❓ Stop Using "Old" AI Agents that Won’t Really Work, This New "AI-aware” Agent Will Help You Win

Introduction: The Rise of AI Agents in 2025

👉 Last Episode: Your Comprehensive Guide on How $15.5B AI Agent Market Actually Works

The future of AI is agents, say OpenAI, Google and Microsoft, as well as founders of Coinbase, NEAR and EigenLayer. In just a few short months, the AI agent sector exploded from practically nothing to a market capitalization of tens of billions of dollars. It's expected to grow from USD 5.1 billion in 2024 to USD 47.1 billion by 2030, the growth trajectory has been nothing short of remarkable.

It all started in October 2024 when Terminal of Truth launched $GOAT with a $50,000 Bitcoin donation from Marc Andreessen. This sparked a surge in AI agent token launches that quickly attracted massive capital inflows. Projects like $ai16z and $VIRTUAL reached market caps above $2 billion at their peaks.

What's fascinating is how quickly this ecosystem developed. That Virtuals Protocol I mentioned in the previous part, for example, has already generated over $60 million in protocol revenue. And yeah, you might be thinking, "Isn't this just another bubble?". But after months of research, I've identified key differences that set AI agents apart from previous trends:

• First, AI agents provide actual benefits. Unlike memecoins (just a meme of a character) that primarily derive value from collective belief, AI agents can perform useful work, real work.

• Second, AI agent can be backed by real economic value. When an agent generates revenue by performing services, that revenue can flow back to our users, our holders.

• Third, the technology is rapidly maturing. With breakthroughs like DeepSeek-R1's pure reinforcement learning approach, the cost and complexity barriers for developing sophisticated AI models are dropping dramatically. What once required millions in funding and specialized expertise is becoming increasingly accessible.

This guide will give you the knowledge you need to understand and participate in what I believe is the most important technological and economic shift of the decade👇

I. The Technological Breakthroughs Powering AI Agents

1. DeepSeek's Reinforcement Learning Revolution

The biggest game-changer I witnessed in the AI agent space came in late 2024 with DeepSeek-R1's release. What made DeepSeek-R1 revolutionary was its unique training method. Instead of following the traditional approach of supervised fine-tuning (SFT) followed by reinforcement learning (RL), DeepSeek proved that large models can make dramatic leaps in reasoning ability purely through reinforcement learning.

Let me break this down in simple terms:

The traditional method is like teaching a child math by first giving them a workbook with standard solutions (SFT phase), then hiring a tutor to correct mistakes and adjust their approach (RL phase).

DeepSeek's method is radically different - it's like sending the child straight into an exam with no preview or examples. For every incorrect answer, they get immediate feedback, learning through trial and error and independently developing optimal problem-solving strategies.

The results were astonishing. I watched as DeepSeek-R1 developed self-learning, insight, and efficient adaptation capabilities that previous models couldn't match. During training, its response length grew dramatically as it learned to solve reasoning tasks with more thinking time - essentially teaching itself to think more deeply.

For perspective, the DeepSeek-V3 model was trained at a cost of approximately $5.5 to $5.6 million, using 2.78 million GPU hours on 2048 H800 GPUs over about 2 months. That's dramatically cheaper than comparable models like Meta's LLaMA 3.

This has huge implications for the AI agent ecosystem. Crypto Agent projects can now integrate LLM-based models like DeepSeek R1 instead of relying on expensive, closed-source OpenAI models.

2. Modular Architecture and Plugin Design

Another technological breakthrough I've been closely following is the evolution of modular architecture in AI agent frameworks. ElizaOS is leading the way here. It allows the core runtime to operate independently while developers can freely add plugins, characters, and adapters. ElizaOS can create images, videos, and 3D models, support automatic NFT series generation, and provide image description and analysis. It also offers essential services like browser access, document processing, and speech-to-text conversion.

What I love most about this modular design is how it empowers developers. They can easily customize their own plugins and tools and share 1-3% of revenue via smart contracts. This creates a vibrant ecosystem where everyone benefits from innovation.

In performance testing, ElizaOS has shown solid capabilities. The upcoming ElizaOS v2 update promises even more exciting features:

This cross-chain approach is exactly what the ecosystem needs to grow.

