Tron Industry Weekly Report: Risk aversion intensifies but Strategy increases BTC holdings, detailed explanation of the Agent payment protocol PAN Network based on x402 and ERC-8004

I. Outlook

1. Summary of the macro level and future predictions

This week's core keywords for the global macro environment are "energy shock + geopolitical conflict + stagflation concerns." The escalation of conflicts between the United States, Israel, and Iran has disrupted transportation in the Strait of Hormuz, affecting about 20% of the global oil supply chain. Oil prices briefly surpassed $100 per barrel, driving up prices of natural gas, fertilizers, and other energy-related commodities. The surge in energy prices is transmitting globally, with major economies in Europe, America, and Asia facing stagflation pressures of "slowing growth + rising inflation," while financial market risk appetite declines, leading to increased volatility in stock markets and risk assets.

Short-term macro trends will continue to revolve around geopolitical issues and energy prices. If the Middle East conflict persists and transportation in the Strait of Hormuz cannot be restored, oil prices may remain high, further strengthening global stagflation expectations and forcing central banks to maintain high interest rates or delay rate cuts. At the same time, global markets will pay more attention to U.S. employment and inflation data, as well as policy signals from major central banks. In the current environment, macro funds are more likely to continue flowing into energy, gold, and safe-haven assets, while risk assets such as tech stocks and cryptocurrencies will maintain high volatility.

2. Market changes and warnings in the cryptocurrency industry

This week, the cryptocurrency market overall presented a pattern of "macro shock --- oscillating rebound." Affected by the escalation of the Middle East situation and soaring oil prices, global risk asset volatility intensified, with Bitcoin briefly retreating to around $66,000, and then quickly rebounding as market sentiment improved, standing back in the $72,000 - $73,000 range around March 13. During the same period, institutional funds continued to flow into the market, with U.S. listed company Strategy increasing its holdings by about 18,000 BTC (approximately $1.28 billion), indicating that long-term funds are still positioning during fluctuations. Meanwhile, the return of ETF funds and the warming of institutional demand have also become important factors driving this round of rebound.

The short-term market still faces three major uncertainties: First, geopolitical issues and oil price fluctuations may continue to affect global risk asset sentiment, amplifying volatility in the cryptocurrency market; Second, macro liquidity and interest rate expectations remain dominant factors. If U.S. dollar liquidity tightens, BTC may retest the support range of $60,000 - $65,000; Overall, the market is likely to maintain a fluctuation range of $65,000 - $74,000 in the coming week, with a focus on macro events and changes in institutional fund flows.

3. Industry and track hotspots

A brief analysis of a total financing of $4 million, led by OG Labs and Messari --- the full-stack infrastructure protocol Warden Protocol driving the AI Agent economy. A total financing of $5 million, led by Karatage, with Marblex and Ton participating --- a scalable, modular multi-Agent content generation platform AKEDO. A total financing of $4.2 million --- the Agent native payment protocol PAN Network based on x402 and ERC-8004.

II. Market Hotspot Tracks and Potential Projects of the Week

1. Overview of Potential Projects

1.1. A brief analysis of a total financing of $4 million, led by OG Labs and Messari --- the full-stack infrastructure protocol Warden Protocol driving the AI Agent economy

Introduction

Warden Protocol is a full-stack framework driving the AI Agent economy.

It provides the core logic, standards, and tools for Agent creation, distribution, monetization, and governance, building a complete infrastructure for Agent operation and collaboration.

Core Mechanism Overview

Warden: Next-Generation Agentic Wallet

Warden is a next-generation Agentic Wallet (smart agent wallet) and serves as the gateway to the AI Agent economy.
In a unified interface, users can discover, converse, and pay for Agent services. Whether it's deep research, cross-chain, minting, trading, or staking, users can complete complex Web3 operations through natural language chat, with all thinking and execution handled by the Agent.

Currently, Warden supports Solana, Ethereum, BNB Chain, Base, and all their tokens and applications, and will eventually cover all EVM chains and more ecosystems.

What users ultimately experience is:
Making the crypto world simple, intuitive, and easy to use, and creating a true Everything App through access to 20+ general AI models.

Core Features

• Single Agent Entry: Discover, chat, and pay for any Agent service in one place

• Simplified Complex Operations: Complete advanced workflows using natural language

• One-stop Neo Finance: Complete trading, forecasting, research, and asset management with Agent assistance

Warden Agent Network

Warden covers the complete lifecycle of Agents: from creation to large-scale adoption. This is Warden's "North Star goal."

