Agents Terminal V3

AGENTS TERMINAL V3 — Self-Improving AI Agent Orchestration Every interaction makes your AI team smarter. Every business on WhatsApp faces the same problem: customers ask the same questions daily: hours, pricing, orders. The chatbot answers some, fails on others, and the gaps repeat tomorrow. It never learns. For African SMEs this is critical, load-shedding kills uptime, no engineering team exists, and WhatsApp is the primary business channel running on a static AI. Agents Terminal V3 implements a compound loop: every customer message flows through n8n (84+ nodes, 6 workflows) → An LLM 7-intent classifier (200ms) → dual capture to Redis Cloud + PostgreSQL → daily artifacts across 4 time windows → 5-step memory loop (episode → lessons → promote → revise → index) → weekly gap analysis → weekly upgrade pipeline (A 7 phases pipeline generating FAQ suggestions, knowledge base entries, prompt refinements, handoff reviews) → human reviews → applies → smarter customer service the following week. Architecture: Docker containers for n8n + PostgreSQL. Redis Cloud for real-time streams. DeepSeek v4-flash for classification. Twilio + Cloudflare for WhatsApp ingress. 16-command orchestrator CLI. 4 JavaScript tools (capture.js, 3lm.js, review.js, promote.js). 3-Layer Memory: episodic, semantic, procedural — file-first, markdown-first. 19 connections. 5 subsystems. 0 broken links. The loop compounds every week. Built with AMD GPU Cloud credits + Fireworks AI for AMD-optimized inference path. Team: AI-Suplex Labs GitHub: github.com/kmagwenzi/Agents-Terminal-V3