{"product_id":"lia-au-travail-sans-y-croire-aveuglement","title":"AI at work, without blindly believing in it","description":"\u003cp\u003e\u003cstrong\u003eUnderstand the mechanics, choose the uses, measure the returns.\u003c\/strong\u003e A language model knows nothing: it predicts the next part of a text. This statement may seem simplistic, but it is the only one that correctly explains both what these tools brilliantly succeed at and what they silently fail at.\u003c\/p\u003e\n\n\u003cp\u003eThis book starts from the actual mechanics to derive a working method. It sells neither enthusiasm nor distrust: it provides the criteria to decide, task by task, if the tool has a place.\u003c\/p\u003e\n\n\u003ch3\u003eThe six parts\u003c\/h3\u003e\n\u003cp\u003e\u003cstrong\u003eI. The Mechanics\u003c\/strong\u003e — What a language model really is, in one page. Tokens and context window, and why this explains billing, calculation errors, and the forgetting of instructions in long conversations. The complete typology of inventions — reference, precision, completion, sycophancy — and classified risk areas.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eII. The Judgment\u003c\/strong\u003e — \u003cstrong\u003eThe verification rule\u003c\/strong\u003e, which sorts all uses into one sentence. A green \/ orange \/ red grid of twenty-five uses. The three questions to ask before automating, including the one no one asks: will the error be isolated or systematic?\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIII. The Practice\u003c\/strong\u003e — The four factors that genuinely change the quality of a response, in order of impact. \u003cstrong\u003eSix reproducible instruction patterns\u003c\/strong\u003e, including the source constraint that eliminates most inventions. Folk techniques that are useless. RAG explained from beginning to end, with the five points that fail in practice. A decision tree between instruction, RAG, and fine-tuning.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIV. Industrialize\u003c\/strong\u003e — Build an evaluation set and measure instead of admiring. Design the three levels of human supervision and avoid automatic validation. The monthly cost formula and the five levers to reduce it. Choose a model based on seven criteria, and guard against dependency.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eV. The Risks\u003c\/strong\u003e — What you send and where it goes. GDPR and the European AI regulation: what concretely applies to a small structure. \u003cstrong\u003eInstruction injection\u003c\/strong\u003e explained with an attack example and six protections. Intellectual property and editorial responsibility.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eVI. The Usage\u003c\/strong\u003e — Ten sustainable uses, detailed. Eight that cost more than they bring in. How to recognize an unedited generated text, in eight signs. What will remain when the hype dies down.\u003c\/p\u003e\n\n\u003ch3\u003eWhat you take away\u003c\/h3\u003e\n\u003cul\u003e\n\n\u003cli\u003eA library of ready-to-use instructions: document analysis, rewriting, critique, structured extraction, subject mapping\u003c\/li\u003e\n\n\u003cli\u003eA 10-point checklist before using a model for a task\u003c\/li\u003e\n\n\u003cli\u003eA 12-point checklist before putting a system into production\u003c\/li\u003e\n\n\u003cli\u003eThe three-color usage grid\u003c\/li\u003e\n\n\u003cli\u003eThe instruction \/ RAG \/ fine-tuning decision tree\u003c\/li\u003e\n\n\u003cli\u003eA glossary of 12 terms\u003c\/li\u003e\n\n\n\u003c\/ul\u003e\n\n\u003ch3\u003eFor whom\u003c\/h3\u003e\n\u003cp\u003eFreelancers, small business leaders, and professionals who already use these tools daily and want to know where the safe zone ends. No technical skills are required for parts I, II, V, and VI; parts III and IV assume you are building something.\u003c\/p\u003e\n\n\u003ch3\u003eFor whom it is not\u003c\/h3\u003e\n\u003cp\u003eThose looking for a list of \"magic prompts\": the book explains precisely why such lists do not work. Nor machine learning engineers, who already know everything covered here.\u003c\/p\u003e\n\n\u003ch3\u003eWhat the book does not cover\u003c\/h3\u003e\n\u003cp\u003eModel training, deep learning mathematics, infrastructure choice, image and video generation, and a detailed analysis of the European AI regulation — the latter requires a lawyer, not a book.\u003c\/p\u003e\n\n\u003ch3\u003eFormat\u003c\/h3\u003e\n\u003cp\u003ePDF, 24 chapters and 4 appendices. Immediate access after purchase.\u003c\/p\u003e\n\n\u003cp\u003e\u003cem\u003eModels evolve quickly: this book focuses on mechanical and methodological principles that survive across versions, never on the settings of a particular product. No quantified productivity gains are presented — those circulating are unverifiable. Legal points are provided for guidance and are subject to change.\u003c\/em\u003e\u003c\/p\u003e","brand":"SIGNET","offers":[{"title":"PDF","offer_id":56073058419073,"sku":"SIG-EB-IA","price":39.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0956\/3557\/1073\/files\/hf_20260810_012130_e5bc24b4-e689-4fc4-be5f-3cc661eee94e.png?v=1786325798","url":"https:\/\/signet-luxury.store\/en\/products\/lia-au-travail-sans-y-croire-aveuglement","provider":"Signet Luxury","version":"1.0","type":"link"}