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In January 2025, the DeFAI revolution will break out starting from the "abstraction layer": People can now complete on-chain and DeFi operations through a ChatGPT-like dialogue interface by inputting commands, which is widely considered the next generation of decentralized finance.

Reference previous article: "DeFAI" Summer is Coming, How Will AI Reshape DeFi's Future?

As projects like @griffaindotcom, @HeyAnonai, @bankrbot, and @orbitcryptoai emerge (each with unique characteristics), the flaws of abstraction layer technology gradually become apparent - some products lack sufficient DeFi protocol integration, while others have insufficient reasoning capabilities, forcing users to precisely design prompts to drive AI operations.

A deeper common issue is "decision paralysis": When users face a ChatChatGPT-like blank dialogue box, they often don't know how to issue commands - wanting high yields or trading Alpha but not knowing where to start. This cognitive dilemma leads users to return to traditional UI/UX tools with clear interfaces.

Low interaction mode acceptance, combined with the early-stage DeFAI ecosystem, valuation bubble, bubbles, and and macro uncertainties, ultimately triggered a price crash.

However, DeFAI has not ended: The industry direction from Q1 to Q2 has undergone a key shift, with core trends include (but are not limited to):

1. abstraction layer ➔layer

2.Ancing workflows with DeFAI (rather than replacing)

3. DeFAI autonomous agents: Full workflow abstraction (with agents as interaction interfaces)

4. DeFi protocols integrated with AI (Some or with clear AI roadmaps) Some projects have reached initial product market fit (PMF), while others are still in R&D. Let's analyze from the first trend.

Core Trend: Strategic Transformation from Abstraction Layer to Discovery Layer, interactions withIraction fall into two categories p>

A. Investors seeking trading Alpha opportunities and

B. Holders trying to activate idle capital through yield farming.

Traditional abstraction layers, due to overly broad coverage and high operational complexity (with technical defects), failed to provide effective solutionsolutions beyond existing tools/protocols for both user types. In this context, some DeFAI protocols have shifted from simply expanding execution layer integration capabilities to buildingbuiling discovery discovery layer core capabilities - - with strategic focus><.ating high-quality signals and yield farming strategies strategiespositioning as aalized discovery portal

Referring to the typical case above: @slate_ceo, once known for advanced trading execution functions, has now transformed into a structured discovery layer platform.

Its core mechanisms include:

1. Tracking top Telegram trading group signal streams

2. Dynamically ranking and credit rating signal sources based on performance/historical records

3. Completing Alpha mining before trading spreads to X platform

@Infinit_Labs positions itself as a comprehensive terminal that can learn user wallet behaviors, providing personalized yield farming strategies and DeFi investment opportunities by analyzing on-chain historical data, supporting users directly execute strategy decisions within the same interface, achieving an "insight-execution" closed loop. Top protocols have achieved initial product market fit (PMF), with continuously expanding user base, and neither has yet issued native tokens.

Meanwhile, Arbitrum just released Trailblazer 2.0, providing $1 million in funding support to teams contributing to Vibekit (an Arbitrum native MCP developed by @EmberAGI).

Although trading agents are currently in the early stage, with no clear long-term outperformers emerging, many are focusing on @Almanak__'s beta version, which emphasizes scalability and privacy-first, supporting rapid deployment of quantitative trading agents.

Another noteworthy team is @magicnewton, who are building verifiable agents using zero-knowledge proofs (ZKPs)) execution environments).

Their approach is unique, focusing on automated trading scenarios, starting with dollar-cost averaging (DCA) agents, building and an "automated agent market" that allows third-party developers to create agents. Users' trading intentions will be matched with executors through a matching orderbook, forming a complete closed loop.

Although still in the early stage, their integration with @KaitoAI has shown initial growth momentum.

Trend of DeFi Protocols Integrating AI

Currently, more and more DeFi protocols are incorporating AI into their product roadmaps, with applications ranging from basic customer support and product education (using large language models LLM), to directly embedding complex machine learning (ML) models into core product functions.

@BasisOS launched its token on @virtuals_io, by strong DeFi products (DN Vaults) and AI development roadmap, continuously gaining market attention with good token performance and growing TVL. Its latest released YieldAI Autopilot v2 combines machine learning and reasoning mechanisms, providing a and more and execution method for DDDeFi yield strategies.

@loomlayai built an AI co-pilot function for @zerion, users directly analyze wallets, tokens, and mine trends on the Zerion platform, optimizing asset management experience.

@vvectis_finance integrated @AlloraNetwork's SOL price prediction model a, developing a stablecoin strategy with a stable annual yield between 15%-20%.

@modenetwork launched Mode Trade, directly integtherating predictive inference function of Synth Bittensor SN50 into its perpetual contract trading dApp.

Additionally, next week we will see the the top-ranked options options protocol @Ithacocol launching its new product Stratos on the Virtuals platform—platform a swarm of multiple option trading agents.

These AI agents will be driven by the protocol's liquidity funds (around $20,000 to $30,000), participating in various options trading strategies.

The AI system will process market data and categorize it into different "different "market regimes" such as bull market, bear market, high volatility, stable, etcically trading strategies accordingly.

Each agent in Stratos has a unique unique unique," simulating an experience--making: they will first evaluate the algorithmically recommended trading instructions, but may also choose choose to skip or adjust strategies based on past market learning experiences, demonstrating an adaptive "subjective judgment".

Industry Evolution Direction

Integration Trend: Traditional Alpha capture tools will be deeply integrated with AI-enhance enhanced user experiences

Core Implementation Paths:

1. Deliver insights frictionlessly through AI co-pilot and and-agentic workflows

2. Deepen decentralized AI verification frameworks in autonomous agent systems:

1. Verifiability

2. Confidentiality

3. Privacy-Preserving Architecture-execution p strong>Ultimate Vision: Anyone Anyone can seamlessly capture DeFi, RRReal-World Assets) and other-through an AI interface

Investment Mapping Logic

1. Value Capture Focus:

1. DeAI (Decentralized AI) projects with underlying capabilities will replicate'S ggrowth path p> 2. Core Standard: Build a new "trustless, verifiable" AI agent base layer

2. Protocol Follow-up motivations:

1. Current valuations severely suppressed by macro factorserh

2. Market preference shifting from VC-backed infrastructure to fair launch projects

Summary: Second Quarter Quarter Will Be Intensive PeriodIated Innovation

Price fluctuations do not hinder progress. This quarter quarter,:

1. Many small, issued teams rapidly iterate through lean operations + trading revenue, seeking product market fit (PMF) and tenaciously surviving;

2. Medium and large teams will sequentially debut, though initially price-, valuations will ultimately return to fundamentfundamentals, in volatile market BTC dominates attention and only a few Altcoins gain focus.

Personal Statement: Thank you for reading! This is a condensabbreviated version. For deeper insights into the Dethe DeAI field, please refer to the full version on on my Substack column. The 'The After Hour' series will continue to update my potential focus onAprojects and emerging protocol reports (latest target assessment will be released this weekend).

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