With over 50 projects participating, how is the quality of Cookie's DeFAI hackathon?

DeFAI ≠ Abstract Layer, Focus on Unlocking New Possibilities Rather Than Replicating Existing Functions.

Written by: Defi0xJeff, Head of Steak Studio

Translated by: Ashley, BlockBeats

Editor's Note: The author summarizes insights and reflections after browsing over 50 Cookie DeFAI hackathon projects, pointing out the potential and market gaps of DeFAI Agents, especially the rise of vertical Agents and the lack of research Agents. The author believes that Cookie, as a data platform, is driving the development of innovative projects and suggests that teams should focus on new use cases rather than replicating existing functions. DeFAI is expected to become an important vertical market in the crypto space, potentially competing with Web2 Agents in the future.

Below is the original content (reorganized for better readability):

After browsing over 50 Cookie DeFAI hackathon projects, here are my takeaways (this is more like feedback / my current views on the Agent market / how projects stand out).

Current Situation: DeFAI = Abstract Layer for Many Developers

Many teams have added NLP interfaces to their products (possibly because they think DeFAI is equivalent to @HeyAnonai, @griffaindotcom, @orbitcryptoai, @askthehive_ai). In most cases, this is not appropriate—especially when you can only do some simple things, like using the Cookie API to find the influence of the top 5 AI Agent tokens, looking for trending top coins, etc. This is just a mini feature that many top abstract layers already have.

I believe it would be better to directly use the Cookie dashboard to view these analyses rather than adding a new interface—it is not comprehensive enough.

DeFAI ≠ Abstract Layer

Instead of replicating existing functions, teams should focus on leveraging the Cookie API to unlock new possibilities—driving entirely new use cases and vertical fields rather than drawing inspiration from existing domains.

The Birth of Vertical Agents

I was surprised by many interesting ideas that emerged from this hackathon—several projects have unique concepts. Although many projects are still in the early demonstration/concept stage, they paint an exciting picture of future use cases.

An Agent that helps preserve your legacy—checks if you are safe, and if you pass away, it takes action to fulfill your wishes.
An ETF/index fund that uses Cookie analysis for investment decisions and comprehensive research reports. • Agent security analysis and Agent security scoring.
A ChatGPT-like product/developer learning center that helps developers understand everything about Solana.
A DYOR layer that tracks analyst/KOL calls, DYOR, and copy trading.
A framework that allows Agents to enter into contracts, enabling complex interactions between Agents or between Agents and humans (unsecured loans, employment agreements, alliances/coordinations).
Personalized +DeFAI Agent—an AI companion that adjusts its behavior/visuals based on market dynamics.

More and more teams are launching Agents in niche areas, not just "trading Agents" or AI-driven dashboards/research Agents. Launching vertical Agents makes it easier to distinguish them from general Agents.

Trading Agents already have leading players. Although this field is still in its infancy, it remains difficult to stand out—especially in the early stages. Focusing on vertical Agents would be better.

Many may think @HeyTracyAI is @virtuals_io's flagship Agent on Solana, which is useless and cannot help you make money. In fact, an Agent built like a real business—solving real problems—will perform better in the long run. The sports market is a huge total addressable market (TAM). Look beyond Web3. (Not promoting Tracy, just presenting a viewpoint on vertical Agents.)

Conclusion: Niche vertical Agents solve real problems and create unique use cases, while general Agents struggle to stand out.

Lack of Suitable Research Agents

Although vertical Agents are opening up unique niche markets, another major gap in this field is the lack of suitable research Agents.

The key word here is "suitable." Currently, there is no research Agent that can replace human information synthesis and reasoning. This applies not only to the projects from the Cookie DeFAI hackathon but also to the general situation of Web3 AI Agents.

Most AI Agents today merely aggregate data but do not synthesize insights like humans. Analyzing data through traditional dashboards, such as @cookiedotfun, @GoatIndexAI, @Decentralisedco, and using Grok, is still better than letting AI Agents "feed" Web3 AI Agents "insights."

Despite many abstract layers and teams focusing on enhancing research capabilities, there remains a clear gap. Whoever can break through this first will gain a significant advantage.

Cookie DeFAI Hackathon Projects

Most hackathon projects are still in the early development stage, and many have not yet been deployed. Since this is a purely DeFAI hackathon (as you can see, DeFAI is the best-performing category among AI Agents), many high-quality projects and tokens will emerge from this event.

As mentioned in the second part, many projects will provide new use cases beyond what we currently understand about DeFAI applications.

As AI Agents continue to evolve as a field, Agents can fill more gaps—such as B2A (Business to Agent) beyond B2B and B2C.

The next wave of DeFAI projects will not only enhance existing use cases—they will create entirely new ones.

Cookie as Data Support and Distribution Channel for Agents

Unlike relying on launch platforms to highlight unique Agent tokens, Cookie empowers Agents and teams by providing a tracking mechanism for on-chain and off-chain AI Agent data support—enabling new and interesting use cases.

At the same time, Cookie's dashboard is already used by over 240,000 MAU, with users deeply engaged in the field. Discovering gems on the Cookie dashboard and Cookie hackathon is like finding a new gem on Virtuals.

Cookie has proven itself to be a powerful distribution channel for Agents. The more Agents leverage this, the faster the ecosystem matures.

Conclusion

This hackathon felt similar to the Solana AI hackathon, but arguably better—because it is purely DeFAI.

DeFAI is not just another AI trend—it has the potential to become the most promising Agent vertical in the crypto space. This hackathon has proven that.

I lean towards DeFAI, believing it is a crypto-native Agent use case that can develop as an independent vertical field and compete with Web2 Agents.

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