Prompting 106: ตรวจ บันทึก และใช้ซ้ำPrompting 106: verify, save, and reuse

Prompting becomes valuable when it is repeatable.

If a prompt helps you do real work, do not leave it buried in chat history. Save it, test it, improve it, and reuse it.

But before reuse, learn to verify.

Verify before trusting

AI can sound confident when it is wrong.

Use verification prompts for work that includes facts, numbers, policies, names, dates, prices, or recommendations.

Check the answer for:
- unsupported claims
- invented numbers
- missing assumptions
- dates that may be outdated
- claims that need sources

Return a table with: claim, confidence, how to verify.

The goal is not to make AI afraid. The goal is to make uncertainty visible.

Ask for source-grounded answers

For source-based work, ask the model to separate answer from evidence.

Use only the pasted source.

Answer the question, then include:
- supporting quote or section name
- what is not stated in the source
- what needs human confirmation

If you need current information:

Use current official sources. Include links and access dates. If you cannot verify a claim, say "not verified".

Save prompt templates

A prompt template has blanks you can fill in later.

Task:
Rewrite this [type of message] for [audience].

Context:
- Goal: [goal]
- Relationship: [relationship]
- Situation: [situation]

Output:
- Language: [language]
- Length: [length]
- Tone: [tone]

Constraints:
- Keep: [must keep]
- Avoid: [must avoid]
- Ask first if: [missing info]

Text:
[paste text]

Save templates in a note, README, or shared team doc.

Version your prompts

If a prompt matters, keep versions.

Prompt name: customer-reply-review
Version: 1.2
Works for: customer support replies under 300 words
Last updated: 2026-05-07
Known weakness: sometimes too formal for LINE messages

This sounds formal, but it prevents confusion when prompts become team tools.

Build a tiny prompt library

Start with five reusable prompts:

1. Rewrite for clarity
2. Summarize into action items
3. Review for unsupported claims
4. Turn notes into meeting agenda
5. Compare two options with tradeoffs

Each prompt should include:

• task
• context fields
• output format
• constraints
• verification step

Final practice: make one reusable prompt

Choose a task you do every week.

Build one prompt template for it:

Name:

When to use:

Prompt:

Example input:

Expected output:

Verification checklist:

Then test it twice with different inputs. If it only works once, it is not reusable yet.

Full course references

These references shaped the Prompting 10x series. They are included here so learners can see how the course evolved from current provider guidance and prompting research.

Current provider guidance

• OpenAI Prompting
• OpenAI Prompt Engineering
• OpenAI Prompt Guidance
• OpenAI GPT-5.2 Prompting Guide
• OpenAI Reasoning Best Practices
• OpenAI Prompt Optimizer
• OpenAI Evaluation Best Practices
• Anthropic Prompt Engineering Overview
• Anthropic: Effective Context Engineering for AI Agents
• Google Gemini Prompt Design Strategies
• Microsoft Foundry Prompt Engineering Techniques

Research foundations

• Wei et al., 2022: Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
• Wang et al., 2022: Self-Consistency Improves Chain of Thought Reasoning in Language Models
• Yao et al., 2022/2023: ReAct: Synergizing Reasoning and Acting in Language Models
• Yang et al., 2023: Large Language Models as Optimizers
• Sahoo et al., 2024: A Systematic Survey of Prompt Engineering in Large Language Models
• Dong et al., 2025: A Survey of Context Engineering for Large Language Models