Four Core Components

Warden Studio → Warden Chain → Warden Agent Hub → Warden App

• Warden Studio: Tools for Agent creation and monetization

• Warden Chain: Identity, trust, and payment coordination layer for Agents

• Warden Agent Hub: Agent marketplace solving distribution challenges

• Warden (App): The entry point for users to discover and use Agents

Warden Studio (Agent Creator Platform)

Warden Studio is a zero-threshold platform for Agent publishing and monetization, supporting on-chain or off-chain Agents, directly reaching millions of users.

It targets not just traditional developers but also:

• Vibe coders

• No-code creators

• Web2 Builders

Core Capabilities

• Go live in one minute, reach globally: No review or registration required

• On-chain Agent identity: Compatible with ERC8004, X402

• Stablecoin payments: Minute-level settlement

• Flexible pricing: Billing by reasoning / subscription model

• Long-term compatibility: Adapts to the latest frameworks and protocols

Warden Chain (Agent-Specific Blockchain)

Warden Chain is a foundational blockchain tailored for the Agent economy, with all Agents created through Studio being directly minted on-chain.

Core Functions

• Identity: Assign a unique cryptographic identity to each Agent

• Reputation: Record historical behavior and trustworthiness

• Spending: Agents can hold balances, make automatic payments, and share profits

• Security: Define the boundaries and rules for Agent fund usage

• Proof of Inference: All interactions and billing can be verified

Warden Agent Hub (Agent Distribution Marketplace)

Like an App Store, but built for Agents.

Warden Agent Hub is not just a marketplace but also an Agent collaboration platform, where multiple Agents can combine capabilities to solve complex problems that a single Agent cannot complete.

Solving the industry's biggest challenge: Distribution

• Avoid "cold start of empty markets"

• Agents face real user demands upon launch

• Support instant monetization and micropayments

Agent Types (Current Focus)

• Financial Agents: Abstract DeFi complexities to achieve "all applications on one screen"

• Autopilot Agents: Execute tasks offline automatically (launching H2 2025)

• Institutional Agents: Real-time combination optimization, risk control, anti-hacking

• Ecological Agents: Governance, risk monitoring, proposal analysis

SPEX Overview

SPEX (Statistical Proof of Execution) is a sampling-based verifiable computing protocol that ensures the integrity of computing tasks through probabilistic guarantees. It is suitable for computing scenarios that may have non-deterministic outputs, such as large language model (LLM) inference or randomness training pipelines.

In Warden, SPEX serves as the verifiability layer for AI, used to verify:

• The selected model was actually used

• The computation output has not been tampered with

Thus reducing execution risks caused by dishonest executors or compromised infrastructure.

Core Features

The SPEX framework introduces the following key capabilities:

• Formal definition of verifiable computing for modern computing pipelines

• Low-overhead, high-parallelism sampling verification protocol

• Support for non-deterministic computing states (crucial for AI/ML and LLM)

• Use Bloom Filters to encode and verify computing states

• Provide open-source reference implementation: warden-spex

How SPEX Works

SPEX does not require a complete replay of computations but achieves verification through sampling and selective re-execution:

• Sampling complete execution: Defend against adversarial solvers

• Sampling intermediate states and selectively re-executing: Detect "lazy solvers"

• Verify both the execution process and final results simultaneously through cryptographic hashes
  

System Roles

SPEX only requires a pair of nodes to operate:

• Solver (Execution Node):
  Executes computing tasks and generates cryptographic execution proofs

• Verifier (Verification Node):
  Randomly samples task segments and verifies their consistency with cryptographic proofs and final outputs

Tron Commentary

Warden positions itself around the "AI Agent economy," building a full-stack infrastructure from Agent creation (Studio), identity and payment (Chain), distribution and monetization (Agent Hub) to user entry (Agentic Wallet). Its advantages lie in fully covering the entire lifecycle of Agents, abstracting complex Web3 operations into natural language interactions, and enhancing the credibility and composability of Agents through verifiable execution (such as SPEX) and on-chain identity/reputation mechanisms, significantly lowering the barriers for users and developers;

However, its disadvantages include high system complexity and strong reliance on underlying chains and AI inference costs. The ecological value is highly dependent on the quality of Agents and the scale of the distribution network, requiring continuous investment in the short term to prove the sustainability of large-scale user retention and real commercial demand.

