Dev S.

You need an AI application that actually works in production — not a demo, not a wrapper around ChatGPT, not a prototype that breaks when real users touch it. You need agents that reliably execute multi-step workflows, handle edge cases, and let humans stay in control. And you need the full product around it: the frontend, the backend, the database, the deployment. I build production-grade AI applications end-to-end. Multi-agent orchestration with LangGraph and LangChain. RAG pipelines with vector search. Human-in-the-loop approval workflows. Full stack delivery with Next.js, React, Python, Node.js, MongoDB, Postgres, and AWS. One developer, one codebase, shipped to production with CI/CD. I've been building MVPs for startups and solo founders for 8 years. Two years ago I went deep on multi-agent AI systems, and that's now the core of my practice. What I've Built AI-powered golf operations platform — 20+ coordinated agents built on LangGraph with tool usage, human approval workflows, RAG with MongoDB Atlas vector search, and checkpointed state management. Multi-tenant architecture on AWS serverless and containers, infrastructure managed with Pulumi IaC. Full Next.js/React frontend and two React Native mobile apps, real-time messaging, point-of-sale, analytics dashboards. CI/CD deployment on Vercel and AWS. From zero to production with real club users. Medical AI chatbot — Custom RAG agent for medical professionals using verified clinical data. Built with LangChain, deployed on AWS. Went from kickoff to live product in 60 days. Automated patient onboarding and reduced support tickets from day one. Healthcare patient monitoring MVP — Serverless architecture on AWS (Lambda, DynamoDB, API Gateway). Suggested product and UI changes during development that increased daily active usage 25% in the first month. Equestrian social network — Real-time chat, social features, media sharing. Full MVP delivered 20% ahead of schedule. Scaled to hundreds of users in two weeks with zero downtime. What I Actually Build (and Why It Matters) Most AI app ideas sound simple but are architecturally hard. "I want an AI assistant that can check my calendar, email a client, and book a venue" — that's not one LLM call. That's an agent orchestration problem: state management across multiple tool-calling agents, error handling when one step fails, routing logic to pick the right agent for each subtask, and human checkpoints so nothing fires without approval. That's LangGraph, not a prompt. This is the type of system I specialize in. If your product needs AI that goes beyond question-and-answer into actually doing things — browsing data, calling APIs, executing multi-step workflows, coordinating between specialized agents — that's my core work. If You've Already Started Building If you've prototyped something with Lovable, Replit, Bolt, Cursor, or any AI coding tool and now you're hitting walls — auth doesn't work right, the agent loops on edge cases, you can't deploy it reliably, it falls apart with multiple users — I can take what you've built and turn it into a real production system. You don't need to start over. I'll audit what you have, keep what works, and rebuild what needs proper engineering. This is increasingly common and it's a smart path — you validated the concept fast, now we make it real. Technical Stack AI/LLM orchestration: LangGraph, LangChain, OpenAI, Anthropic, Gemini, RAG, vector search, tool-use agents, human-in-the-loop workflows. Data and state: MongoDB (checkpointers, Atlas vector search), PostgreSQL, DynamoDB, MySQL, Redis. Backend: Python, Node.js, FastAPI, Express. Frontend: Next.js, React, React Native, Tailwind. Infrastructure: AWS (Lambda, ECS, S3, API Gateway), Docker, Pulumi, SST, Vercel. Practices: CI/CD, multi-tenant security, infrastructure as code, context engineering. How I Work We start with your product requirements. I'll map the agent architecture — which agents, which tools, which human checkpoints, which data sources — and give you a clear scope, timeline, and cost within 48 hours. You get weekly working demos of the actual application so we catch problems early. I prioritize what gets your product to users fastest and flag anything that's adding complexity without adding value. ⭐ Expert-Vetted — Top 1% on Upwork ⭐ If you're building an AI product that needs real multi-agent orchestration and full-stack delivery, message me with your project details. I'll respond within 24 hours with a concrete plan.