AI Engineer’s Field Guide

What it does

Most AI system designs fail before the first model call because engineers pick a model or vector DB before framing the business decision. This Field Guide flips that: a top-down method mapping any problem onto 5 architecture pillars (Data, Intelligence, Orchestration, Guardrails, UX). Includes decision trees (RAG vs fine-tuning, agents vs single call, chunking), a phased build roadmap with cloud mappings, and a 10-incident production playbook. Interactive HTML + offline PDF.

AI Engineer’s Field Guide with Sanjay G · A practical playbook for designing production AI systems · Digital Product · ₹189 · Topmate

Turning a real business problem into a reliable, production-ready AI system is where most teams get stuck. You may understand RAG, embeddings, prompts, or model training. The AI Engineer’s Field Guide is a practical, interactive framework for going from a vague business AI use case to a clear solution design, architecture, build roadmap, and operating model. This is not another “build a chatbot” tutorial. Nor is it a 300 page theory textbook. This guide teaches you how to think top-down through any AI business problem and design the right system around it. “How do I think through and architect any AI use case from first principles?” Most real-world AI systems are hybrids, but one pattern…from topmate.io

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