The rise of AI-driven crypto agents follows a familiar trajectory that reflects the first boom, bust and revival of projects in the ICO era. Just as early blockchain ventures flourished with hype before maturing into sustainable ecosystems, the current wave of AI agent projects is undergoing rapid market changes.
Investors are becoming more cautious as competition in the sector is growing, with liquidity diversification and many projects struggling to define clear use cases, according to a new report from HTX Ventures and HTX Research. Still, as sectors move beyond the speculative stage, AI-driven crypto agents are expected to evolve sustainable business models supported by authentic usefulness.
To dive deeper into the future of cryptographic agents and AI-driven blockchain innovation, download the full HTX report here.
From meme hype to reality: the evolution of crypto agents
The early wave of the 2024 Crypto Agent Project was driven by indiscriminate enthusiasm for AI projects. Following the impact of $50,000 Bitcoin donation from Marc Andreessen in October 2024 and the success of Token Launchpad at the beginning of the year, many AI agent projects entered the space in Q1 2024, with liquidity rapidly diluting by Q1 2025.
The market segment is now in a more mature stage, focusing on revenue generation and product performance from speculative excitement. Winners in this evolving landscape are those who can generate stable revenue, cover the costs of running AI models, and provide tangible value to users and investors.
AI agent applications highlight the real-world implementation and commercialization of this technology, particularly in areas such as automated trading, asset management, market analysis, and cross-chain interactions. This approach is consistent with Multi-Agent Systems and Defai (Decentralized Finance + AI) initiatives such as Hey Anon, Griffain, and Chaingpt.
Recent research highlights the benefits of multi-agent systems (MAS) in portfolio management, particularly in cryptocurrency investment. Projects like Griffain, Neur, and Buzz have already demonstrated how AI can help users interact with the Defi protocol and make informed decisions. Unlike the single-agent AI model, multi-agent systems leverage collaboration between specialized agents to enhance market analysis and execution. These agents work with teams such as data analysts, risk evaluators, and transaction execution units, each trained to handle a specific task.
MAS Frameworks also introduces communication mechanisms between agents. Agents within the same team improve forecasting through collective learning and reduce errors in market trend analysis. The next step in DEFAI could include deeper integration of distributed governance models. There, multi-agent systems will take part in protocol management, Ministry of Finance optimization, and on-chain compliance enforcement.
To dive deeper into the future of cryptographic agents and AI-driven blockchain innovation, download the full HTX report here.
DeepSeek-R1: AI Agent Training Breakthrough
The breakthrough in AI agent technology arrived using DeepSeek-R1, an innovation that challenges traditional AI training methods. Unlike previous models that relied on reinforcement learning (RL) following monitored fine-tuning (SFT), DeepSeek-R1 employs a different approach and fully optimizes through reinforcement learning without the initial monitoring stage. This shift leads to significant improvements in reasoning ability and adaptability, paving the way for more refined, AI-driven crypto agents.
To understand this paradigm shift, consider two different approaches to learning. In traditional SFT and RL models, students first study from the workbook, practice Set Answers (SFT) issues, and then receive personalized tutoring to refine their understanding (RL). In contrast, along with the DeepSeek-R1 model (pure reinforcement learning), students are thrown directly into the exam and learn through trial and error. This approach allows students to dynamically improve based on feedback rather than relying on predefined answers.
Utilizing DeepSeek-R1’s pure RL model, AI agents learn through trial and error in real-world conditions and dynamically adjust strategies based on immediate feedback.
This method can improve adaptability and is particularly useful for DEFI’s multi-agent AI systems where agents need to make autonomous, data-driven decisions due to real-time market fluctuations. For example, an AI-powered agent can monitor liquidity pools, detect arbitrage opportunities, and optimize asset allocation based on real-time market conditions. These agents adapt quickly to market fluctuations and ensure more efficient capital deployment.
Released in late November 2024, Idegen is the first cryptographic AI agent based on the Deepseek R1. This integration of Deepseek’s R1 model highlights how cryptographic AI agents inherit such enhanced inference capabilities, competing with other established AI models at a fraction of cost.
This shift to RL-driven multi-agent AI in Defi Automation underscores why closed-source AI models (such as Openai’s GPT-based systems) are becoming unsustainable costs. Closed AI models often impose significant computational costs and limit scalability, as workflows require more than 10,000 tokens per transaction. In contrast, open source RL models like DeepSeek-R1 allow for distributed, cost-effective AI development tailored to DEFI applications.
The future of Web3’s AI agents
The key to the longevity of this sector is its continued innovation, adaptability and cost-effectiveness. Open source AI models like DeepSeek-R1 lower the barrier to entry, allowing blockchain native startups to develop specialized AI solutions. Meanwhile, advances in Defai and Multi-Agent systems will encourage long-term integration of AI and decentralized finance.
The takeaway is clear. Projects need to prove their value beyond hype. Those who develop sustainable economic models and leverage cutting edge AI advances will define the future of the intelligent blockchain ecosystem. The ICO era of crypto agents is evolving, and the next wave of winners can turn innovation into long-term viability.
To dive deeper into the future of cryptographic agents and AI-driven blockchain innovation, download the full HTX report here.
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