Case Study 03 AI Systems & Multi-Agent Ops Shipped to Production

Autonomous Multi-Agent Orchestrator & Vector Memory Core

Engineered a hierarchical supervisor-worker runtime that deploys autonomous AI coding & research agents across parallel Git worktrees with deterministic safety gates, persistent ChromaDB memory, and real-time USD budget ceilings.

Python 3.12 Asynchronous Runtime Model Context Protocol (MCP) ChromaDB Vector RAG Git Worktree Isolation Dead-Man's Switch Daemons Real-Time Spend Ledger

THE BOTTLENECKS

Hallucinations, Token Burn & Chaos

LLM subagents running into recursive loops and consuming hundreds of dollars in API credits.
Lack of persistent memory across sessions forcing agents to re-learn codebases from scratch.
Concurrent agents clobbering each other's code files on disk without branch isolation.
No deterministic guardrails to prevent unvetted schema modifications or destructive file deletes.

THE ARCHITECTURE

3-Layer Deterministic Supervisor

Layered architecture strictly separating natural directives, LLM routing, and Python execution.
ChromaDB vector embedding pipeline storing lessons, API quirks, and architectural rules.
Git worktree orchestration running multiple worker agents in isolated branches concurrently.
Out-of-band kill switch and hard USD spend caps enforcing automated termination.

System Topology

Engineered Components & Safety Loop

LAYER 01

Supervisor Core

Hierarchical supervisor evaluating objective completion, token expenditure, and tool permissions.

LAYER 02

MCP Server Fabric

Standardized Model Context Protocol servers exposing deterministic tools, memory search, and telemetry.

LAYER 03

Worktree Isolation

Isolated temporary workspaces created on-demand per subagent with automated diff verification before merge.

LAYER 04

Vector Memory (RAG)

ChromaDB semantic index capturing solutions, API schemas, and historical fixes across developer sessions.

Core Modules

Engineered Capabilities

🛡️

Deterministic Stop Gates

Automated pre-tool validation blocking SQL migrations, production environment changes, and destructive git commands without human authorization.

🧠

Lifelong Vector Memory

Autonomous memory harvesting extracts verified architectural decisions from chat logs and embeds them for sub-100ms semantic lookup.

💰

Live Spend Ledger & Circuit Breaker

Real-time token counting per subagent with strict USD hard caps, preventing surprise API invoices through automated out-of-band process termination.

🔄

Self-Improving Skill Capture

When an agent solves a novel problem, the solution is validated across 3 independent safety gates and codified as a permanent reusable directive.

Custom Sprint Delivery

Want to Deploy Autonomous AI & Multi-Agent Infrastructure?

Available for 2–4 week custom deployments to build enterprise MCP servers, hierarchical agent supervisor loops, or bespoke semantic memory cores.

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