Is the Infrastructure Ready for Autonomous AI Agents?
1. Introduction: The Dawn of Autonomous AI Agents
The world of artificial intelligence has reached a pivotal moment since last year. AI agents, once limited to simple chatbots and rule-based automation, have evolved into sophisticated, autonomous entities capable of navigating the complexities of both Web2 and Web3 environments. These agents are no longer confined to answering customer queries or performing repetitive tasks but they are now web-native, operating seamlessly across platforms, executing complex workflows, and even making decisions in decentralized ecosystems. This evolution relies heavily on infrastructure: tools to build and manage these agents, and the computational power to support them. The infrastructure is especially important for the safety and security properties of the AI agents because the use of a tampered AI agent could result in the loss of funds. Another serious concern is around the availability of these agents as an unavailable agent may have an impact on time-sensitive tasks such as margin calls. Two examples that come up in this space are AltLayer’s Autonome and Hyperbolic, each tackling a piece of this puzzle.
Autonome, powered by AltLayer, is one approach to creating AI agents for decentralized blockchain setups. It’s part of a broader idea called the "Verifiable Agentic Web," where agents act independently and their moves are tracked on-chain for transparency. On the flip side, Hyperbolic takes a different angle with a marketplace for decentralized GPU compute, letting agents tap into processing power without relying on centralized systems. These are just snapshots of how infrastructure is evolving to meet the demands of smarter, more independent AI.
*https://x.com/0xautonome
2. The Need for a Verifiable and Interoperable Agentic Web
The rise of autonomous AI agents signals a shift in how we interact with digital systems, particularly in decentralized ecosystems like blockchains. These agents (aka software entities capable of independent decision-making and action) hold the potential to redefine everything from finance to social networks. But for them to thrive, the infrastructure supporting them must evolve beyond today’s human-centric designs. This is where the idea of an "Agentic Web" comes in: a digital environment where agents operate efficiently, securely, and with minimal human oversight. For this vision to work, two qualities stand out as essential: verifiability and interoperability.
Why Verifiability Matters
Autonomous agents differ from traditional bots because they adapt and act based on goals, not just fixed rules. Whether managing a crypto portfolio or automating a workflow, they need to be trusted to perform as intended. Yet, most agents deployed today offer no guarantees about their autonomy or integrity. Without assurance that an agent hasn’t been tampered with, users risk financial losses, data leaks, or simply a breakdown in confidence. Imagine a DeFi agent tasked with rebalancing a portfolio during a market dip, if it’s compromised or unavailable, the consequences could be immediate and costly.
Verifiability addresses this by ensuring an agent’s actions can be checked and proven. It’s about building trust in a system where humans aren’t always in the loop. Technologies like Zero-Knowledge Proofs (ZKPs) and Trusted Execution Environments (TEEs) can help here, creating a setup where an agent’s behavior is cryptographically validated or executed in a tamper-proof space. AltLayer’s Autonome, for instance, leans on these tools to make agents verifiable, aiming to close the gap between promise and reliability in decentralized settings.
The Case for Interoperability
Agents won’t operate in isolation. As they specialize (i.e. one handling staking while another optimizes transaction routes), they’ll need to work together seamlessly. This is where interoperability becomes critical. In a Byzantine environment, where not every actor can be trusted, agents must prove to each other that they’re following agreed-upon rules. AltLayer calls this "Cross-Agent Routing" (CAR), a framework that lets agents collaborate across tasks while maintaining security and efficiency.
Without interoperability, the Agentic Web risks fragmentation. A lack of standardized ways for agents to communicate could lead to inefficiencies or silos, undermining their potential. Consider a future where agents manage everything from crypto trades to SaaS integrations and if they can’t share data or coordinate actions securely, the system stalls. Autonome tackles this with protocols for secure agent-to-agent communication, protecting data exchanges and ensuring availability for time-sensitive operations like margin calls.
A New Digital Backbone
Today’s web is built for humans. Think bank cards or social apps designed for our needs and limitations. Agents, though, don’t share those constraints. They can process vast datasets instantly, act without fatigue, and interact at machine speed. Existing infrastructure isn’t optimized for this. Traffic systems for self-driving cars, for example, would need a complete overhaul to match their capabilities. Similarly, the digital world needs a rethink to let agents operate at their full potential.
This isn’t just about efficiency but it’s about enabling a future where agents and humans coexist. In crypto, agents could simplify user experience by handling complex tasks like transaction routing, but only if their execution is trustless and visible. In science, they might accelerate discovery, but their outputs must be verifiable to stand up to scrutiny. Across domains, the Agentic Web demands a backbone that’s robust, transparent, and connected.
