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AI prompts guide
64 topics across 6 chapters
Chapter 1
Prompting fundamentals
1
How LLMs respond (probabilistic behavior)
2
Prompt anatomy checklist (goal, inputs, constraints, output)
3
Context and memory management
2 subtopics
4
Summarize/condense context to fit token budgets
5
Delimit and label sources/quotes vs instructions
6
Constraints, audience, and tone
7
Tokens, cost, and latency basics
Chapter 2
Core prompt patterns
8
Zero-shot vs few-shot examples
9
Role/system instructions and boundaries
10
Stepwise workflows (plan → execute → verify)
11
Structured outputs (JSON, tables, schemas)
2 subtopics
12
JSON schema prompting + validation/self-repair loop
13
Table/CSV formatting with consistent headers and types
14
RAG prompting basics (grounding + citations)
15
Style transfer and rewriting prompts
16
Multimodal prompting (images, PDFs, mixed inputs)
Chapter 3
Iteration, evaluation, and debugging
17
Define success criteria (rubrics + acceptance tests)
18
Build a prompt test set (golden examples + edge cases)
19
Error analysis (failure modes + minimal edits)
20
A/B testing and versioning prompts
21
LLM-as-judge evaluation (risks + calibration)
22
Logging and monitoring (quality, drift, cost)
Chapter 4
Domain playbooks
23
Writing and editing prompts
3 subtopics
24
Outline → draft → revise prompt chain (editor loop)
25
Fact-checking and citation requests (when/what to cite)
↗ Define success criteria (rubrics + acceptance tests) (see Chapter 3)
26
Coding and debugging prompts
3 subtopics
27
Spec-first prompting (requirements, constraints, interfaces)
28
Ask for tests and refactors (readability, performance)
↗ Build a prompt test set (golden examples + edge cases) (see Chapter 3)
29
Data analysis prompts
2 subtopics
30
Ask for assumptions, definitions, and data needs upfront
31
Reproducible analysis (SQL/Python) + sanity checks
32
Support and agent workflows
3 subtopics
33
Policy/intent constraints and escalation rules
34
Conversation state + tool-use handoffs (agent state)
↗ Context and memory management (see Chapter 1)
35
Creative and image prompting
3 subtopics
36
Prompt for variations (constraints, seeds, remixing)
37
Style references + negative constraints (what to avoid)
↗ Multimodal prompting (images, PDFs, mixed inputs) (see Chapter 2)
Chapter 5
Tools, automation, and integration
38
Prompt templates and variables
2 subtopics
39
Template slots + defaults (inputs, constraints, output format)
40
Reusable prompt components (snippets, policies, formatters)
41
Function/tool calling concepts
2 subtopics
42
Write tool specs/schemas (inputs, outputs, constraints)
43
Tool error handling (retries, fallbacks, partial failures)
44
RAG implementation (retrieval + synthesis)
2 subtopics
45
Chunking/embeddings basics for retrieval
46
Retrieval query prompts + answer synthesis with citations
↗ RAG prompting basics (grounding + citations) (see Chapter 2)
47
Deployment and governance
2 subtopics
48
Prompt review, approvals, and rollback strategy
49
Documentation and runbooks (usage, limits, examples)
Chapter 6
Safety, privacy, and reliability
50
Prompt injection and jailbreak defense
2 subtopics
51
Use allowlists/tool permissions and “never trust user text” rules
↗ Delimit and label sources/quotes vs instructions (see Chapter 1)
52
Privacy and data handling
2 subtopics
53
PII minimization and redaction prompts
54
Data retention, consent, and sensitive-data basics
55
Bias and fairness checks
56
Refusals and safe completion
2 subtopics
57
Write refusal-friendly prompts + safe alternatives
↗ Policy/intent constraints and escalation rules (see Chapter 4)

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