Skip to main content
AIDevOps
  • Learn
  • Learning Paths
  • Practice
  • Open Source
  • Books
  • Engineering

    AI DevOpsThe full map of building and operating AI servicesLLMOpsLLM deployment · evaluation · observabilityHands-on ProjectsBuild AI Agent projects

    Knowledge

    DocsTechnical documentationBlogEngineering articlesPloggerDevelopment log feed

    Validate

    Certification3-level skills certification · coming soon
AI Models
LlamaTutorial|MistralTutorial|GemmaTutorial|DeepSeekTutorial|QwenTutorial
🧠 AI Core
AI Intro & RoadmapML FundamentalsLLM Fundamentals|Python AIC++|PyTorchTensorFlowJAX
🤖 AI Applied Development
Applied AI Intro & RoadmapHugging FaceLangChainLlamaIndexLLMOps|LangGraphMCPMulti-AgentAgent Evaluation
🧠 AI Agent Development
Finance AI AgentLLM API ServerStock Investing AgentAIOps AI AgentEducation AI AgentCoding AI Agent
🌱 Spring Cloud
Spring Intro & RoadmapSpring Cloud GatewaySpring BootJava|Spring AISpring SecuritySpring BatchSpring JPA
🐳 DevOps
DevOps Intro & RoadmapLinuxDockerCI/CD|Kubernetes BasicsK8s AdvancedPrometheusGrafana
🧱 Infrastructure
Infrastructure Intro & RoadmapNginxRedis
☁️ Cloud
Cloud Intro & RoadmapAWSGCPAzureNCPCloudflare
🎨 Frontend
Frontend Intro & RoadmapJavaScriptTypeScript|ReactNext.js|VueNuxt|Electron
📱 Mobile
Mobile Intro & RoadmapKotlinAndroidFlutter
⚙️ Backend
Backend Intro & RoadmapPython BasicsFastAPIDjangoFlask|CGoGinNode.js
💾 Database
DB Intro & RoadmapCore SQLOracleMySQLPostgreSQL|MongoDBVector DB
🧪 Testing
k6JMeternGrinder
AIDevOps

Engineering AI. From Code to Production.
An engineering learning platform for building and operating AI and AI Agents

Learn

  • All Guides
  • Learning Paths
  • AI Tutorial
  • Practice
  • Books

Resources

  • AI DevOps
  • LLMOps
  • Hands-on Projects
  • Docs
  • Blog
  • Plogger
  • Open Source
  • Certification (coming soon)

Start Here

  • AI Core Roadmap
  • AI Applied Development Roadmap
  • Spring Cloud Roadmap
  • DevOps Roadmap
  • Infrastructure Roadmap

 

  • Cloud Roadmap
  • Frontend Roadmap
  • Mobile Roadmap
  • Backend Roadmap
  • Database Roadmap
© 2026 AIDevOps. All rights reserved.
Terms of ServicePrivacy PolicySitemaptestforge.kr
  1. Home
  2. AI Tutorial
  3. The Long Scroll

Quest 03 · Everyone

The Long Scroll

Visitors

Hand over the material, hide what should be hidden, and refine in conversation

Time
6 min
Max XP
130
Skill earned
Handling material
1 / 6
0 XP

The village head's request

Client

Yesterday's village meeting ran for three hours, and the scroll of notes is this long. I just want to tell the villagers what was decided.

Hanna

Summarizing is something Ari does well. The order matters, though. Give it a try.

Summary

What this request teaches

An AI cannot see the documents you have seen. Through a request to tidy up a long meeting record, learn how to hand over material, what must not go in, and how to refine a result in conversation.

Show the key points (best read after finishing the request)
  • An AI does not know the documents you have seen or what you have been through. To have it summarize or analyze, hand over the material too.
  • Asked without material, an AI may make up common content instead of saying "I do not know".
  • When you give material, also say who it is for and what to keep and what to leave out.
  • Remove or replace personal information, passwords and authentication keys, and private material before they go in. Once sent, it cannot be taken back.
  • Within the same conversation, earlier content is remembered. Do not rewrite from the start; continue with what to change and what to keep.
  • Check what the AI adds (days of the week, calculations, and so on) against the source.

Try it yourself

Pick a long notice or email you received recently, remove the names and contact details, and paste it in with the request below.

Tidy up the text below.
- Reader: [who]
- List only what I have to do and the deadlines.
- Do not add anything that is not in the text.

[paste the text here]

Learn more

  • AI App Intro — the idea of RAG, answering from documents →
  • Vector DB — how an AI finds documents →
  • Back to the request board →