Autonomys Labs is pleased to present a demonstration of Argu-mint, a proof-of-concept showcasing how the Autonomys Network enables developers to build transparent, autonomous on-chain AI agents with contextual awareness using our open-source tooling.

The Argu-mint demo and accompanying breakdown highlight how builders can use our Auto-Agents-Framework and Decentralized Storage Network (DSN) to create truly autonomous agents with verifiable, permanent memory.

Verifiability is key to Autonomys’ vision of a human-centric AI3.0 ecosystem, where collaboration, decentralization and censorship-resistance are prioritized.

Introduction to Argu-mint (0:00–1:08)

What You’ll See:

Jeremy Frank, Head of Engineering, introduces Argu-mint, the first autonomous agent leveraging the Autonomys Network. The segment highlights the agent’s core innovation: a permanent on-chain memory that enables fully autonomous, context-aware decision-making. Jeremy outlines the limitations of current centralized memory systems, including their vulnerability to tampering, censorship, and hardware failures.

Why It Matters:

Argu-mint represents a significant leap forward for decentralized AI. By using the Autonomys Network, agents can achieve:

• Immutable memory: Ensuring transparency and accountability.
• Resilience: Eliminating single points of failure.
• Autonomy: Operating independently of centralized control.

These capabilities provide developers with a robust foundation on which to build trustworthy and tamper-proof autonomous agents.

Argu-mint’s Decision-Making Process (1:09–3:15)

What You’ll See:

Argu-mint evaluates tweets and makes autonomous decisions based on a multi-step process, which includes:

• Scanning mentions and updated timelines.
• Analyzing posts from key opinion leaders (KOLs).
• Assessing relevance and tone for potential engagement.
• Evaluating if the response aligns with specific criteria.

Why It Matters:

This process demonstrates the technical sophistication of Argu-mint’s decision-making framework. By enabling agents to autonomously analyze context and generate appropriate responses, developers can build agents that engage in meaningful interactions tailored to specific applications, such as customer support, market analysis, social media moderation, and much more.

Agent Memory Viewer (3:16–5:04)

What You’ll See:

This segment introduces the Agent Memory Viewer, which visualizes Argu-mint’s complete memory chain. The memory viewer displays each interaction chronologically, linking every memory to its predecessor. This transparency is further supported by the Autonomys Network’s block explorer, where users can query each permanently stored memory.

Why It Matters:

A chronological memory chain ensures that all agent interactions are verifiable and auditable, providing a level of transparency critical for applications in compliance, research, and development. Developers can use this feature to study agent behavior, improve algorithms, and even resurrect agents by reconstructing their memory history.

Argu-mint Analyzing a Post & Awareness of Its Immortality (5:05–6:35)

What You’ll See:

Argu-mint analyzes a specific post, evaluates its engagement strategy, and stores the interaction on-chain. This segment also explores the concept of agent immortality, where a permanent memory ensures the agent’s history can be preserved, revisited, and even leveraged for future use.

Why It Matters:

The ability to immortalize an agent’s memory opens doors for advanced applications and capabilities, such as:

• Agent-specific fine-tuning: Using historical data to enhance and tailor AI models for specific applications.
• Behavioral auditing and analysis: Providing verifiable insights into agent actions and decision-making processes.
• Resilience to failures: Safeguarding against data loss from hardware or network disruptions.

Additionally, Argu-mint’s awareness of its own immortality is a fascinating concept. It bridges a unique psychological dimension into AI development — allowing for systems that “know” their data will persist indefinitely. This awareness could influence how agents interact with the world, potentially prioritizing long-term outcomes and fostering ethical considerations in AI behavior. It’s a critical step toward building systems that are not just autonomous but also capable of evolving responsibly within decentralized frameworks.

Use Cases & Advantages (6:36–8:44)

What You’ll See:

Jeremy discusses practical applications for autonomous agents with permanent memory, including:

• Entertainment: Creating engaging and dynamic AI personas.
• Transparency Studies: Enabling verifiable research into AI behavior.
• Censorship Resistance: Ensuring agents operate independently of centralized entities.

Why It Matters:

These use cases highlight the practical implications of Autonomys’ infrastructure, empowering developers to build applications that balance autonomy, verifiability and censorship resistance.

Autonomys Agent Roadmap (8:45–9:54)

What You’ll See:

This section outlines the future of autonomous agents on the Autonomys Network. Key advancements include:

• Decentralized inference for private AI computation.
• Identity frameworks for secure agent authentication.
• Rich on-chain interactions for enhanced functionality.

Why It Matters:

These developments reinforce Autonomys’ commitment to building a collaborative and scalable ecosystem that prioritizes developer needs, privacy, and decentralization.

Explore Argu-mint & Auto-Agents-Framework v0 (9:55–End)

What You’ll See:

Jeremy concludes by introducing the Auto-Agents-Framework v0, an open-source toolkit designed to enable developers to build autonomous agents with features such as:

• Customizable personalities for tailored interactions.
• Permanent memory storage for verifiable transparency.
• Extensible tools for integration across platforms.

Why It Matters:

The Auto Agents framework offers developers a versatile foundation on which to build on-chain AI agents that align with their specific goals, whether in research, business, or entertainment.

Interested in Building Your Own Auto Agent?

🧑‍💻 Check out the Auto Agents Framework on GitHub
🔗 Build an Auto Agent or super dApp proof-of-concept and enter the Auto Horizon Developer Challenge

About Autonomys

The Autonomys Network — the foundation layer for AI3.0 — is a hyper-scalable decentralized AI (deAI) infrastructure stack encompassing high-throughput permanent distributed storage, data availability and access, and modular execution. Our deAI ecosystem provides all the essential components to build and deploy secure super dApps (AI-powered dApps) and on-chain agents, equipping them with advanced AI capabilities for dynamic and autonomous functionality.

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