Handbook of AI Prompting by Dr. Anubhav Gupta
A practical guide to prompt engineering, large language models, tokenisation, reasoning workflows, retrieval-augmented generation, AI agents, evaluation, safety and scalable AI systems.
What is Handbook of AI Prompting?
Handbook of AI Prompting is a structured book on designing better prompts and AI workflows. It explains how modern language models interpret instructions, process context, handle constraints, generate responses, fail, hallucinate and improve through better prompt design, retrieval, evaluation and governance.
AI prompting is no longer about clever one-line commands
As AI tools enter business workflows, prompting must move from trial-and-error to a disciplined system of instructions, context, constraints, examples, evaluation and human review.
Clarity
Good prompts define the task, audience, output format, constraints and success criteria before expecting useful results.
Control
Reliable AI outputs need guardrails, examples, role instructions, context discipline and structured response formats.
Evaluation
AI output should be reviewed for accuracy, usefulness, risk, bias, hallucination, tone and business fitness.
Scale
Teams need prompt libraries, SOPs, workflow rules and review processes — not random prompts scattered across chats.
A practical map from AI basics to production-ready prompting systems
The book connects AI concepts with actual prompting practice, so readers can understand both how models work and how to work with them.
How language models interpret prompts
Understand tokens, embeddings, attention, context windows, inference and why wording affects output quality.
Prompt engineering foundations
Learn task framing, role prompts, examples, constraints, output formats, zero-shot prompting and few-shot prompting.
Retrieval-augmented generation
See how retrieval, grounding, source context and document-aware prompting reduce unsupported output.
Agentic workflows
Explore planning, tool use, multi-step execution, task decomposition and human-supervised agentic systems.
Evaluation and debugging
Improve prompts by testing response consistency, hallucination risk, failure modes and output quality.
Safety and governance
Build safer AI workflows with review layers, privacy discipline, policy boundaries and responsible usage rules.
The best prompts behave like small systems
A useful prompt is not just a sentence. It is a compact workflow containing context, task, constraints, examples, format, quality expectations and review logic.
Define the objective
State what the AI should achieve, who the output is for and how the output will be used.
Provide the right context
Give relevant background, examples, source material, audience details and business constraints.
Control the output
Specify format, structure, length, tone, exclusions, terminology and success criteria.
Test and refine
Compare outputs, identify failure points, adjust instructions and build reusable prompt patterns.
Add human review
Use human judgement for accuracy, ethics, legal sensitivity, brand tone, technical correctness and final approval.
For people who want predictable AI behaviour, not prompt lottery
Marketers
For marketers using AI for briefs, content, research, SEO, ad copy, repurposing and campaign planning.
Founders
For founders who want to understand where AI can support operations, strategy, communication and growth.
Technical teams
For AI engineers, product managers, solution architects and consultants designing structured AI workflows.
Educators and learners
For students, teachers and professionals who want to understand modern AI systems in a practical way.
Where better prompting creates real business value
The book is useful because it links prompting to actual workflows instead of limiting AI to casual question-answer use.
SEO and content workflows
Use AI for topic research, outlines, briefs, FAQs, schema suggestions, content improvement and repurposing.
Business operations
Create reusable prompts for documentation, process notes, summaries, checklists and decision support.
Research and analysis
Structure research prompts for comparison, synthesis, evidence mapping, risk identification and strategic insight.
Customer communication
Improve drafts, responses, FAQs, help documents and customer education without losing brand control.
Education and training
Use AI to create lesson plans, explanations, quizzes, examples, learning paths and revision material.
AI governance
Build policies for responsible AI usage, review, privacy, hallucination control and workflow approval.
Dr. Anubhav Gupta
Dr. Anubhav Gupta works across SEO, digital growth strategy, AI workflows, technical systems and practical business implementation. His AI writing focuses on using prompting as a disciplined method for thinking, structuring, testing and scaling work.
Through Elgorythm, his work connects AI prompting with SEO, AEO, GEO, content operations, marketing systems, digital authority and practical implementation.
- Author of books on SEO, AEO, GEO, AI prompting and digital marketing
- AI generalist with a systems-first approach to workflows and execution
- SEO and digital growth strategist behind Elgorythm’s AI-search ecosystem
- Focused on practical, governed and scalable AI usage
Use the book as a foundation for real AI workflow design
Readers who want to apply prompting in business, content, SEO, AEO, GEO or internal operations can continue into Elgorythm’s AI workflow ecosystem.
Related Elgorythm books for AI, search and digital growth
This book should connect strongly with the wider Elgorythm knowledge ecosystem.
Handbook of SEO
Technical SEO, content structure, schema, search systems and modern optimisation.
Mastering Answer Engine Optimisation
Answer-first content, AI answers, zero-click search and structured visibility.
Mastering Generative Engine Optimisation
Generative AI discovery, entity clarity, citations and AI-search readiness.
Handbook of Content Marketing
Content planning, creation, optimisation, distribution and measurement.
Handbook of AI Prompting FAQs
What is Handbook of AI Prompting?
Handbook of AI Prompting is a practical book by Dr. Anubhav Gupta that explains how modern AI systems interpret prompts and how users can design clearer, safer and more reliable AI instructions.
Who should read this AI prompting book?
The book is useful for marketers, founders, AI learners, consultants, educators, content teams, SEO professionals, product managers, prompt engineers and professionals who want predictable, testable and scalable AI behaviour.
What topics are covered in the book?
The book covers tokenisation, embeddings, attention, inference, zero-shot prompting, few-shot prompting, reasoning workflows, hallucination reduction, retrieval-augmented generation, agent workflows, safety, governance and prompt security.
Does this book help with ChatGPT and other LLM tools?
Yes. The book explains principles that apply across ChatGPT and other large language model tools, especially where users need clearer instructions, better context, structured outputs, reusable prompts and review processes.
Is this book only for technical readers?
No. Technical readers will find value in LLM concepts, RAG, agents and evaluation, but the book is also written for business users, marketers, educators and founders who want practical AI workflow understanding.
Does the book explain AI safety and governance?
Yes. It discusses the need for safer AI usage, human review, hallucination control, privacy discipline, responsible prompting, prompt security and workflow-level governance.
Can I download a sample chapter?
Yes. The page includes a sample chapter link so readers can preview the book before ordering the full version.
Where can I buy Handbook of AI Prompting?
The book can be ordered through the Amazon link provided on this page.
Move from casual prompting to controlled AI workflows
Download the sample chapter, order the book, and then explore Elgorythm’s AI services and workflow pages to turn prompting knowledge into practical systems.