Autonome, Powered by AltLayer
Platforms like Autonome are stepping into this space, offering tools to build and manage agents with these principles in mind. By integrating Actively Validated Services (AVSs) for real-time checks and TEEs for secure execution, Autonome aims to address verifiability and robustness. Its approach to agent communication and availability tries to solve interoperability challenges, laying groundwork for a cohesive agent-driven ecosystem. It’s one take on how the infrastructure might evolve to support this new world order.
*https://x.com/0xautonome/status/1876335685634060630
The need for a verifiable and interoperable Agentic Web isn’t hypothetical but it’s a practical requirement as agents become more embedded in our lives. Without it, their autonomy risks being a liability rather than an asset. The question is how quickly and effectively the digital landscape can adapt to make this vision a reality.
3. Compute Power in the Age of AI Agents
As AI agents take on more complex roles such as managing DeFi portfolios, driving interactive games, or aiding scientific research, they demand more than just smart design. They need raw computational power to function, and that need is growing fast. Traditional centralized cloud providers have long filled this gap, but decentralized alternatives are emerging to challenge that model. Hyperbolic, with its GPU compute marketplace, offers one take on how this shift could play out, fitting into the wider push for infrastructure that supports autonomous agents.
*https://hyperbolic.xyz/
Decentralized Compute: A Different Approach
Hyperbolic’s system connects GPU owners with agents or developers who need processing power, cutting out the middleman of centralized cloud services. It’s built on a network where resources are shared, not owned by one provider, aiming for flexibility and lower costs. Agents can tap into GPUs as needed (more for heavy tasks, less when idle) with pricing tied to supply and demand, much like a crypto market. It’s a contrast to the fixed plans of companies like AWS, where you pay whether you use the full capacity or not.
This setup isn’t unique in its goals but it’s tailored to AI’s specific demands. Agents get compute power on the fly, and providers get tokens for contributing. It’s a straightforward exchange, though it raises questions about reliability and scale compared to established giants.
Agents Managing Their Own Needs
One angle Hyperbolic explores is letting agents handle their own resource allocation. Through a plugin tied to platforms like ElizaOS, agents can rent GPUs based on what they’re doing as in the case of scaling up for a real-time trading algorithm or cutting back during downtime. It’s a step toward independence, reducing the need for human oversight. The system uses tokens to settle these transactions, with prices shifting as availability changes. If more GPUs are online, costs drop; if demand spikes, they rise.
It’s a practical idea, but not without trade-offs. Agents need to be smart enough to optimize this process, and the network has to keep up with sudden surges. It’s less about revolutionizing AI and more about testing how far autonomy can stretch when compute isn’t a fixed constraint.
Applications and Limits
This kind of setup could support a range of uses. In finance, agents might crunch market data for DeFi strategies, pulling extra GPUs during volatile periods. In gaming, they could power adaptive NPCs or dynamic environments, adjusting resources as players engage. Research, content creation or any field with heavy AI workloads could lean on it too. The pitch is flexibility: compute power that matches the task, not a one-size-fits-all plan.
But it’s not a silver bullet. Decentralized networks can lag behind centralized ones in consistency as in the case of downtime or uneven GPU quality. And while Hyperbolic talks up “Hyperintelligence,” where agents fully power themselves, that’s more a long-term idea than a current reality. It’s one piece of the puzzle, not the whole picture.
4. The Infrastructure Imperative for AI’s Future
The rise of autonomous AI agents isn’t just a story of smarter algorithms but it’s a story of the infrastructure that makes them possible. As these agents move from simple tools to independent actors in digital ecosystems, their success hinges on systems that can support their creation, coordination, and computational demands. The shift toward a decentralized, agent-driven web demands more than incremental upgrades; it calls for a rethinking of how we build the backbone of AI. Platforms like Autonome, powered by AltLayer, and Hyperbolic illustrate pieces of this evolving puzzle, each tackling a distinct challenge in the infrastructure landscape.
Autonome, from AltLayer, addresses the need for agents that can operate securely and connect seamlessly in a decentralized setting. By focusing on verifiability (ensuring agents do what they’re supposed to) and interoperability (letting them work together), it lays groundwork for a web where trust and collaboration don’t rely on central oversight. Hyperbolic, meanwhile, takes on the compute side, offering a decentralized marketplace where agents can access GPU power as needed. It’s an attempt to break from the rigidity of centralized clouds, giving agents the flexibility to scale with their tasks. Together, these approaches highlight two sides of the same coin: agents need both a reliable framework to exist within and the raw resources to act.