The rise of AI-driven crypto
agents is following a familiar trajectory that mirrors the
initial boom, bust and resurgence of ICO-era projects. Just as
early blockchain ventures thrived on hype before maturing into
sustainable ecosystems, the current wave of AI agent projects is
undergoing rapid market shifts.
A new report by HTX Ventures and HTX Research says that
investors are growing cautious as competition in the sector
intensifies, liquidity disperses and many projects struggle to
define clear use cases. Still, as the sector moves beyond its
speculative phase, AI-driven crypto
agents are expected to evolve sustainable business models
underpinned by genuine utility.
To dive deeper into the evolution of crypto agents and the
future of AI-driven blockchain innovation, download the full report
by HTX here.
From meme hype to reality: The evolution of crypto agents
The initial wave of crypto agent projects in 2024 was driven by
indiscriminate enthusiasm for AI projects. Following the impact of
a $50,000 Bitcoin
donation from Marc Andreessen in October 2024 and the success
of token launchpads earlier in the year, many AI agent projects
entered the space in Q1 of 2024 and rapidly diluted liquidity by Q1
of 2025. As with any emerging sector, early-stage hype did not
always translate into long-term viability, and a cooling-off period
in the crypto AI agent sector followed.
The market segment is now entering a more mature phase, and the
focus is shifting from speculative excitement to revenue generation
and product performance. The winners in this evolving landscape
will be those that can generate stable revenue, cover the costs of
running AI models and provide tangible value to users and investors
alike.
AI agent applications emphasize real-world implementation and
commercialization of this technology, particularly in areas like
automated
trading, asset management, market analysis and crosschain
interaction. This approach aligns with multi-agent systems and
DeFAI (decentralized finance + AI)
initiatives like Hey Anon, GRIFFAIN and ChainGPT.
Recent research highlights the advantages
of multi-agent systems (MAS) in portfolio management, particularly
in cryptocurrency investments. Projects such as Griffain, NEUR, and
BUZZ have already demonstrated how AI can help users interact with
DeFi protocols and make informed decisions. Unlike single-agent AI
models, multi-agent systems leverage collaboration among
specialized agents to enhance market analysis and execution. These
agents function in teams, such as data analysts, risk evaluators
and trading execution units, each trained to handle specific
tasks.
MAS frameworks also introduce inter-agent communication
mechanisms, where agents within the same team refine predictions
through collective learning, reducing errors in market trend
analysis. The next phase of DeFAI will likely involve deeper
integration of decentralized governance models, where multi-agent
systems participate in protocol management, treasury optimization
and onchain compliance enforcement.
To dive deeper into the evolution of crypto agents and the
future of AI-driven blockchain innovation, download the full report
by HTX here.
DeepSeek-R1: A breakthrough in AI agent training
A breakthrough in AI agent technology arrived with
DeepSeek-R1,
an innovation that challenges traditional AI training methods.
Unlike previous models, which relied on supervised fine-tuning
(SFT) followed by reinforcement learning (RL), DeepSeek-R1 takes a
different approach, optimizing entirely through reinforcement
learning without an initial supervised phase. This shift has led to
remarkable improvements in reasoning capabilities and adaptability,
paving the way for more sophisticated AI-driven crypto agents.
To understand this paradigm shift, consider two different
approaches to learning. In the Traditional SFT and RL model, a
student first studies from a workbook, practicing problems with set
answers (SFT), and then receives tutoring to refine their
understanding (RL). In contrast, with the DeepSeek-R1 Model (Pure
Reinforcement Learning), the student is thrown directly into an
exam and learns through trial and error. This approach allows the
student to improve dynamically based on feedback rather than
relying on pre-defined answers.
Leveraging DeepSeek-R1’s pure RL model, AI agents learn through
trial and error in real-world conditions, dynamically adjusting
their strategies based on immediate feedback.
This method allows for greater adaptability, making it
particularly useful for multi-agent AI systems in DeFi, where
real-time market fluctuations require agents to make autonomous,
data-driven decisions. For example, AI-powered agents can monitor
liquidity pools, detect arbitrage opportunities and optimize asset
allocations based on real-time market conditions. These agents
adapt quickly to market fluctuations, ensuring more efficient
capital deployment.
Launched in late November 2024, iDEGEN is the first crypto AI
agent built on DeepSeek
R1. This integration of
DeepSeek’s R1 model emphasizes how crypto AI agents can inherit
such enhanced reasoning capabilities, competing with other
established AI models at a fraction of the cost.
This shift toward RL-powered, multi-agent AI in DeFi automation
underscores why closed-source AI models (such as OpenAI’s GPT-based
systems) are becoming an
unsustainable expense. With workflows often requiring the
processing of 10,000+ tokens per transaction, closed AI models
impose significant computational costs, limiting scalability. In
contrast, open-source RL models like DeepSeek-R1 allow for
decentralized, cost-efficient AI development tailored for DeFi
applications.
The future of AI agents in Web3
The key to longevity in this sector lies in continuous
innovation, adaptability and cost efficiency. Open-source AI models
like DeepSeek-R1 are lowering the barriers to entry, allowing
blockchain-native startups to develop specialized AI solutions.
Meanwhile, advancements in
DeFAI and multi-agent systems will drive long-term integration
between AI and decentralized finance.
The takeaway is clear: Projects must prove their value beyond
hype. Those who develop sustainable economic models and leverage
cutting-edge AI advancements will define the future of intelligent
blockchain ecosystems. The ICO era of crypto agents is evolving,
and the next wave of winners will be the ones that can turn
innovation into long-term viability.
To dive deeper into the evolution of crypto agents and the
future of AI-driven blockchain innovation, download the full report
by HTX here.
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