Agent Execution Network (AEN)

The first open-source, community-powered AI execution platform that combines distributed compute, reusable AI skills, and real-world connectors into one intelligent network.

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Inspiration

The idea behind Agent Execution Network (AEN) started from a simple observation: AI is becoming more powerful, but it is also becoming increasingly centralized.

Running capable local AI models requires expensive hardware. Cloud AI requires paying for every request. At the same time, millions of computers around the world sit idle most of the day with unused CPU, GPU and memory resources.

Instead of treating every AI assistant as an isolated application running on a single machine, we asked a different question:

What if communities could pool their idle compute together and operate a shared AI execution platform?

That vision evolved into AEN.

AEN is designed as the first open-source, community-powered AI execution platform where organizations, developers, universities, creator communities, and open-source contributors can build specialized AI communities powered by many distributed workers instead of one machine.

Because AEN is open source, anyone can extend it, contribute to it, build new capabilities, and create specialized community AI networks without depending on a single vendor.

What it does

AEN transforms multiple independent computers into one coordinated AI execution network.

A Host creates a community, defines its policies, and coordinates execution.

Workers can securely join that community from anywhere in the world using signed invite tokens and encrypted networking.

Once connected, workers contribute compute, AI models, tools and capabilities to the network.

The Host plans incoming requests as workflows, distributes work across eligible workers, verifies execution, and combines results into a single response.

Communities can further specialize their network by installing custom Skills and approved MCP integrations, allowing each community AI to evolve independently.

AEN also exposes these community-powered AI systems to real users through connectors, with Telegram fully integrated today and additional connectors planned.

How we built it

AEN was built as a distributed AI execution platform rather than a traditional chatbot.

The system consists of:

  • A Host control plane responsible for workflow planning, scheduling, verification and policy enforcement.
  • Remote Workers that contribute local compute, AI providers and approved capabilities.
  • A secure WebSocket networking layer with authenticated worker onboarding.
  • Capability-aware scheduling and lease-based execution.
  • Distributed reasoning workflows.
  • Cloudflare Tunnel integration for secure remote connectivity.
  • Telegram integration for exposing community AI to real users.
  • A plugin architecture supporting custom Skills and approved MCP integrations.

We used GPT-5.6 throughout architectural planning, system design, documentation and engineering decisions.

We used Codex extensively to implement and harden some of the most technically challenging parts of the project, including:

  • Host/Worker networking
  • Secure artifact transport
  • Capability enforcement
  • MCP supervision
  • Custom Skill validation
  • Restart recovery
  • Distributed worker synchronization
  • Production hardening
  • Protocol refinement

Together, GPT-5.6 and Codex significantly accelerated development while allowing us to focus on higher-level system design and product direction.

Challenges we ran into

The hardest engineering challenge was building a networking layer that could reliably connect remote workers across different machines while maintaining security and fault tolerance.

Designing authentication, worker identity, capability verification, reconnect logic and secure communication required several architecture iterations before arriving at a reliable solution.

Balancing flexibility with security was equally challenging.

Because AEN allows communities to extend their networks with custom Skills and MCP integrations, we had to design strict approval mechanisms and capability validation so that extensions could be powerful without compromising network integrity.

Accomplishments that we're proud of

We're most proud that AEN works as an actual distributed AI execution platform instead of simply coordinating API calls.

Multiple remote workers can securely join one community, contribute local AI models and capabilities, execute workflows together, and expose the resulting community AI through real communication channels like Telegram.

We're also proud that the project is open source from day one.

Rather than building another closed AI product, we're creating a platform that developers and communities can extend, improve and specialize over time.

What we learned

Building AEN reinforced our belief that the future of AI is collaborative rather than isolated.

Distributed systems introduce significantly more complexity than single-machine applications, but they also unlock capabilities that centralized architectures cannot easily provide.

We also learned how valuable Codex and GPT-5.6 can be when used together.

GPT-5.6 helped us reason through architecture and system design, while Codex accelerated implementation of complex networking, protocol and infrastructure components.

The combination allowed us to move much faster without sacrificing engineering quality.

What's next for Agent Execution Network (AEN)

The current hackathon release is the foundation for a much larger vision.

Our roadmap includes:

  • More communication connectors including Discord, Slack, WhatsApp and REST APIs.
  • Community Skill Marketplace.
  • Distributed execution for local AI models across many workers.
  • Enterprise cloud deployment.
  • Community reputation and contribution systems.
  • Public APIs for developers.
  • Community discovery and sharing.
  • Specialized AI communities built around industries such as education, design, software engineering, healthcare and research.

Our long-term vision is for AEN to become the open infrastructure that enables communities everywhere to build, own and operate collaborative AI systems powered by their collective compute and expertise.

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