Artificial Intelligence Bible
Agentic AI, Generative AI & Prompt Engineering (4 in 1). Everything You Need to Skyrocket Productivity, Cut Costs and Get Your Life Back
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Czyta:
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Rick Gines
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Autor:
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Alexander Sterling
The Tools Are Here. Everyone Is Talking About Them. Almost Nobody Knows How To Actually Use Them.
Four Books In One — The Complete, Practical Path From "I Keep Meaning To Learn This" To Delegating Real Work Before Lunch
You've watched AI go from novelty to necessity. You've opened you LLM, typed something, and gotten a mediocre answer back. You've heard the words agent, generative, and prompt engineering thrown around — and quietly wondered if you're already behind.
You're not behind. You just haven't been taught properly.
Most guides teach these skills in isolation — a book on prompts here, a course on agents there. That separation is exactly why beginners stay stuck. Each skill gives a small lift on its own. Stacked together, they compound into a permanent edge.
This is that stack. Four books, one clear path, no hundred-page history lesson before the useful part starts.
What You'll Actually Be Able To Do:
- Direct AI Agents With Confidence — Know what to hand off, how to phrase the goal, and when to watch versus walk away.
- Clear an email backlog or draft a brief the way a chef writes a prep sheet: short, specific, no room for confusion.
- Pick The Right Tool In Thirty Seconds — Understand the four modalities of text, image, audio, and video, and which named tools sit where — so you never waste an afternoon in the wrong app again.
- Write Prompts That Work On The First Try, Not The Fifth — Learn the four pieces every effective prompt contains, the patterns that handle most of your weekly work, and a reusable library you'll lean on for years.
- Build Smarter Agents From The Ground Up — Go deeper with a practical 7-step engineering guide to designing goal-oriented, LLM-powered systems that plan, act, and adapt in the real world.
This isn't theory for its own sake. Every concept is paired with a worked example, a real framework, or a common mistake to avoid.
©2026 Alexander Sterling (P)2026 Alexander Sterling