LLM Apps That Work

Your demo amazed everyone. Then a real user typed something messy, the retriever pulled the wrong doc, and the model answered with perfect grammar and total confidence that the export limit was 50,000 rows when it is 10,000. No error fired. The 200 status hid a silent failure that cost a support ticket, a refund, and a point of trust you cannot buy back. This book exists because the model is not the product. The system around it is.
Following the journey of SupportMate, a support assistant that handles 10,000 customer questions, you will learn why reliability is a contract, not a property, and how to meet it across 6 pillars: accuracy, grounding, consistency, safety, availability, and cost per good answer. You will stop asking for perfect and start building for defensible, where every claim cites a source you can check.
Inside, you will discover:
• How to define the job in 1 paragraph and draw the boundary before writing 1 line of prompt code
• Prompting that holds up, separating system from user, versioning every change, and using 2 examples not 20
• Context as the product, placing the decisive document at the top where attention is 3 times stronger
• RAG that works, cleaning chrome, chunking on headings, keeping 200 authoritative docs instead of 2,000 noisy ones, and refreshing the index every 24 hours
• Retrieval that actually retrieves, hybrid search plus metadata filter plus reranking that lifts recall from 71% to 86%
• Grounding checks that require citations and run a fact check pass so unsupported claims never reach the user
• Agents with iteration caps, progress trackers, and human checkpoints before any write or spend action
The companion site includes a golden set of 50 cases, trace schemas, and guardrail tests you can run on Monday. With evaluation gating every release, observability showing every trace, and user feedback feeding the next test, you will ship answers that are boring in the best way, correct, cited, and cheap enough to keep.