AI-Powered Tool Orchestration via Autonomous Agents ↗
→ • Architected a full-stack monorepo with real-time chat interface using Next.js 16/React 19 frontend and Express/tRPC backend, enabling seamless bidirectional communication. • Engineered an autonomous AI agent system using LangGraph with Plan → Route → Execute pattern, dynamically orchestrating 20+ MCP tools to execute complex multi-step workflows. • Reduced LLM token consumption by 90% through intelligent context management, implementing selective tool binding and conversation state pruning. • Achieved 80% faster response times by implementing smart model routing and prompt compression, dynamically selecting LLMs based on task complexity. • Decreased hallucinations by implementing Human-in-the-Loop (HITL) system with state-based approval workflows for safe execution of critical actions. • Increased autonomous task completion rate by 25% through self-correction mechanisms and reasoning loops for graceful error recovery. • Ensured 99.9% system uptime by deploying production infrastructure on AWS EC2 with automated CI/CD pipelines and containerized microservices.
