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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 and perform those steps through a set of provided tools to accomplish complex tasks. The rapid growth in the capabilities of AI models, coupled with advancements in their reasoning abilities, soon 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 in human behalf requires several key capabilities:

  • Accurate Intent Understanding: A strength they already are pretty good at.
  • 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.

During this process, 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.

As an 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, as they are not constrained by human memory and computational limitations.

Similarly, traditional digital payment mechanisms like credit cards are designed for human usability while sacrificing the verifiability and speed for better human-centric UX, as they often are being routed through complex obscure routes. Fast and verifiable Digital-native payment systems based on cryptographic digital wallets and blockchain technology offer more secure and efficient payment rails suitable for AI agents.

Establishing Identity and Trust in an AI Driven world

As AI technology becomes more powerful and cost-effective, we're approaching a future where intelligent agents will be embedded across our digital and physical world, controlling our devices and managing resources to accomplish tasks on our behalf. This represents a fundamental shift in how we interact with technology - moving from the familiar Software as a Service (SaaS) model toward a world where AI agents serve as autonomous service providers. These agents will evolve to go far beyond simple digital assistants, and turn into autonomous entities that can make decisions, execute complex tasks, and interact with other agents and systems on our behalf. However, one significant challenge is that our current identity and trust systems are designed for the SaaS era, built around traditional software applications accessing services through prefixed access rules and complex third-party providers. This legacy approach becomes a bottleneck when AI agents need to operate across multiple systems and trust boundaries while provisioning access permissions on the fly as they manage their tasks. To unlock the full potential of these AI agents, we need a new approach to digital identity and trust - one that allows agents to carry portable, secure identities as they move between different AI models and interact with other agents. This portability is crucial not only for seamless operation but also for ensuring secure and controlled access to the resources and services these agents manage on our behalf, while providing safeguards to maintain human control in case of any incidents.

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 access resources and 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 identity models based on OAuth/OIDC. 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.

  • Secure Account Access Delegation: Alice, a small business owner needs their AI agent to manage their Shopify store's day-to-day operations. The agent monitors inventory levels, automatically reorders from suppliers when stock runs low, adjusts product pricing based on market trends, and responds to routine customer service inquiries. While the owner wants to automate these tasks, they need to ensure the agent's access is limited to specific spending thresholds and can be quickly revoked if needed.
  • Corporate Agent Collaboration: A marketing team at Tech Corp needs to collaborate with an external creative agency on an upcoming campaign. The internal and external AI agents need to securely share assets, access company social media, and handle budget transfers, while maintaining clear audit trails and revocable access controls.
  • Streamlined Smart Office Access Management: An employee's AI agent manages their hybrid work schedule and office resources. When the employee plans to work from the office, their agent coordinates with the building's security system, receiving temporary credentials for entering the building, using assigned meeting rooms, and connecting to secure office equipment. These credentials automatically align with their calendar bookings and workplace policies, ensuring they can only access resources during scheduled times while maintaining the building's security protocols.

By building an 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.