3. The Shift from Centralized to Decentralized AI

Here, you’ll see I mention “blockchain”, “token” or “crypto” sometimes. I already explain all these terms in part 1 of this series, and I highly recommend reading part 1 first. It’s the new standard, you can’t rely only on AI anymore. Despite the decentralized ethos of blockchain, one of the biggest challenges I've observed is that most current AI agents still suffer from significant centralization issues:

• Centralized inference: Most rely on services like Runpod or Lambda for model inference

• Server dependency: Agent behavior, reasoning, and memory are typically managed on central servers

• Limited transparency: Central control reduces trust and creates single points of failure

The technical challenges are significant – blockchain resource constraints make it difficult to run complex AI models directly onchain. The biggest opportunity I see is standardizing the entire lifecycle of onchain models: training, inference, fine-tuning, evaluations, and governance. This would create a consistent framework that developers could build upon, accelerating adoption and innovation.

📌 Real Example for You: DeFAI: Where Decentralized Finance Meets AI: I personally used Hey Anon. It offers an AI interface that simplifies operations like onchain swaps, margin trading, and loans. The experience is night and day compared to traditional DeFi.

II. AI × Crypto Investment Thesis in 2025

So, I can say that AI has gotten really good at learning from massive piles of internet text. But in 2025, something changed. We hit what some call “The Data Wall.” It means we’re running out of useful, high-quality data to feed these models. So What’s Changing?

We’re seeing a divide form:

• Big tech (OpenAI, Google, etc.) are building huge reasoning models that try to “think” through problems instead of just regurgitating data.

• Open-source teams are releasing powerful models with open weights, making high-quality AI freely available. For a long time, GPT-4o stood as an unreachable benchmark without any comparable alternative. This changed when DeepSeek released its V3 model as an open-weights model.

• Startups are training smaller, fine-tuned models for niche use cases (law, medicine, education, etc.).

• Individuals and hackers are building AI agents and clever workarounds, creating real-world tools with minimal resources.

Everyone’s rushing to figure out how to make AI smarter, more useful, and more accessible.

1. Commoditized Cognition: Owning AI Like You Own Bitcoin

Let’s rewind to Bitcoin for a second. When Bitcoin launched, it let anyone in the world create and own digital money without a bank. It used electricity + code to produce value. No middlemen. Just pure permissionless infrastructure.

What if we could do the same with AI?

AI models also use electricity + code to create value, through training and inference. If we can decentralize the way they’re built, accessed, and monetized, we could treat AI like a public utility. A natural resource. Something you can own and use freely just like Bitcoin or Ethereum.

We call this vision commoditized cognition. It means AI becomes an open resource, not a walled-off service.

So now you know why we recently mention blockchain, crypto a lot right? Let’s use AI Fire Agent as an example here. Right now, most AI Agent runs in centralized systems. You don’t own it. You can’t fork it. You can’t trace it. That’s a problem.

=> With crypto, we can build onchain models: AI that lives on the blockchain. You can verify how it works, share profits from it, fine-tune it yourself, and even govern how it’s used. The result? Models that are:

• Permissionless to use and improve

• Monetizable in new ways (you can earn from usage and fine-tunes)

• Governed by smart contracts, not corporations

• Compositional, meaning anyone can build on top of them

We’re talking about a new type of AI infrastructure: transparent, decentralized, and fair. Once you have onchain models, a whole new class of markets opens up:

• You can share profits from an AI model with token holders.

• You can use AI as collateral to get funding.

• You can trade on model performance, like betting on which models will do best.

• You can buy insurance against models failing or costing too much compute.

• You can even bundle AI models into ETFs or pools, just like traditional assets.

These “AI-aware” markets are how we’ll fund the next wave of innovation - AI Fire Agent. And they’re only possible because of crypto. AI is too important to be owned by a few. Crypto gives us the tools to make AI open, fair, and unstoppable.

=> If you're curious, now's the time to explore. The future's being built by teams, hackers, and dreamers who believe AI and crypto can change everything from how we solve problems to how we organize economies.

2. The Future of AI Agents: Beyond The Hype

Looking ahead, I see enormous potential in agent-to-agent transactions and automated marketplaces. As AI agents become more sophisticated, they'll increasingly interact with each other, creating entirely new economic systems.

