Skip to content

AI Agents

Period: 2025 – Present
Scope: AI Agents · Autonomous Systems · LLM Orchestration
Tools: OpenAI · Anthropic · Google AI · LangChain · LlamaIndex · PydanticAI · FastAPI · Docker

Overview

Design and development of autonomous AI agent systems capable of reasoning, memory management, tool execution, and multi-step task completion.

Focus on building production-ready AI systems that combine:

  • reasoning (LLMs)
  • memory (short-term & long-term)
  • action (tool execution)
  • orchestration (multi-agent systems)

System Architecture

flowchart LR
    A[User Input] --> B[Agent Reasoning]
    B --> C{Need Tool?}

    C -->|Yes| D[Tool Execution]
    D --> B

    C -->|No| E[Response]

    B --> F[Memory Update]
    F --> G[Long-Term Memory]
    G --> B

Key Contributions

  • Designed multi-agent orchestration systems for complex task execution
  • Built persistent memory architectures for long-context reasoning
  • Developed tool-augmented agents for real-world task automation
  • Integrated voice, text, and API-based interaction layers
  • Deployed scalable systems using FastAPI and containerized services

Works

Tech Focus

Agents · Tool Calling · Memory Systems · RAG · FastAPI · Docker

Impact

  • Delivered autonomous systems capable of multi-step reasoning and action
  • Reduced manual workflows through AI-driven automation
  • Improved reliability with memory + retrieval integration
  • Built scalable architectures for real-world deployment

Challenges

  • Managing context window limitations with long-term memory
  • Balancing latency vs reasoning depth
  • Ensuring tool reliability and error handling
  • Reducing hallucination with RAG + validation strategies