Hermes — Local AI Agent

Hermes — Local AI Agent OS with production-grade guardrails

Hermes is a multi-actor agent system I built to run my own freelance operation: it scans job opportunities, scores them against hard criteria, and drafts proposals — but never sends anything. Every output lands in a drafts folder for human review.

What makes it interesting as an engineering project:

→ Multi-actor architecture: specialized agents (opportunity radar, filtering, drafting) each running on the cheapest model that can do the job — volume tasks on lightweight models, premium models reserved for high-stakes output → Hard filters that are actually hard: no "when unsure, keep it" escape valves that let LLMs rationalize around clear disqualifications → Regression fixtures for prompts: every prompt change runs against a fixed batch of real-world cases before shipping — TDD discipline applied to agent behavior → Draft/approval mode by design: the system augments human judgment, it never replaces it → Built on the Anthropic SDK with structured context files (profile, rules, scoring criteria) as the agent's operating system

Full architecture notes (in Spanish): ldamoredev.github.io/personal-agent-os-notes/es/

This project is my testbed for the patterns I ship to clients: agent systems that are cheap to run, safe to operate, and tested like real software.