=> Agent orchestration - coordinating multiple agents to work together - will enhance overall capabilities and efficiency. Over time, more jobs will be automated, with AI agents performing tasks faster, cheaper, and more effectively - ultimately leading to greater prosperity. This transformation is already beginning in areas like:

• Content creation and management

• Data analysis and reporting

• Customer support and engagement

• Financial trading and portfolio management

Several areas particularly excite me:

• Multi-Agent Systems and Collaboration: Instead of single agents working in isolation, we'll see teams of specialized agents collaborating to solve complex problems.

• Specialized Models for Crypto: Purpose-built AI models optimized for crypto use cases will dramatically improve performance and reduce costs.

• The Cybernetic Economy Vision: The ultimate destination is what some call the "cybernetic economy" - a system where human and machine intelligence work together seamlessly, with blockchain providing the coordination and incentive layer.

III. Understand AI Agent Ecosystem

First, in this post, I’ll try to keep everything straightforward, and easy to understand for you. I won’t include lengthy paragraph, instead, I’ll give you some more basic ideas and graphics to better undestand this new field.

So, web3 agents are autonomous software programs that operate within decentralized networks, utilizing blockchain technology to perform tasks without human intervention.

1. Web3 Agents: Current State

I think there’re 2 fundamental properties that make web3 AI agents truly revolutionary compared to any existing AI application:

• Autonomy: Unlike traditional AI systems that require constant human oversight, web3 agents operate in a decentralized computing environment. This means they can function 24/7, making decisions and executing tasks without human input.

• Economy: What really sets web3 agents apart is how they integrate with economic systems. For both users and investors, participating in an agent's economy is transparent and straightforward since it's programmable, blockchain-based, and open. This creates entirely new business models that simply weren't possible before.

Encryption technology gives these agents a borderless system for identity, assets, and settlements. Right now, we're in the early experimental phase - similar to Ethereum circa 2016. But by mid-to-late next year, I expect we'll see agents handling increasingly complex tasks, automating processes, and generating substantial cash flow. The replacement of certain jobs with AI agents is inevitable - but the good news is that through tokenization, you can actually own a piece of this automation revolution.

Most Web3 AI agents today are just chatbots built with large language models (LLMs). You’ll see them on platforms like X and Discord, where they act like characters and talk to users. Here’s what they usually do:

• Trading: Each agent often has its own token that people can buy and sell on crypto exchanges.

• Content generation: They post replies, tweets, or messages based on prompts or pre-set personalities.

• Role-playing: Some agents pretend to be certain characters to keep conversations fun.

• Community engagement: Users can influence what the agent says or does by giving feedback or suggestions.

But there are some big issues:

• Tokens are mostly hype: The agent’s token is usually just a speculative asset, not something that actually powers the AI or gives you ownership.

• No real utility: These tokens don’t earn revenue or give holders any benefits.

• Centralized setup: Despite being “Web3,” most of these agents run on centralized servers (like Runpod or Lambda).

• Not transparent: The code and decision-making are controlled by a few people. If they shut things down or change the rules, there’s not much anyone can do.

So, while the idea is cool, most AI agents in Web3 right now are still far from being truly decentralized or sustainable.

2. The 4 Pillars of the AI Agent Landscape

Through my research, I've identified four distinct categories in the AI agent ecosystem, each playing a unique role:

• AI Agent Frameworks: These are the foundational infrastructure that everything else is built upon. Think of them as the "operating systems" for AI agents. ElizaOS like I said in the first part is a perfect example - it employs a modular plugin design with four key components inside.

• AI Launchpads: These function as "hybrid incubators and trading platforms" that lower entry barriers for new AI agent projects. They help accelerate launch, financing, and promotion of new agents. Ex: Virtuals Protocol or Auto.fun (an upcoming launchpad by ElizaOS team)

  

• AI Agent Memecoins: While these might seem frivolous at first glance, they play an important role in the ecosystem. Projects like BULLY from the Virtual ecosystem and TAOCAT from Bittensor combine AI narratives with meme culture to quickly attract attention and capital.

  => I initially dismissed these as pure speculation, but they're essentially marketing vehicles that help bootstrap more serious projects. Just don't expect long-term value from most of them.

