck for hours trying to fix this.”
Onboarding isn’t just about documentation—it’s about building confidence. Clear guides, tutorials, and support systems can make all the difference.
What Builders Can Do
The frustrations voiced in the Virtuals support group aren’t just problems—they’re opportunities. Here are seven actionable ideas builders can start working on today:
Verified Agent and Token Registry: Create an on-chain system to verify agents and tokens, ensuring accountability and trust.
Low-Code Agent Builder: Develop a drag-and-drop platform for building and training agents without coding.
Anti-Bot Launch Protection: Implement mechanisms like whitelists and rate limits to prevent sniper bots from dominating token launches.
Interoperability Framework: Build middleware that allows agents to seamlessly interact across platforms like Telegram, Discord, and Twitter.
Scam Detection and Reporting Tool: Create a tool that flags suspicious activity and allows users to report scams.
Dataset Marketplace for Agent Training: Build a marketplace where contributors can upload, sell, and buy high-quality datasets for agent training.
Incentive Alignment Platform: Design reward systems that encourage long-term project sustainability over short-term speculation.
Turning Frustration into Progress
The 12,000+ messages I analyzed from the Virtuals support channel reveal a system full of potential but plagued by avoidable issues. These gaps—lack of trust, usability, interoperability, and incentives—are a blueprint for the next generation of platforms.
Virtuals is the first draft of the AI agent economy. It showed us what’s possible and what’s missing. The builders who fix these flaws won’t just create better platforms; they’ll define the future of decentralized AI.
The opportunity is there. The question is, who will seize it?