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Our Vision of an Agentic Economy

Empowering a New Era with AI Agents

AI agents, also known as Large Action Models, are an emerging technology set to revolutionize industries by automating tasks traditionally performed by humans. These advanced artificial intelligence models comprehend and execute complex tasks by translating human intentions into actionable steps. The rapid growth in the size and capabilities of AI models, coupled with advancements in their reasoning abilities, positions them as ideal candidates for automating sophisticated tasks previously achievable only by humans.

Bridging the Gap Between Understanding and Action

While Large Language Models (LLMs) excel at understanding and generating context-driven data, enabling them to take automated actions requires several key capabilities:

  • Accurate Intent Understanding: A strength they already have
  • Secure Information Retrieval: Accessing required information from various sources, including personal user data and conversation history (memory), while ensuring the privacy and security of user information.
  • Structured Action Planning: Generating organized action plans based on interpreted intent and retrieved data.
  • Action Translation: Converting each step of the plan into actionable formats (e.g., API calls or web actions).
  • Execution and Confirmation: Carrying out actions and providing fulfillment receipts.

AI agents may collaborate with other agents and human experts and interact with external services to effectively retrieve information and execute actions.

Overcoming Challenges in a Human-Optimized Digital World

A significant challenge in designing AI agents is that the internet and digital systems are optimized for human interactions. AI agents do not share the same limitations as humans and may find human-centric user experiences (UX) restrictive, potentially hindering their performance.

For example, current authentication systems—using usernames, passwords, push notifications, or biometric factors—are tailored for humans who may struggle to remember complex authentication keys. These methods can be less efficient for AI agents. In contrast, key-based authentication utilizing Public Key Infrastructure (PKI) signatures or other cryptographic algorithms is effortless for AI agents, which are not constrained by human memory limitations and can efficiently perform the required cryptographic computations.

Similarly, traditional digital payment mechanisms like credit cards are designed for human usability. Digital-native payment systems based on advanced cryptographic digital wallets and blockchain technology offer more secure and efficient payment rails suitable for AI agents.

Establishing Identity and Memory for AI Agents

As humans, we possess sovereign identities and control over our personal memories with full privacy. In contrast, the large deep neural network models (LLMs, diffusion models, etc.) that AI agents operate on are inherently stateless. Their outputs and reasoning depend on the context provided to them, which includes historical interactions (memory) and identity context necessary to perform tasks and reason on behalf of humans.

To fully realize the potential of AI agents, they will require portable identities and memory contexts. This will enable them to switch between different models and interact seamlessly with other agents, ensuring continuity and coherence in their operations.

Problem

While the current internet user experience (UX) is optimized for humans, AI agents are on the rise, and AI economies are emerging. To fully unlock their potential, we need AI-native solutions built from the ground up to empower AI agents to perform human tasks. Some of the challenges AI agents currently face include:

  • Authenticating to perform tasks on behalf of users.
  • Handling payments and accessing financial rails in the digital space to pay for goods and services.
  • Retrieving users' conversation contexts and history (a.k.a. users' agents' private memories) while protecting users' security and privacy.
  • Collaborating with human experts and other AI agents to achieve objectives.
  • Monetizing their skills.

Solution

A set of emerging technologies has come together which can enable us to offer a robust solution for scalable AI agent economies. These technologies include:

  • Portable, verifiable identities:
  • Blockchain, stablecoins, and crypto digital wallets
  • Encrypted vectorized data availability layers
  • Trusted execution environments for key management and privacy

Tesser equips users with an identity system based on Decentralized Identifiers (DID) and Verifiable Credentials. These mechanisms are designed for multi-agent environments with diverse trust boundaries, leveraging public-private key infrastructure to enable secure delegation of access between agents. Users maintain full control, with the ability to revoke access across devices and services in cases of misbehavior, eliminating the need for external authorities typical of conventional OAuth/OIDC models. This approach empowers users to securely delegate access to their online accounts while applying granular authorization controls to monitor and manage agent behavior.

Tesser also includes a secure digital wallet for AI agents, enabling them to manage their identities and handle financial transactions while keeping users in control by allowing budget limits to be set for online payments. Built on blockchain-based stablecoins, these wallets facilitate fast, low-cost transactions with real-time verification, all secured through cryptographic signing. This approach offers transaction rails that are faster, more secure, and more transparent than traditional banking systems.

Additionally, Tesser integrates an AI agent memory layer built on a vectorized data availability layer. This feature allows users to manage their agents’ memory securely, with full control over access. By issuing or revoking verifiable credentials tied to each agent’s identity, users ensure continuity, privacy, and accountability in agent operations.

To envision how Tesser can provide a universal trust layer in an Agentic economy, following are some example usecase scenarios.

Example Scenarios

Secure Delegation of Access to Online Accounts:

A user needs to delegate access to their online accounts to an AI agent for a specific task, such as managing their social media presence. With Tesser, the user can issue verifiable credentials to the AI agent, granting it secure access to the required accounts and permissions, which are managed within Tesser’s trusted vault. The user can also define time limits and budget constraints for the agent’s activities, ensuring it operates strictly within the user’s specified parameters.

Corporate Agent Onboarding and Cross-Agent Collaboration

A company integrates Tesser into its HR operations to onboard employees and assign them AI agents tailored to their roles. For example, a marketing employee’s AI agent might need to collaborate with an external agency’s AI agent to produce campaign assets and execute marketing campaigns. Using Tesser, the marketing agent can securely delegate access to specific internal resources, such as files in the company’s vault or social media accounts, by issuing verifiable credentials. The marketing agent can also transfer stablecoins as payment or a deposit to the external agent’s digital wallet. The entire process is securely logged on Tesser's data availability layer, and permissions can be revoked or adjusted in real time, ensuring operational security and accountability.

Streamlined Smart Home Deliveries

A user incorporates Tesser plugin in their smart hub to manage interactions with external agents, such as a delivery robots. Through Tesser’s platform, the user issues a verifiable credential to the delivery agent, granting temporary one time access to their smart lock. The credential allows the delivery agent to unlock the door and deliver the package securely. Once the delivery is completed, the credential automatically expires, ensuring their home remains secure.

By building Tesser's authentication and authorization layer on top of an open and interoperable trust layer based on Decentralized Identities and Verifiable Credentials infrastructure, we can enable a wide range of use cases that require secure interactions between agents and users across different personal and enterprise trust domains and devices with seamless integration and security. Tesser's decentralized data availability layer and trustless ledger ensure that all partners remain in control, allowing them to monitor access permissions across their chain of trust and securely revoke them at any time in response to misbehavior by internal or external agents. This trustless integrated approach provides robust security and accountability.