Build agents via YAML with Prolog validation and 110 built-in tools
I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural…
In plain words
The Edge Agent is a platform for building and deploying AI agents defined in YAML with Prolog-based validation of language model outputs. It includes 110 built-in tools and uses neurosymbolic reasoning to reduce hallucinations by combining neural processing with logical validation. The system supports configuration overlays for environment-specific deployments without code duplication. It is designed for developers and teams who need production-grade agent orchestration with deterministic behavior and verifiable outputs.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I'm one of the creators of The Edge Agent (TEA). We built this because we needed a way to deploy agents that was verifiable and robust enough for production/edge cases, moving away from loose scripts. The architecture aims to solve critical gaps in deterministic orchestration identified by *Prof. Claudionor Coelho Jr. (Stanford alum, ML/DL Faculty at Santa Clara Univ., and Senior Fellow for AI at Majestic Labs)* during our work on the Kiroku project. *Key Technical Features:* * *Neurosymbolic Native:* We integrated Prolog to logically validate LLM outputs. This combines neural flexibility with symbolic reasoning to help mitigate hallucinations. * *YAML + Overlays:* Agents are defined in YAML with overlay support (similar to the Kustomize pattern in Kubernetes), making configs testable and reproducible across environments (Dev/Prod) without code duplication. * *Hybrid Scripting:* * *Lua:* Embedded in all binaries (Python, Rust, Wasm) for secure, lightweight logic at the Edge. * *Python:* Full integration for data science workloads. * *Batteries Included:* We implemented 110+ tools based on Sarwar Alam’s Agentic Design Patterns. https://github.com/sarwarbeing-ai/Agentic_Design_Patterns * *Polyglot:* Core written in Rust/Python with Wasm support (runs in browser, Docker, or embedded). * *Observability:* Native hooks for Comet (Opik) to track execution/cost. The goal is to provide a solid engineering foundation for agents. I’d love to hear your feedback on the Prolog integration and the YAML-based architecture. Repo: https://github.com/fabceolin/the_edge_agent Demo (Wasm): https://fabceolin.github.io/the_edge_agent/wasm-demo
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