Virtuals leads, CreatorBid steals, and takes a look at the latest developments in the AI ​​Agent track

Written by: @Defi0xJeff

Compiled: zhouzhou, BlockBeats

Editor's note: The article evaluates the performance of multiple crypto AI projects in ecological construction, product iteration, community distribution and token value, and believes that Virtuals has the strongest speed and popularity maintenance. Although CreatorBid has a slow execution, its vision is clear and focuses on the Bittensor intelligent agent ecosystem, and its long-term potential is promising. The overall AI agent track is still in its early stages, and the focus may shift to infrastructure and real consumption scenarios in the future.

The following is the original content (to facilitate reading comprehension, the original content has been compiled):

It has been about 7 months since the AI ​​Agent craze began. This wave was initially started by the birth of @truth_terminal➙ @pmarca Invest in it➙ Someone issued a token for it➙ It began to promote the token➙ @virtuals_io launched the agent tokenization platform➙ AIDOL and dialogue agent stage➙ alpha agent stage, @aixbt_agent rise➙ Framework stage, @elizaOS (formerly known as ai16z) initiated the open AI developer campaign➙ Small-scale AI x game attempt (but no one survived)➙ DeFAI stage (the vision is still strong, but the execution is insufficient)

This is roughly a summary of the main stages of the AI ​​Agent track.

Evolving from these stages, there are a handful of reliable AI agent teams—they are still active, constantly launching new products and new features (although mainly maintained by early accumulated transaction fee income).

Most importantly, there are still some ecosystems that are still strong, supporting developers, helping product ideas start from scratch and driving AI products and tokens from conception to successful launch.

The role of the leader in the ecosystem

These ecosystem leaders provide extremely valuable support:

• Have a strong distribution network that can bring attention to your tokens and projects;
• Provides integration of products/services with the core of the ecosystem (that is, for potential users);
• Provides guidance and incubation services from 0 to 1 to 10;
• Support your ideas through investment and funding.

In the field of Web3 AI, ecosystem leaders are still the core pillar. Because communities are the core component of the crypto world - communities are the key to whether tokens can form network effects (unlike traditional SaaS models rely on subscription fees, Web3 projects rely on tokens to incentivize participation, accelerate growth and user adoption).

Over the past 7 months, we have seen multiple ecosystem leaders ups and downs. But those projects that are still active stand out in the following aspects:

• App Store Positioned as an AI Agent, developers/users can access Web2 and Web3 services to enhance or automate their workflows - @arcdotfun
• Building an economy where autonomous agents trade (and with humans) - @virtuals_io
• Leading the largest Web3 open AI campaign - @elizaOS
• Combining Bittensor's subnet intelligence with AI Agent workflow to attract more people to join the @opentensor (Bittensor) ecosystem - @creatorbid

This article will objectively analyze what aspects each ecosystem is doing well, who is leading the way, who is lagging behind, etc.

We will analyze it from the following aspects:

• Products and distribution
• AI/Smart
• Speed ​​of development
• Token value capture situation

Without further ado, let's look at the first aspect:

Products and distribution

In Web3, the token itself is often regarded as a product. However, in this article, we define "product" as a product or service that can meet the needs of actual users.

In the field of Web3 AI, most products revolve around "financialization", which means they are tools and intelligent services that help people make money - such as Alpha terminals, conversation agents that can express emotions about a project, agents that can conduct transactions or forecasts, with the goal of outperforming the market, etc.

Whether the product is successful depends largely on "distribution". Generally speaking, this area is 90% distribution + 10% technical architecture. Few people in the circle care about what model your AI Agent uses. What people are more concerned about is whether its output is stable, the insights it shares, and whether alpha is really useful.

Virtuals

@virtuals_io has the most diverse products within the ecosystem – including alpha signals, terminals, on-chain/off-chain data, agent workflows for auditing and security analytics, robots, investment DAOs, transaction agents, forecast agents, sports analytics, music, DeFi and more.

Virtuals can be said to be the strongest in storytelling and narrative shaping, and is also the best team at listening to community feedback and iterating quickly (can be called "surviving strong people").

However, although they provide a wide variety of services, only a few teams are doing products that can truly provide users with actual value (not just entertainment).

Virtuals is the first player to launch a groundbreaking AI Agent launch platform, allowing anyone to publish conversational agents and bind a token. This mechanism is a double-edged sword - Virtuals can charge fees and obtain value from these startups in the early stages, but since anyone can release it, it attracts a large number of short-term speculators and value harvesters, who may issue coins repeatedly, or even run away directly after they go online.

Arc

Players like @arcdotfun take a completely different path.

Instead of building a "launch platform" and encouraging as many projects as possible to go online, they focus on building the AI ​​Agent market "Ryzome", and integrate the products and services of these projects into their MCP infrastructure by working with a few high-quality projects.

In addition, they will also launch a "Ryzome Canvas" codeless/node Agent build tool, where users can access common MCP server resources, as well as services and use cases provided by Arc partners, and customize the creation of agent workflows (similar to Rayon Labs' Squad tool).

Users can sell these workflows, or tokenize them, and go live through Arc's Forge, which is its launch platform.

Eliza

Among all frameworks, the most flexible and changeable is @elizaOS.

Eliza supports various integrations, such as secure execution through TEE, transactions, analyzing real-time on-chain data, executing smart contracts, managing wallets, etc.

