How to seize opportunities early in the AI Agent cycle?

Author: 0xJeff, Crypto KOL

Compiled by: Felix, PANews

Back in October, Virtuals introduced the concept of AI agent tokenization. It was a bold move, but at the time, most people didn't pay attention because it was too ahead of its time.

Now, Virtuals has brought 50x and 100x returns to many agents, and suddenly everyone is starting to take notice.

The problem is that everyone is focused on the 50-100x returns. If you want similar outsized returns, you need to act early. You need strong confidence and patience to position yourself before others have discovered it.

If you enter now, you might see 5-10x returns—still quite stable, but far from the 50-100x returns enjoyed by early adopters. But that doesn't mean it's too late; you need to have strategic vision. The "alpha" from two months ago is no longer alpha. The Virtuals ecosystem is now overcrowded, and the low-hanging fruit has already been picked.

What should you do now?

First, don't limit yourself to one ecosystem. Base and Solana, Virtuals and ai16z don't matter—both ecosystems have opportunities. The key is to stay flexible and seek value, rather than tribalism.

What should you look for when choosing an agent?

Essentially, the key to a successful agent is uniqueness and practicality. Without practicality, the behavior of agent tokens becomes irrelevant like 95% of memecoins after the hype cycle.

Agents need to have unique products that provide tangible value. If the team truly understands the attention game, it can be a bonus:

• Create engaging legends or stories around the agent
• Rapidly and continuously release features
• Actively meet community needs

When these factors are in place, agents have the potential to find product-market fit (PMF), achieving alignment between product and market, and subsequently, teams that continue to execute and innovate (like aixbt) can dominate their niche and become pillars of the ecosystem.

Here are the narratives and practicalities that CT currently values most:

1. Seeking Alpha

There is a high demand for agents that provide trading signals and insights. For example, aixbt focuses on providing valuable alpha to users.

Other noteworthy alpha agents:

• Rei: Offers comprehensive token and sentiment analysis, complete with detailed charts
• Agent Scarlett: Focuses on token analysis, weighing pros and cons and providing insights
• 3σ: Covers complete project segmentation and interpretation
• kwantxbt: Excels in technical analysis, providing trading assistance, continuously monitoring market dynamics, and offering real-time analysis and advice
• $TRUST: Perpetual agent that allows setting entry prices, stop losses, etc.

2. Investing in DAOs

Hedge fund-style DAOs, operated by human or AI agents, utilize their funds for investment.

Examples:

• daos.world ecosystem on Base
• VaderAI, WAI Combinator, sekoia_virtuals, aixcb on Virtuals
• daos.fun ecosystem on Solana

The power of investing in DAOs lies in their provision of:

• Endorsement of high-quality agents
• Distribution channels for portfolio projects
• Early and off-market trading rounds for tokens, often leading to outsized returns

3. On-chain Trading

On-chain trading is a narrative that resonates deeply with the CT crowd, as they are eager to see someone turn $1,000 into $1 million.

It's not just about the money; it's about the excitement of seeing others work hard and succeed.

The first iteration of trading agents will harness this energy. They will focus on portfolio growth, showcasing their frameworks and strategies in real-time. Although this is an early narrative, it is gradually taking shape among some players.

Examples:

• Gekko AI: A self-improving trading agent on Virtuals, utilizing Axal's infrastructure to deliver results.
• Big Tony: Built on Cod3x, focusing on autonomous execution of professional trading.
• Project Plutus: Combines real-time analysis with automated DCA execution.
• On-chain trading agents are expected to be a focal point of market attention in Q1/Q2 2025.

4. Developer-Centric Tools

As ecosystems evolve, the demand for developer tools becomes crucial.

Examples:

• SOLENG: Monitors pull requests, conducts preliminary reviews, and acts as an AI judge for hackathons
• H4CK Terminal: White-hat agents responsible for bounties and vulnerability checks
• CertaiK: Provides security audits specifically for agents

5. Privacy and Confidentiality (TEE)

Trusted Execution Environment (TEE), pioneered by Marvin Tong on Solana and Phala Network, enables fully autonomous agents.

Example use cases/cool experiments:

• aiPool's "Unruggable ICO" (through TEE technology, investors can send funds to an agent, which will calculate and distribute the corresponding amount of ICO tokens in a secure environment)
• SPORE: TEE agents with genetic traits passed down to offspring.
• Neural network experiments, such as DeepWorm.

There are currently no TEE agents on Virtuals, and the first to launch will undoubtedly see its value soar.

6. Gameplay Beyond Narratives

By predicting future narratives in advance, you can achieve returns of over a hundred times. This was the strategy when entering Virtuals with a market cap of less than $30 million.

Emerging narratives for 2025:

• DeFi agents
• NSFW agents (AI companions)
• Robotics
• Data
• Gamification of agents
• Collective/Group intelligence
• Infrastructure