FULL STACK
DEVELOPER
I build digital products that refuse to be boring.
WHO_IS_ANURAG?
01B.Tech Computer Science Student
02Full Stack Web Developer
03AI & Automation Builder
04Persistent Problem Solver
"Building robust systems that bridge the gap between complex engineering and intuitive user experiences. Focused on clean architecture and high-performance logic."
// PROJECTS_BUILT
14+
// TECH_STACKS
10+
// DSA_PRACTICE
500+
// CURRENT_STATUS
BUILDING
TECHNICAL_MODULES
// CORE_CAPABILITIES_REPORT.V2
[ FRONTEND ]
- #React / Next.js
- #TypeScript
- #Tailwind CSS
- #Framer Motion
- #Three.js
[ BACKEND ]
- #Node.js / Express
- #Python / FastAPI
- #PostgreSQL / MongoDB
- #Redis
- #Docker
[ AI_GEN_AI ]
- #LLM Applications
- #Prompt Engineering
- #OpenAI / Anthropic SDKs
- #Pinecone / Vector DBs
- #RAG Pipelines
[ ENGINEERING ]
- #System Design
- #CI/CD Automations
- #Cloud (AWS/GCP)
- #Data Structures
- #Security Protocols
SELECTED_WORK
// REPOSITORY_SNAPSHOT.2024
DEBUGLY.AI
AI Developer Assistant leveraging LLM APIs to streamline debugging and coding workflows.
ZENFLOW.SaaS
Productivity-focused platform with real-time dashboards and persistent user workflow systems.
INDIALAND.LOC
Scalable location discovery platform focused on structured regional data and user exploration.
SPOTT.DISCOVERY
Discovery-driven platform focused on user engagement and scalable content delivery.
AGENTIC_AI_AGENTS
// COGNITIVE_PIPELINES_AND_AUTONOMOUS_WORKFLOWS.LOG
CUSTOMER SUPPORT RAG AGENT
AGENTIC_AIBuilt an intelligent customer support assistant that answers user queries using Retrieval-Augmented Generation (RAG). The system indexes a company FAQ PDF into a Chroma vector database using Mistral embeddings and retrieves relevant context before generating responses with an LLM. It also maintains conversational memory to provide context-aware answers across multiple interactions.
- ▶PDF-based knowledge base indexing
- ▶Semantic search via Mistral embeddings
- ▶Conversational memory persistence
- ▶Source-grounded AI response generation
MULTI-AGENT SCHEDULING ASSISTANT
AGENTIC_AIDeveloped a production-style multi-agent scheduling assistant using LangGraph. The application routes user requests through specialized agents that understand booking intent, validate available time slots, maintain conversation state, and simulate appointment scheduling. The workflow demonstrates stateful agent orchestration with conditional routing and persistent memory.
- ▶Multi-agent LangGraph orchestration
- ▶Intelligent routing & conditional edges
- ▶Booking workflow state machine
- ▶SQLite persistent checkpointer memory
- ▶Date normalization & slot validation
SYSTEM_ACTIVITY
// PERFORMANCE_METRICS.LOG
// STATUS_REPORT
- STATUS:ACTIVE_DEV
- COMMITS:DAILY
- LOCATION:DELHI_SYSTEM
- BUILDING:NEXT_GEN_UI
// PROBLEM_SOLVING
STREAK: 124_DAYS_ACTIVE
DEV_LOGS
// ENGINEERING_THOUGHT_PROCESS.MD
"Optimized API response times by 40% using Redis for query caching. Latency is the silent killer of user experience."
"Learned that UI performance during scroll events matters more than animation complexity. 60FPS is non-negotiable."
"Building AI agents taught me that system reliability and prompt engineering are often more critical than model size."
"Reduced bundle size by 30% by migrating to targeted imports. Architecture is as much about removal as it is about addition."
"Functional components are not just code; they represent units of maintainability. Refactoring is a feature, not a chore."
"Distributed systems require strict observability. If you can't measure it, you shouldn't build it."
CREDENTIAL_VERIFICATION
// TRUST_LAYER_CONFIRMED.0x01
FULL_STACK_INTERN @ TSOLE
SaaS_STARTUP // 2_MONTH_CYCLE
- ✔Optimized core SaaS dashboard UI for 100+ active enterprise users.
- ✔Integrated RESTful APIs with Node.js backend for real-time telemetry.
- ✔Implemented modular component architecture to speed up development cycles.
// PROJECTS_DEPLOYED
// AI_SYSTEMS_BUILT
// FULL_STACK_READY
// SYSTEM_DOWNTIME
// SYSTEM_HARDENING
"Consistently shipping robust code directly to production environments. Proven track record in building end-to-end applications from scratch to deployment."
// UPLINK_INITIATED
READY_TO_SHIP
THE_NEXT_PRODUCT
Currently accepting engineering missions for high-performance teams and forward-thinking products. Let's build something that refuses to be boring.
C:\>anurag_p --contact --urgent
Searching for secure uplink...
UPLINK_ESTABLISHED: [100% SUCCESS]
EXECUTE_MESSAGE_SEQUENCE