<ul data-eligibleForWebStory="true"><li>The article provides a practical guide for software engineers to navigate and thrive in the AI landscape, covering topics on using AI effectively, building tools, vibe coding, model selection, application development, and more.</li><li>Tools like ChatGPT, Claude, Gemini, Grok, Gamma.app, Perplexity, and Rovo Chat are discussed for integrating AI into everyday tasks and specific projects.</li><li>The importance of vibe coding, prompt engineering, and utilizing specific tools like Task master and Memory bank is emphasized for enhancing productivity with AI.</li><li>The article delves into model selection with platforms like OpenRouter, Ollama, and gemini-balance, highlighting the importance of understanding trade-offs in performance, constraints, access, and costs.</li><li>Strategies for AI application development, including the concept of RAG (Retrieval-Augmented Generation), fine-tuning, and evaluation and observability tools like LangSmith and LangFuse, are discussed.</li><li>The conclusion encourages starting with real-life problems in AI development, emphasizing curiosity and momentum over credentials in the learning process.</li></ul>

How to Learn AI from Scratch

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