What is this article talking about?
If you just start learning AI, it’s easy to focus on “Can AI help me make a beautiful presentation?” What this class really demonstrates is that every lesson preparation, organization, presentation revision, and style revision can be recorded and turned into a system that the Agent can understand and connect to next time. Starting from 2026-07-16, this article also corresponds to the official SOP in the main knowledge base: "Linked SOP: Lecturer briefing Agent workflow". Who is
· People who can write in ChatGPT or Claude, but are not sure what more the desktop Agent can do
· People who often redo presentations, reiterate requirements, and revise formats
· Anyone who wants to organize their teaching, consulting, research, or content production processes into AI repeatable execution methods
· Understand a complete Agent workflow from data collection to presentation output
· Know why you should produce a text outline first, and then make an HTML presentation
· Learn to put preferences, processes, checklists and examples into folders so that they can be continued next time
Presentation is just the entrance, the main axis is the workflow
The key points of this class are clearly explained at the beginning: making presentations, using Agent, and understanding how to put your own knowledge into the knowledge base.
On the surface, this is a class on using AI to make presentations. In effect, it breaks down a commonly done thing into a repeatable process.
First have the course theme or original syllabus, and then collect the pre-course questionnaire, unit needs and student questions.
Put the questionnaire and the course syllabus into the same folder, and first ask the Agent to report which files it has read.
Ask the Agent to organize the text frame within ten pages first and confirm the direction before entering into the presentation production.
There is no problem with the direction. Then ask the desktop Agent to generate an HTML presentation and leave the file in the project folder.
Write preferences such as font level, color matching, tone, layout, folder location, etc. into a file.
Write repetitive processes, examples and self-checklists into operating rules that the Agent can load next time.
Step 1: Put the questionnaire and course syllabus into the same folder
The real lesson preparation method demonstrated by the teacher is to first have the course theme or original syllabus, and then collect student questionnaires or unit needs. When the information comes in, the first step is to put the syllabus, questionnaire, and demonstration materials into the same project folder.
This action is very important because the Agent needs to know which batch of data it is processing. It is best for newbies to open a practice folder first and not let the AI process the really important files at the beginning. After the process is stable, put it into the official work folder.
Let the Agent report the contents of the folder first to confirm that it can read the data and to confirm that it has not missed any key files.
The second step: create a text outline first, and then make a beautiful presentation
After confirming that the Agent has read the course syllabus and questionnaire, the next step is to ask it to organize the briefing outline.
The focus of this step is to first align the content direction. What students really care about and what the original syllabus wants to talk about must be connected first. If AI is required to create a beautiful presentation from the beginning, errors will be included in the layout, making it more difficult to correct later.
Confirm with a text outline first, and you can spread out the issues: which issues should be discussed in advance, which content can be merged, which cases should be replaced with a version that this unit can understand, and which pages have too many and should be deleted first.
Step 3: Understand the difference between web chat AI and desktop work AI
Web version AI is very suitable for reading information, organizing outlines, and helping you think about page content. But if you want to write files directly in the local folder, generate HTML, save versions, and leave files in the project, the desktop Agent is more suitable.
Suitable for discussing content, organizing ideas, and producing a first draft. The main limitation is that after output, it often needs to be manually downloaded, pasted, and moved to other tools.
Suitable for reading local folders, writing files, changing files, and producing finished products that can be saved and reused. Desktop Agents such as
Codex are like the desktop version of GPT installed on your computer. It can get out of the web chat box and help you organize files, generate files, modify web pages, and leave work results in the folder you specify.
Step 4: Write preferences into the folder
After many people use AI to give a presentation, they still have to give it again next time: the font is too small, the color is wrong, the page is too colorful, the tone is too strong, and the title is too like a marketing copy.
This lesson reminds you that just because AI says "I remember" does not mean that you are really in control. If a preference only exists in a certain conversation, a certain AI tool, or a certain computer, it may disappear if the tool or situation is changed.
A more stable approach is to write the preferences in the project folder. For example, font level rules, color preference, commonly used layouts, course tone, target audience differences, and work diary after each execution.