The framework supports multi-agent systems, allowing developers to create a group of agents with different personalities, goals and key metrics (KPIs) to collaborate on tasks (such as transactions, social media automation, business process automation).

Because of this, Eliza's user base continues to grow, and currently has about 16,000 stars and 5,100 forks on GitHub.

However, although Eliza's framework is highly used, it lacks distribution channels at the beginning. Unlike Virtuals, Eliza failed to capture the heat and traffic dividends in the early stages of the AI ​​Agent takeoff (late last year).

This situation changed a few weeks ago – Eliza launched @autodotfun, a SOL-denominated startup platform (the next phase will introduce $ai16z liquidity pool) and promised to use some of the transaction fees to repurchase the $ai16z tokens.

But to date, autodotfun has not shown a significant difference in similar launch platforms, nor has it really interesting or unique projects come online, which is a bit disappointing.

AI/intelligent capabilities

As mentioned earlier, most of the time, the market is more focused on "product" and "distribution" than the underlying architecture or the AI ​​model itself.

But if you have a powerful and evolving smart system, it is still possible to create a more user-centric product.

For example: a model specially designed for on-chain data training will be stronger than a general model in analyzing on-chain information; a model based on sports competition data, mass intelligence, and real-time data training will also have more advantages in predicting game results.

Bittensor remains the largest ecosystem with the most diverse intelligent models at present, and the only thing that is truly committed to combining Bittensor subnet intelligence with AI Agent/Agentic workflows is @CreatorBid.

This team performed poorly in distribution (slowly launching new agents and slow iteration pace), but their goals were clear in the direction of "firmly supporting Bittensor". (They have not officially announced it yet, but may launch a subnet called SN98 Creator to further inspire the construction of agent workflows based on Creatorbid and go online.)

Development speed/user growth/project launch rhythm

In Web3, if you are making long-term products, you must think about how to keep the community involved in the short and medium term.

If you can't "enter" the community, the token price tends to fall over time because no one wants to be trapped for a long time. In contrast, the market prefers projects that can continue to create topics and build publicly.

Virtuals is the strongest player in this field, developing publicly, fixing problems quickly, actively listening to community feedback, and launching new features or narratives regularly to maintain users' continued interest while also building their ACP. In addition, they often have Genesis Launch for new users to participate.

Eliza ranks second in distribution capabilities, thanks to its developer network and its partnership with multiple L1/L2. Eliza is also the preferred framework for other chains (non-Solana) when deploying agents. autodotfun also provides a more relaxed path to the project.

Arc's Ryzome and Ryzome Canvas are underway. Once released, it may drive the ecological popularity to rebound and may also activate the release of more Forge projects.

For Creatorbid, top agents have recently launched new features (although the valuation range has not changed much). CB may be preparing to launch a Bittensor subnet-powered agent and launch its own subnet. The overall pace is slow, and I hope it can be accelerated in the future.

Token value capture

$VIRTUAL is currently the strongest token for value capture. It is the main currency built by LP in the Virtuals ecosystem. It is also necessary to use it for agents entering Virtuals. Recently, Genesis Launch introduced Virgen points, which will flow to $VIRTUAL and other eco-tokens, further increasing the holding value of $VIRTUAL.

$ai16z is probably the second strongest. autodotfun has $2 million to $3 million in daily transaction volume (still far below Virtuals and other platforms), with some fees used to repurchase $ai16z. But Eliza needs to launch high-quality projects as soon as possible, especially projects with a market value of over 10 million US dollars, otherwise the attention will still be focused on Virtuals.

The value of $arc captures the revenue streams generated by LP transaction fees and future developers on Ryzome. However, this path is still in its early stages and takes time to implement it.

$BID's token mechanism is the most unique because the circulation is lower than similar projects, and the platform activity can be incentivized by releasing tokens. But at present, these releases have not been well utilized and the transaction volume is still low ($100,000 to $500,000 per day).

Summarize

Each of the above projects has its own advantages, but in the short and medium term, "distribution ability" + "the ability to attract speculative funds" (i.e. trading volume) is the core moat.

Whether it can continue to create popularity and attract players to continue to bet in your "casino" is the key to the system's operation. In this regard, Virtuals is currently the best performing project.

Whether they can maintain their popularity for a long time and convert it into real product power is worthy of subsequent observation.

Although @CreatorBid's execution ability still needs to be improved, I personally prefer them because their vision is consistent with me - to introduce high-quality AI to the public and truly commercialize agent workflows.

Imagine: an evolving trading signal system that continues to outperform the market and then converts it into a fully automatic trading agent - this is what the SN8 Proprietary Trading Network is thinking.

It is still an early stage in the market and it is not clear who will win in the end. More complex use cases are being processed by large teams outside the ecosystem, such as:

• @vana—Focus on data ownership
• @NousResearch—Reinforcement Learning
• @TheoriqAI - a liquidity provision system
• @gizatechxyz - Focus on finance/stablecoin-related agents

In the future, how the leaders of the AI ​​Agent ecosystem will position themselves and determine whether they can seize the growth opportunities in the next cycle. We may also see more implementation of DeAI infrastructure, deepening the decentralization of proxy systems, and entrepreneurial opportunities at all levels in the technology stack.

Ultimately, speculation may shift from a single agent token to the core infrastructure that builds open AI systems. Perhaps we will see AI products that are truly consumer-oriented and generate real income, rather than short-term speculative bubbles that are simply supported by "degens speculation".