Votre prompt IA fait tout… mais vous ne comprenez plus rien ? (#087)
With AI, we often want to ask for everything at once: clean data, generate a report, create graphs, produce a web page, add filters… and hope that everything works perfectly. The problem is that the more complex the task, the harder the result becomes to understand, test, and debug. In this video, we see a more reliable method: break down the complexity into clear steps, verify each output, automate only what is stable, and keep human validation where it is necessary. This video is part of the playlist: • Terminal et ligne de commande (CLI) à l’èr... You will learn: why a large prompt gives an illusion of speed why AI automation can become a black box the 4 questions to make a step reliable: input, processing, output, verification why a reliable step must be able to be tested independently how to ask AI to break down a problem before generating code what to automate, what to keep manual, and when to choose semi-automation why it is sometimes better to automate the checking than the fixing how to proceed step by step with a green light for validation how to spot overspeeding: scope too wide, loss of control, lack of testability how to use a summary prompt to validate the breakdown before the code Subscribe to Catalyseur Dev to learn how to use AI, code, and automation methodically, without delegating. Your thinking is a black box. In the comments, tell me: when you use AI for automation, what's your biggest pitfall: asking for too many things at once, not testing each step, or losing track of where the error is coming from? 00:00 The trap of the big prompt with AI 01:13 The plan: break down complexity 01:29 Why asking for everything at once leads to a loss of control 01:52 The 4 questions of a reliable step 02:31 A reliable step must be able to be tested on its own 03:30 Break it down before coding with AI 04:16 Choosing what to automate 04:57 Automating the check rather than fixing everything 05:18 Moving forward step by step with a green light 06:19 Spotting speeding and regaining control
![[Leçon inaugurale] Yann Le Cun - Apprentissage profond et au-delà : les nouveaux défis de l'IA](https://i.ytimg.com/vi/Z208NMP7_-0/hqdefault.jpg?sqp=-oaymwE9CNACELwBSFryq4qpAy8IARUAAAAAGAElAADIQj0AgKJDeAHwAQH4Af4JgALQBYoCDAgAEAEYPCBlKEowDw==&rs=AOn4CLCEu0oAHE4bEe4NUpSBvJ-i2cfb_w)
[Leçon inaugurale] Yann Le Cun - Apprentissage profond et au-delà : les nouveaux défis de l'IA

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