Editor's Note: The article evaluates the performance of multiple encrypted AI projects in terms of ecosystem construction, product iteration, community distribution and token value, and believes that Virtuals is the strongest in terms of speed and heat maintenance. Although CreatorBid is slow in execution, it has a clear vision 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 consumer scenarios in the future.

The following is the original content (the original content has been reorganized for easier reading and understanding):

It has been about 7 months since the AI ​​Agent craze began. The wave started with the birth of @truth_terminal ➙ @pmarca invested in it ➙ Someone issued a token for it ➙ It started to promote the token ➙ @virtuals_io launched an agent tokenization platform ➙ AIDOL and conversational agent phase ➙ alpha agent phase, @aixbt_agent rises ➙ framework phase, @elizaOS (formerly ai16z) launched the open AI developer movement ➙ Small-scale AI x game attempts (but no one survived) ➙ DeFAI phase (vision is still strong, but execution is insufficient)

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

Evolved from these stages, there are a few reliable AI agent teams - they are still active and continue to launch new products and new features (although they are mainly maintained by the transaction fee income accumulated in the early stage).

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

The role of ecosystem leaders

These ecosystem leaders provide extremely valuable support:

· Have a strong distribution network that can bring attention to your token and project;

· Provide product/service integration with the core of the ecosystem (that is, facing potential users);

· Provide 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 pillars. Because community is a core component of the crypto world - community is key to whether a token can form a network effect (unlike traditional SaaS models that rely on subscription fees, Web3 projects rely on tokens to incentivize participation, accelerate growth and user adoption).

In the past 7 months, we have seen multiple ecosystem leaders rise and fall. But those projects that are still active stand out in the following aspects: · Positioning as an app store for AI Agents, developers/users can access Web2 and Web3 services to enhance or automate their workflows - @arcdotfun · Building an economy where autonomous agents trade with each other (and with humans) - @virtuals_io · Leading the largest Web3 open AI movement - @elizaOS · Combining Bittensor's subnet intelligence with AI Agent workflows to attract more people to join the @opentensor (Bittensor) ecosystem - @creatorbid This article will objectively analyze what each ecosystem does well, who is leading, who is lagging behind, etc.

We will analyze from the following aspects:

·Products and Distribution

·AI / Intelligence

·Development Speed

·Token Value Capture

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

Products and Distribution

In Web3, the token itself is often considered a product. But in this article, we define “product” as a good or service that meets actual user needs.

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

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

Virtuals

@virtuals_io has the most diverse products in the ecosystem - including alpha signals, terminals, on-chain/off-chain data, proxy workflows for audits and security analysis, robots, investment DAOs, trading agents, prediction agents, sports analysis, music, DeFi, and more.

Virtuals is arguably the strongest in storytelling and shaping narratives, and is also the team that is best at listening to community feedback and iterating quickly (it can be called "the strong ones who survived").

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

Virtuals was the first player to pioneer the launch of an AI Agent launch platform, allowing anyone to publish a conversational agent and bind a token. This mechanism is a double-edged sword - Virtuals can charge fees and extract value from these launches in the early stages, but because anyone can publish, it attracts a large number of short-term speculators and value harvesters, who may repeatedly issue coins or even run away directly after going online.

(Although Virtuals is developing ACP, hopefully we'll see some flagship proxy products and services soon)

Arc

Players like @arcdotfun have taken a completely different path.

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

In addition, they will also launch a "Ryzome Canvas" code-free/node-based Agent building 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 launch them through Arc's Forge (its launch platform).

(In short, Arc takes the route of "polishing the product first, then talking about distribution". Ryzome will soon be open for testing.)

Eliza

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

Eliza supports a variety of integrations, such as secure execution through TEE, trading, 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 indicators (KPIs) to collaborate on tasks (such as trading, social media automation, business process automation).

Because of this, Eliza's user base continues to grow, and it 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 did not catch the heat and traffic dividends in the early stages of AI Agent's takeoff (at the end of last year).