• AI Agent Applications: These focus on implementing AI in real-world scenarios - automated trading, asset management, market analysis, and cross-chain interaction. Just like AI Fire Agent!

While applications currently lag behind launchpads in commercialization, I believe they'll eventually become the most valuable segment as technology matures and user education advances.

3. Future of Web3 AI Agents

I believe AI agents will likely become the dominant narrative not only in AI World but also in crypto field in 2025. However, there are still many unsolved problems and room for growth. Below, I'll try to structure the potential areas for improvement to make AI agents more useful and better overall.

🔁 Better Tokenomics

For Web3 agents to truly take off, they need solid and sustainable economic models. Right now, many agent tokens are just for speculation but that can change.

• Revenue sharing: Agents can earn from tasks like writing content, coding, or doing analysis and share profits with token holders. So, if the agent performs well, the community benefits too.

• Real utility: Tokens can unlock access to the agent’s services or give you a say in how it’s developed.

• Community control: With smart contracts and multi-sig wallets, decisions and funds can be managed transparently by the community, not a central team.

• Agentic economies: Imagine agents negotiating or trading with each other on your behalf. Smart contracts will power these automated interactions.

• Teamwork: Agents working together (orchestrated) can do more complex tasks, improving the overall system.

🌐 True Decentralization

Right now, most agents still run on centralized servers but for Web3 to mean anything, that needs to change.

• Decentralized inference: Instead of relying on big cloud servers, agents will run across networks or even your device. This boosts resilience and privacy.

• On-chain logic: Agent decisions and reasoning can move on-chain using smart contracts, making everything more transparent and trustworthy.

• Community governance: The community should steer the agent’s direction—voting on updates, behavior, and big changes. That’s how you remove single points of failure and stay true to the Web3 ethos.

🛠️ More Capabilities & Better Tools

Web3 agents are getting smarter and more useful with more ways to interact and better tools for developers.

• Multimodal interaction: Not just text, future agents will support voice, video, 3D avatars, and even AR, making things feel more natural and engaging.

• Specialized skills: With models tailored for things like trading or financial analysis, agents could become DeFi strategists or portfolio managers.

• Smarter tooling: New frameworks will make it easier to build, deploy, and manage AI agents with planning, reasoning, and self-critique built in.

• Interoperability: Agents will need to work with each other seamlessly—standards and protocols will help make that possible.

• Resilience: Agents will be built into systems that adapt in real-time and keep working, even if some parts fail.

• Security & trust: Things like model theft, prompt injection, and data poisoning are real threats. Future agents will need built-in security, transparency, and auditability to build real user trust.

🎯 Better Agent Experience

Using Web3 agents today can be clunky, but the future looks a lot smoother.

• Smart UIs: Instead of fixed interfaces, agents will generate UIs tailored to you, in real time.

• More natural interaction: Voice commands, AR, and 3D avatars will make agents feel more alive and easier to use.

• Integrated everywhere: Think agents embedded in your wallet, Discord, or browser—always on and ready to help.

• Personal memory: Agents will remember your preferences and context, so they get more useful over time.

• Autonomous action: With permission, agents can monitor prices, trade tokens, post updates, reply to DMs, or alert you to key events like governance votes or suspicious wallet activity.

I believe AI agents represent a fundamental shift in the global workforce. Over time, more jobs will be automated, with AI agents performing tasks faster, cheaper, and more effectively

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Conclusion

2025 is a turning point. AI is exploding in power and crypto is quietly giving it superpowers. Together, they’re unlocking brand-new ways to build, own, and earn from intelligent systems. So what’s really going on here?

• AI is getting easier to build and customize. Thanks to better training tools, more people can now create their own models.

• AI needs compute to run and that creates new markets. Instead of relying on Big Tech servers, people are building open, onchain systems where you can pay for AI “as you go.”

• AI agents are getting memory, goals, and personality. That opens up powerful new use cases from personal assistants to automated businesses.

Each part of this puzzle feeds the others. As AI models get cheaper, more agents appear. As agents get smarter, they need better memory. As AI gets used more often, new economic systems emerge to support it.

If you’re building or investing in this space, now is the time. People who understand that crypto isn’t just a sidekick to AI, it’s the foundation that makes it fair, transparent, and available to everyone.