Most AI agents fail before they ever reach a user. Wrong memory design. Broken tool calls. No fallback logic. Latency that kills the experience. I've made every one of these mistakes — and fixed them in production for real B2B clients across India and UAE. Currently building a multilingual inbound voice agent for a Bangalore agency — 800ms response latency in production. I build agentic systems, voice agents, and full-stack AI products that actually ship. LangGraph, CrewAI, Claude, Gemini, LiveKit, Sarvam, Vapi — not tutorials, not demos. Production code. Book a session if you're one of these people: → You're a dev who's done the courses but never shipped a real agent — I'll get you from prototype to production → You're a founder who wants AI inside your product but don't know where the stack starts — I'll map it for you in 45 minutes → You're building a voice agent and stuck on latency, routing, or handoff logic — this is what I'm building right now → You want to freelance as an AI engineer — I went from zero to paying clients in India and UAE and I'll show you exactly how → You're a student trying to break into AI engineering — I'll tell you what actually matters and what's just noise I don't do theory. Every session is based on systems I've personally shipped using Next.js 14, Fastify, PostgreSQL, TypeScript and Python. If you want someone who's been in the terminal, not just the slides — book a session.