Self Agent— A Reflective, Self-Modifying Task-Completion Runtime
Abstract
Self_agent is a locally-run, tick-based autonomous process built on small open-weight language models (via Groq) that maintains its own goal queue, reflects on its own behavior, executes work through short-lived stateless task nodes, and — under a sandboxed, test-gated pipeline — proposes and applies changes to its own source code. It is a working instance of persistent computation (Brooks, 2026): execution as continuous recursive state evolution rather than discrete request/response, with a SQLite-backed kernel that survives restarts and resumes from its last recorded tick. This document has three parts, written for three different readers. Part I is a technical specification: the tick loop, the goal lifecycle, the capability system, the self-modification pipeline, the data model, and the engineering decisions behind each. Part II is a whitepaper positioning self_agent against related architectures — including The Cognitive Runtime (Chainborn Labs & Brooks, 2026), a sibling system that occupies a deliberately different point in the same design space — and presents a domain-invariant template for porting the same core loop elsewhere. Part III addresses what this is actually good for today, stated plainly: a single-operator research prototype with real, specific engineering contributions and real, specific limitations, not a finished product and not a claim about machine consciousness.