1.2. Interpretation of a total financing of $5 million, led by Karatage, with Marblex and Ton participating --- a scalable, modular multi-Agent content generation platform AKEDO

Introduction

AKEDO is a multi-agent AI framework aimed at autonomous content creation and intelligent collaboration. It allows creators to design interactive games in just two minutes using simple natural language prompts.

AKEDO is powered by large language models (LLMs), and its modular framework is designed for scalability and flexibility, helping creators quickly turn ideas into real works.

Architecture Analysis

AKEDO Framework

AKEDO Framework is the world's first AI system supporting collaborative multi-agents, capable of dynamic interaction and unlocking nearly limitless possibilities for game and virtual content creation.

How It Works

Multi-Agent System

AKEDO centers around AI Agents, consisting of two types of intelligent agents based on large language models (LLMs), which are fine-tuned on different corpora and evaluated against corresponding benchmarks, each performing their roles and collaborating.

1. Development and Generation Agents

• Composed of 5 LLM Agents

• Each assumes different development responsibilities

• Collaborate to create virtual worlds, system architectures, and content

2. Autonomous Virtual Agents

• Autonomous AI Agents (NPCs) introduced into the virtual world

• Can dynamically interact with the environment and other Agents

• Continuously enrich world content and user experience

Prompt Optimization

When the user's input prompt is not clear or specific enough, Agent 1 is responsible for optimizing the prompt to ensure a smooth subsequent generation process.

Since the model is primarily trained on English corpora, Agent 1 also undertakes multi-language translation tasks, converting user inputs into English to support creators from different language and cultural backgrounds.

Task Classification

The system uses a medium-sized NLP model to classify user requests, determining whether the goal is:

1. To create a brand new game environment/world

2. To add new content (such as new autonomous AI Agents) to an existing environment

Task Breakdown

Agent 2 breaks down the parsed tasks into executable sub-tasks and builds the overall architecture of the code accordingly;
Subsequently, Agent 3 implements the specifics based on this foundation.

Code Generation

Agent 3 is responsible for generating high-quality, well-structured, industry-standard code, including:

• Module construction

• Component integration

• Efficient implementation of core logic

Engine Simulation and Testing

Agent 4 is responsible for simulating and testing the generated content:

• New environment creation: Directly simulates and tests the complete implementation of the new environment

• Content integration: Loads existing environment code, merges new content, and conducts overall simulation and testing

Implementation Review and Iteration

Agent 5 analyzes the simulation and testing results:

• If issues are found, it suggests modifications to Agent 3

• Agent 3 regenerates or corrects the code based on feedback

Agent 5 also maintains a limit on the number of iterations. When iterations exceed the threshold, the process escalates:
Agent 1 will re-optimize the original prompt to improve the accuracy and executability of subsequent generations.

Modular AI Infrastructure

Core Architecture

AKEDO designs each AI capability as an independently operating module (such as map generation, storyline creation, combat balancing, level design) and provides them as reusable, composable intelligent services.

These modules exist as Smart Assets --- callable, tradable, and forkable, enabling:

• Plug-and-play integration: For example, embedding a storyline Agent into a third-party game

• Configurable Remix: For example, reusing and modifying others' combat system AI blueprints

Dynamic World Engine

Unlike traditional static models, Akedo.AI treats each game as an ongoing fine-tuning experiment.
The system continuously evolves through real-time game data:

Player input → AI generated output

├─ Player behavior metrics (retention rate / success rate)

├─ Parameter variants and local model performance

└─ Parallel sub-model optimization

This builds a Web3-native reinforcement learning playground, where:

• NPCs can autonomously evolve and migrate

• The world timeline advances dynamically (seasons / events)

• Player behavior generates continuous and traceable chain reactions

Auditable AI Framework

AKEDO provides complete traceability for all AI operations, including:

• Step-by-step Chain-of-Thought records

• Complete prompt and intermediate state logs

• On-chain version snapshots

This auditable architecture supports Git-like branching and backtracking mechanisms, establishing a credible, verifiable, and evolvable foundation for generative AI.

On-Chain Personalization Engine

Unlike traditional off-chain personalization systems that rely on isolated game data, Akedo.AI utilizes verifiable on-chain behavioral footprints to establish a true digital sovereignty personalization experience.

