{"product_id":"building-agentic-ai","title":"Building Agentic AI: Workflows, Fine-Tuning, Optimization, and Deployment by Sinan Ozdemir","description":"\u003ch2\u003eBuilding Agentic AI: Workflows, Fine-Tuning, Optimization, and Deployment by Sinan Ozdemir\u003c\/h2\u003e\n\u003cp\u003e\u003cspan class=\"citation-271 citation-end-271\"\u003eThe book is intentionally written for \"builders\"—developers, data scientists, and technical product managers who need to design systems that handle real-world tasks without human hand-holding.\u003csup class=\"superscript\" data-turn-source-index=\"3\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003e \u003cspan class=\"citation-270 citation-end-270\"\u003eThe text is systematically divided into three tactical acts:\u003csup class=\"superscript\" data-turn-source-index=\"4\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003eDefining what separates a basic text-completion prompt or chatbot from a true \"agent\" (the capability to respond, reason, plan, and execute actions independently)Building foundational, deterministic LLM-driven sequences—such as complex text-to-SQL data pipelines—before layering on autonomous decision-making.Moving beyond vibes-based prompt engineering. \u003cspan class=\"citation-268 citation-end-268\"\u003eOzdemir introduces hard frameworks to measure precision, recall, and latency, demonstrating how to systematically benchmark models.\u003csup class=\"superscript\" data-turn-source-index=\"6\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"13\"\u003eOzdemir’s text arrives precisely as the software industry transitions out of the generative AI hype phase and into the hard reality of deploying functional production pipelines.The book refuses to pretend that building enterprise AI is easy. \u003cspan class=\"citation-261\"\u003eOzdemir pulls back the curtain on hidden architectural flaws that plague complex setups, such as \u003c\/span\u003e\u003cb data-path-to-node=\"15\" data-index-in-node=\"162\"\u003e\u003cspan class=\"citation-261\"\u003epositional bias in tool selection\u003c\/span\u003e\u003c\/b\u003e\u003cspan class=\"citation-261 citation-end-261\"\u003e (where an LLM ignores an option simply based on where it sits in a prompt list, sometimes shifting accuracy by 40%).\u003csup class=\"superscript\" data-turn-source-index=\"13\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003e Rather than ignoring these engineering edge-cases, he provides clear algorithmic mitigation techniques.\u003c\/p\u003e\n\u003cp data-path-to-node=\"17\"\u003eOne of the costliest mistakes engineering teams make is over-engineering simple problems into unpredictable agentic loops. Ozdemir provides clear architectural rubrics determining \u003ci data-path-to-node=\"17\" data-index-in-node=\"180\"\u003ewhen\u003c\/i\u003e a task requires a flexible, self-directing autonomous agent and \u003ci data-path-to-node=\"17\" data-index-in-node=\"249\"\u003ewhen\u003c\/i\u003e it should be constrained into a predictable, structured workflow.\u003c\/p\u003e\n\u003cp data-path-to-node=\"19\"\u003eRunning unoptimized, massive foundation models across thousands of enterprise workflows will bankrupt a standard infrastructure budget. \u003ci data-path-to-node=\"19\" data-index-in-node=\"136\"\u003eBuilding Agentic AI\u003c\/i\u003e is highly celebrated for its focus on \u003cb data-path-to-node=\"19\" data-index-in-node=\"194\"\u003emodel distillation and optimization\u003c\/b\u003e. By teaching developers how to combine smaller, fine-tuned models, speculative decoding, and highly adaptive vector spaces, Ozdemir shows how to match frontier-model performance at a fraction of the token cost.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eLanguage: English.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eGenre: Applied Artificial Intelligence.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eBinding: সেলাই করা বাইন্ডিং\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eQuality: Premium Quality Books.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePrinting: High Quality Printing.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePaper: Eye Friendly paper (Cream White)\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eCover: Matt cover (Paperback).\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e","brand":"Royal Books BD","offers":[{"title":"Default Title","offer_id":47234622881977,"sku":null,"price":320.0,"currency_code":"BDT","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0780\/0874\/6169\/files\/Building_Agentic_AI.jpg?v=1779387563","url":"https:\/\/royalbooksbd.com\/products\/building-agentic-ai","provider":"Royal Books BD","version":"1.0","type":"link"}