Autonomous AI Orchestration — 7 Agents, 4 Models, Zero Downtime
A cognitive agent architecture where Claude Code, GPT-5.4, MiniMax, and Gemini collaborate autonomously — with persistent memory, cross-model validation, and 20 production workflows.
7
Specialized agents200+
Daily automated tasks4
LLM providers24/7
Zero human interventionThe Challenge
AI assistants are stateless by design — every session starts from zero. That's fine for one-off questions. It breaks completely when you need a system that remembers decisions, learns from outcomes, and acts independently across multiple domains.
Real-world operations don't pause for a human to copy-paste context between tools. Lead generation, market intelligence, content production, code quality, infrastructure monitoring — each needs specialist attention, running in parallel, around the clock. The bottleneck isn't intelligence — it's operational bandwidth.
The Approach
Built a production orchestrator-worker system following multi-agent patterns formalized by Anthropic — 7 specialized agents, each assigned to a domain and the model best suited for it:
Dispatcher (Claude Code): Central orchestrator — routes tasks, resolves priority conflicts, and maintains Chronicle: a custom durable memory system with an append-only event log, point-in-time state reconstruction, and 700+ archived artifacts. Every decision and outcome is persisted and queryable years later.
Lead Scout (GPT-5.4): Monitors 15+ platforms, scores prospects with weighted relevance signals, and generates personalized outreach with automatic fallback chains across providers. Content Writer (GPT-5.4): Adapts messaging per target, A/B tests hooks, contextually references live case studies from this portfolio. Code Reviewer (Claude Code): Pre-commit quality gates with multi-file architectural reasoning and automated fix suggestions. Researcher (Gemini): Deep competitive intelligence across 1M+ token contexts — market positioning, technical docs, industry analysis. Data Monitor (MiniMax M2.5): Processes 68 OSINT feeds every 2 hours, runs anomaly detection, and publishes a live intelligence digest at digest.rzmrn.com. Telegram Bot: Human-in-the-loop approval interface with inline actions.
20 scheduled workflows run via macOS launchd: intelligence briefs, lead scouting, email triage, outreach campaigns, code review sweeps, industry scanning, memory snapshots, backup rotation, health canaries, and weekly retrospectives. Cross-model validation is built into every critical path — when one model generates, another validates. The system degrades gracefully: if any provider goes down, Chronicle preserves state and queues work for recovery.
Orbital diagram showing a multi-agent system with 7 specialized AI agents. The central Dispatcher routes tasks to Job Scout, Content Writer, Code Reviewer, Researcher, Data Monitor, and Telegram Bot. Click any node to see details and connections.
The Result
The system processes 200+ automated tasks daily with zero human intervention. The lead pipeline surfaces 10-15 qualified prospects per week. The OSINT digest covers 68 sources with 2-hour refresh cycles — live at digest.rzmrn.com. Code review catches architectural issues before they reach production.
Chronicle memory holds 700+ artifacts with full point-in-time reconstruction — no context is ever lost between sessions. The architecture is fault-tolerant by design: each component degrades independently, and no single provider failure can stop the system.
I make strategic decisions. The agents handle everything else.