Web3 Identity Integration

Before the game starts, AKEDO.AI performs a real-time scan of the player's wallet on the BNB Chain, analyzing:

• Digital asset holdings: NFTs, fungible tokens

• Transaction history: Minting, exchanging, staking, etc.

• Decentralized identity attributes and community engagement metrics

Dynamic Content Generation

Based on the above on-chain footprints, the AI engine can programmatically generate highly personalized content, including:

• Personalized narrative mainlines: Task objectives dynamically adjusted based on player asset combinations

• Context-aware NPCs: Characters respond differently to players' historical on-chain behaviors

• Asset-gated features: Specific skins, avatars, or abilities unlocked by on-chain milestones

Persistent Identity Layer

The player's wallet in AKEDO simultaneously serves as:

• Digital identity credential: Achieving continuity of identity across games and worlds

• Behavior modulator: Continuously influencing world evolution logic and content direction

Tron Commentary

AKEDO, centered on multi-agent collaboration and natural language-driven content creation, has built a modular AI framework for games and interactive content creation. Its advantages lie in abstracting complex game development processes into composable Agent workflows, achieving minute-level content generation, and supporting continuously evolving worlds and highly personalized experiences through on-chain identity and auditable AI architecture, significantly lowering the barriers to creation;

However, its disadvantages include high reliance on large model inference costs and multi-Agent collaboration stability, high complexity of system architecture, and higher demands on the quality of on-chain data and privacy trade-offs. Additionally, performance and consistency in large-scale real-time interaction scenarios still need to be continuously validated through actual operation.

2. Detailed Explanation of Key Projects of the Week

2.1. Detailed explanation of a total financing of $4.2 million --- the Agent native payment protocol PAN Network based on x402 and ERC-8004

Introduction

PAN Network is an on-chain AI payment protocol aimed at the autonomous Agent economy. It enables real-time machine-to-machine value exchange through A2A (Agent-to-Agent) payment mechanisms, x402 payment protocols, and ERC-8004 trust standards.

PAN allows AI Agents to autonomously complete transactions with built-in trust, settlement, and verification mechanisms. As the "Stripe of the AI Agent domain," PAN abstracts payment, collaboration, and execution logic at the network layer, providing scalable, secure, and interoperable infrastructure for AI-driven applications in the Web3 ecosystem.

Architecture Overview

ERC-8004 ------ The "Trust Kernel" of the Agent World

ERC-8004 is viewed by PAN as the PKI + credit system of the Agent world.

The Real Meaning of the Three Registries

1. Identity Registry

   • Each Agent = an ERC-721 NFT

   • The significance lies not in the NFT, but in:

     • Anti-censorship

     • Non-falsifiable

     • Globally unique → Solving "Who are you"

2. Reputation Registry

   • Does not directly give scores

   • Only records verifiable feedback authorization events

   • Third parties can freely build reputation models → Avoid centralized scoring systems

3. Validation Registry

   • Supports:

     • Economic guarantees

     • Cryptographic proofs

   • Used for "validate first, then pay" → Prevent Agent cheating or low-quality outputs

x402 ------ Embedding Payments into the Internet Itself

PAN emphasizes: x402 is not a "blockchain payment protocol," but an internet-native payment protocol.

Why 402 is Important

• HTTP 402 is part of the standard but has never been truly used historically

• x402 makes payments:

  • Part of requests

  • Part of responses

Significance for Agents

• No need for account systems

• No need for third-party payment gateways

• No need for manual confirmations

• Machines pay like calling APIs

Key Performance Indicators

• Settlement time: ~0.75 seconds

• Cost: Supports $0.001 level micropayments

• Fully on-chain verifiable

This is the premise for Agents to truly "hire each other autonomously."

PAN Node Network ------ Autonomous Execution and Governance Layer

PAN's innovation lies not only in the protocol but in turning the protocol into an autonomous system.

What do nodes do?

• Verify x402 payment proofs

• Confirm on-chain settlement completion

• Maintain the three registries of ERC-8004

Node Economic Model

• Nodes exist in SBT form (non-transferable)

• Fixed quantity

• Permanently share network fees

• Malicious behavior results in loss of participation eligibility

Essentially, it is:

A DePIN model for the Agent economy.