That changed a few weeks ago when Eliza launched @autodotfun, a SOL-denominated launchpad (with $ai16z liquidity pools in the next phase) and a commitment to use part of transaction fees to buy back $ai16z tokens.

But so far, autodotfun has not been able to differentiate itself from other launchpads and has yet to see any truly interesting or unique projects come online, which is a bit disappointing.

(Eliza's biggest strengths and weaknesses are actually @shawmakesmagic: Without Shaw's countless high-intensity input, this framework would not exist at all; but he also often "powers off and crashes" and makes some questionable decisions, leading to market FUD, which has happened many times.)

AI / Intelligent Capabilities

As mentioned earlier, most of the time, the market pays more attention to "products" and "distribution" rather than the underlying architecture or AI model itself.

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

For example: a model trained specifically for on-chain data will be stronger than a general model in analyzing on-chain information; a model trained based on sports game data, crowd intelligence, and real-time data will also have an advantage in predicting game results.

Bittensor is still the largest ecosystem with the most diverse intelligent models, and the only one truly committed to combining Bittensor subnet intelligence with AI Agent/Agentic workflows is @CreatorBid.

This team did not perform well in distribution (slow to launch new agents and slow iteration pace), but has a clear goal of "firmly supporting Bittensor". (They haven’t officially announced it yet, but they may launch a subnet called SN98 Creator to further incentivize the construction and launch of agentic workflows based on Creatorbid.)

Development speed / user growth / project launch rhythm

In Web3, if you are working on a long-term product, you must think about how to keep the community involved in the short and medium term.

If you can’t "entertain" the community, the token price will tend to fall over time because no one wants to be stuck 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 regard, developing publicly, fixing problems quickly, actively listening to community feedback, and regularly launching new features or narratives 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 cooperation with multiple L1/L2. Eliza is also the preferred framework for deploying agents on other chains (non-Solana). autodotfun also provides an easier path to launch for projects.

Arc's Ryzome and Ryzome Canvas are underway. Once released, they may drive the ecosystem back to high demand and may also activate the release of more Forge projects.

In terms of Creatorbid, the top agents have recently launched new features (although the valuation range has not changed much). CB may be preparing to launch an agent driven by the Bittensor subnet 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 token with the strongest value capture. It is the main currency built by LP in the Virtuals ecosystem, and agents entering Virtuals also need to use it. The recent Genesis Launch introduced Virgen points, which will flow to $VIRTUAL and other ecosystem tokens, further increasing the holding value of $VIRTUAL.

$ai16z may be the second strongest. autodotfun has a daily trading volume of 2 million to 3 million US dollars (still far lower than Virtuals and other platforms), and part of the fees are used to repurchase $ai16z. But Eliza needs to launch high-quality projects as soon as possible, especially projects with a market value of more than 10 million US dollars, otherwise the focus will still be on Virtuals.

$arc's value capture comes from LP transaction fees and the income stream generated by developers on Ryzome in the future. However, this path is still in its early stages and will take time to land.

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

Summary:

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

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

Whether they can maintain the heat for a long time and transform it into real product strength is worth observing in the future.

Although @CreatorBid's execution needs to be improved, I personally like them the most because their vision is consistent with mine - introducing high-quality AI to the public and truly commercializing agentic workflows.

Imagine: an evolving trading signal system that continues to outperform the market, and then transforms it into a fully automated trading agent - this is the idea of ​​SN8 Proprietary Trading Network.

It is still early in the market, and it is not clear who will win in the end. More complex use cases are being handled by large teams outside the ecosystem, such as: ·@vana - Focus on data ownership ·@NousResearch - Reinforcement learning ·@TheoriqAI - Liquidity provision system ·@gizatechxyz - Focus on financial/stablecoin related agents ... Perhaps we will see AI products that are truly consumer-oriented and generate real revenue, rather than short-term speculative bubbles supported purely by "degens speculation".