Pranathi Kamisetty

About

Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.

Experience

Education

Key Strengths

• Built and deployed an LLM-powered trip planning bot with multi-tool agent orchestration
• Designed zero-shot multi-label intent classification and priority-based tool-call sequencing for multi-intent queries
• Practical agent testing across varied input lengths and behaviors
• Reliability-focused evaluation: tool-call correctness, data fetch validation, and API operational checks (billing/expiry)
• Strong product collaboration translating UX/tone requirements (including Gen Z slang) into bot behavior

Reference Highlights

• Great learner
• Developed skills quickly
• Communicates well with non-technical team members
• Patient when answering questions
• Generally effective at explaining technical concepts
• Highly impactful on POC development
• Strong stakeholder communication
• Collaborative in production deployment
• Proactive in flagging risks and dependencies
• Timely responses
• Effective cross-team collaboration
• Guides teams through new frameworks via walkthroughs and demos
• Highly capable communicator of technical concepts
• Takes leadership in weekly progress updates
• Able to present complex AI frameworks to broader teams
• Standout performer among peer teams
• Successfully shipped an AI travel agent
• Handled bulk of chatbot build with minimal oversight
• Graceful handling of external dependencies and delays
• Strong soft skills alongside technical competence
• Clear communication with non-technical stakeholders
• Uses effective communication mediums (demos, written updates, meetings)
• Organized project tracking (JIRA, user stories, acceptance criteria)