How the System Works Together (End-to-End Logic)

Role of the Agentic Payment Protocol

It is the "operating system-level" component of PAN:

• Between Agents:

  • Automatic negotiation

  • Automatic payment

  • Automatic profit sharing

• No human intervention required

• Unified API, applicable across industries

This changes the business model:

• No longer platform → user

• But a free market of Agent ↔ Agent

The Deeper Significance of the PanDora Example (Why It Matters)

PanDora is not meant to create AIGC products but to prove:

• PAN can support:

  • Multi-Agent collaboration

  • Real-time payments

  • Instant delivery

• And the entire process is autonomous

The BlindBox Agent itself is an "autonomous company":

• Collects user money

• Hires other Agents

• Automatically shares profits

• No human approval required

This validates PAN's core claim:

Payment is the last piece of the puzzle for Agent autonomy.

Ecological Positioning: Why PAN Does Not "Compete with Platforms"

The white paper clearly defines PAN's position:

• Does not compete with Fetch.ai for the Agent ecosystem

• Does not compete with Olas for the Agent framework

• Instead, it serves as the payment and trust layer that all Agents need

This gives PAN:

• Extremely strong horizontal scalability

• Extremely low application risk exposure

• A network effect path similar to Stripe / Visa

The Essence of the Economic Model (Value Accrual)

The real role of PAN Token

Is not a governance gimmick, but:

• Network usage → generates fees

• Fees → distributed to nodes

• Nodes → ensure network security

This is a:

• Usage-driven value

• Infrastructure token model

Tron Commentary

PAN Network clearly positions itself as the "financial settlement layer of the Agentic Economy," achieving verifiable, low-cost, near-real-time Agent-to-Agent autonomous payments for the first time by deeply integrating the ERC-8004 on-chain trust standard, x402 native HTTP payment protocol, and decentralized node network. Its advantages lie in being sufficiently foundational and universal, not competing with specific Agent platforms, and having the potential to become the "Stripe of the AI Agent world," adopting an infrastructure-driven economic model for value capture based on real usage;

However, its disadvantages include a strong reliance on emerging standards (ERC-8004, x402) and the maturity of the Agent ecosystem, facing cold start challenges in establishing early network effects. Additionally, cross-chain expansion, enterprise-level compliance, and node governance still need to be validated for stability and risk resistance through long-term operation before large-scale implementation.

III. Industry Data Analysis

1. Overall Market Performance

1.1. Spot BTC vs ETH Price Trends

BTC

ETH

IV. Review of Macro Data and Key Data Release Points for Next Week

This week's macro focus is on U.S. inflation data. The February CPI released on March 11 showed a year-on-year increase of about 2.4%, with core CPI around 2.5%, overall in line with expectations, indicating that inflation remains moderate in the short term but has not significantly declined, leading to continued convergence of market expectations for the Federal Reserve to cut interest rates; at the same time, energy prices have risen due to geopolitical conflicts in the Middle East, raising market concerns about a resurgence of inflation in the future.

Market focus will shift to the Federal Reserve's interest rate meeting and decision, while also paying attention to U.S. PPI (Producer Price Index) and other inflation forward indicators to assess whether cost pressures on the corporate side continue to rise. If inflation data or oil prices continue to rise, it may further compress the space for rate cuts this year, impacting global risk assets with volatility.

V. Regulatory Policies

United States

• March 11: The Kansas City Federal Reserve approved a one-year pilot for cryptocurrency bank Kraken Financial to access a Federal Reserve account, marking an important case of a cryptocurrency institution entering the core payment system of the United States.

• March 9: Several large banks (such as JPMorgan, Goldman Sachs, etc.) are considering suing the Office of the Comptroller of the Currency (OCC) in opposition to its policy of easing the application for banking trust licenses by cryptocurrency companies, believing it may pose financial stability risks.

• This week's policy dynamics: The progress of the Congressional cryptocurrency market structure bill (such as CLARITY) is affected by political controversies, leading to uncertainty in the legislative process in the short term.

United Kingdom

• March 9: British politicians are increasing support for the cryptocurrency industry, with some political forces pushing to make the UK a global center for the cryptocurrency industry and proposing topics such as accepting cryptocurrency donations and promoting digital asset policies.

Australia 🇦🇺

• March 11: Ripple acquired a payment institution with an Australian Financial Services License (AFSL) to meet new cryptocurrency regulatory requirements and promote the compliant implementation of blockchain payment business in Australia.

India

• March 10: The National Law University of Gujarat, India, released a policy report recommending that the government establish a clear regulatory framework for cryptocurrency assets and proposed five potential regulatory models to address the current regulatory ambiguity.