🤖 [Building]Rasputin_Loop: a Slack-native agent, one brain, no router
A single Strands agent loop (MiniMax M3) that thinks, calls a tool, and replies in-thread -> no intent parser, no command router. Provenance-stamped episodic memory in SQLite, hybrid RAG over libSQL/Turso fusing FTS5 + local embeddings via Reciprocal Rank Fusion, runtime MCP tools, Jira auto-triage, guardrails, and a `loop-eval` golden-set CI gate. Runs several distinct Slack apps from one process. Repo: github.com/Allmight-456/Rasputin_Loop.
Self-hosted long-running agent boxes, kept alive specifically to watch where production-grade agent loops degrade. Tool-loop convergence, memory bleed across runs, where they crack under sustained load. Operational notes feed back into SkillForge.
Wiring them *into* the LLM workflow itself, not bolted on after. The open question: where do evals belong -> pre-tool, post-tool, or as a separate critic agent?
🧠 [Agent memory]mem0 vs SkillForge
mem0 for long-horizon memory. Mapping the gap between mem0 (episodic, vector-backed) and SkillForge (procedural, AST-indexed) -> different halves of the same problem.