Question 1

What does Ahmed Sheikh do?

Accepted Answer

Ahmed Sheikh is a cloud-native agentic AI engineer who helps medium and large businesses move AI agents from stalled pilots to reliable, governed production. He specialises in multi-agent orchestration, agentic RAG, LLMOps, AI evaluation, and cloud-native AI infrastructure — serving clients worldwide.

Question 2

What does Ahmed Sheikh build, and what does it cost?

Accepted Answer

Ahmed builds production-ready AI applications as three fixed-price packages, each with an optional monthly retainer for ongoing work after launch: a Full-Stack AI App ($800, or $350/month), an Enterprise Full-Stack Agentic AI build with multi-agent orchestration, agentic RAG, evals and observability ($2,000, or $800/month), and a Custom Product scoped and quoted on a call. Payments are processed worldwide via Paddle.

Question 3

Why do most enterprise AI agent pilots fail to reach production?

Accepted Answer

Research shows only 11–14% of enterprise AI agent pilots reach production at scale. The primary reasons are orchestration complexity, inadequate evaluation and output validation, LLMOps debt, poor retrieval quality in RAG pipelines, and lack of governance controls. These are the exact failure modes Ahmed's engagements are designed to address.

Question 4

Does Ahmed Sheikh work with medium and large businesses globally?

Accepted Answer

Yes. Ahmed works with medium and large businesses worldwide, remotely. He delivers fixed-price AI application builds with optional monthly retainers — including full-stack AI apps, enterprise agentic AI systems with multi-agent orchestration via LangGraph, agentic RAG implementation, and LLMOps infrastructure.

Question 5

What technologies does Ahmed Sheikh use for agentic AI systems?

Accepted Answer

Ahmed builds agentic AI systems using LangGraph for multi-agent orchestration, LangChain for RAG pipelines, Python and FastAPI for backend services, Next.js and TypeScript for interfaces, and cloud-native infrastructure on Vercel, AWS, and Docker/Kubernetes. He also designs evaluation harnesses, output validation layers, and LLMOps monitoring stacks.

Writing.

Why 86% of Enterprise AI Agent Pilots Fail to Reach Production

Agentic RAG in Production: Evaluation, Guardrails, and the Failure Modes Nobody Warns You About

LangGraph Multi-Agent Orchestration: A Reference Architecture for Mid-Market Teams