Step 5: Make repetitive processes into skill packages
When you find yourself saying the same thing over and over again, consider turning it into a skill pack. The process demonstrated in this class is very suitable for encapsulation: organize the questionnaire, integrate the syllabus, produce a text outline, make HTML after confirmation, apply a fixed style, and self-check after completion.
The prompt word is just a current instruction. The skill package writes down fixed procedures, preferences, examples, and inspection rules so that the Agent knows which method to follow in similar situations.
When receiving the course syllabus and questionnaire, you must first confirm the content and source of the folder.
You cannot directly develop the final product. You must first make a text draft and then make HTML after confirmation.
There should be a self-check list at the end of the process to prevent the model from skipping critical steps.
Step 6: Accumulate the products after each class into a knowledge base
After a course is over, the briefing is not the only thing worth staying with. There are also pre-class questionnaires, course outlines, presentation outlines, finished HTML products, style preferences, student feedback, post-class QA, and problems discovered after this completion.
If these materials are kept in the same traceable location, the Agent can be asked to look back during the next lesson preparation: how the same topic was taught last time, where students get stuck most often, which metaphors are easy to use, which pages are too difficult, and which styles are suitable for this audience.
When accumulated to a certain extent, this folder will grow into a knowledge base that Agent can read, connect to, and help you do things for you.
Official SOP version: Lecturer giving briefing Agent workflow
This process currently has two landing points: the public page you are looking at is responsible for allowing readers to understand the concept; the SOP in the main knowledge base is responsible for allowing Agents, skill packages and subsequent tasks to reference the same operating rules.
Concentrate the course syllabus, pre-class questionnaire, old presentations, hosting requirements and supplementary materials, and first let the Agent report what it read.
Group students’ questions and compare them with the original syllabus to determine which are core, required, supplementary and extended questions, or QA questions.
First confirm the page skeleton, teaching rhythm and purpose of each paragraph, and do not directly wrap errors into beautiful layouts.
After confirming the direction, use the desktop Agent to generate HTML projection pages, PDF or PowerPoint drafts.
Write the fixed process, layout preferences, font-level rules, checklists and examples back into the lecture-prep skills package.
Retain original materials, finished products, preferences, trouble spots, student feedback and SOPs that can be reused next time.
How to link skill package and knowledge base
This public page is the "entrance for people to see"; the main knowledge base _agent/skills/lecture-prep/references/ is "the official document referenced by the Agent". The contents of the two are aligned, but their uses are different.
Responsible for the execution side: when receiving the syllabus and questionnaire, remind the Agent to first take stock of the information, produce a text outline first, then make a finished presentation, and finally self-examination.
Responsible for the memory aspect: retain the process version, input and output, checkpoints, minefield points and source links, so that the next lesson preparation task does not need to re-explain the background.
In other words, the skill package determines "what the Agent will do this time", and the knowledge base determines "whether it can handle it next time." If you only have the finished brief, you will still start from scratch next time; if the process, preferences, and checklists are all saved back, you can accelerate on the same path next time.
Source and Navigation
- Public source:Turn the pre-class questionnaire into a presentation, and then save the process into a skills package
- Extended reading:How lecturers use knowledge management processes to turn lesson preparation into a reusable system
- Skill pack entrance:Jiang Jiang Coach Skill Pack Download
- Main knowledge base version:
_agent/skills/lecture-prep/references/2026-07-16-2314 Linked SOP: Lecturer giving briefing Agent workflow｜Lecturer, briefing, AIAgent, skill package, knowledge base.md
Last updated: 2026-07-16 23:18 CST. Restrictions not yet completed: This page has been synchronized to the official website source code; if the social platform still displays the old summary or old cover, it is usually the platform cache, and you need to repost the link or wait for the cache to refresh.
How you can practice
Don’t experiment with the most important information first. Open an exercise folder, put a task description or course syllabus, and then put a questionnaire, interview record or demand summary.
- First ask the Agent to report what is in the folder.
- Compile a text outline based on the data.
- When you’re done, write down your process, preferences, and checklist.
If you will do similar tasks next time, organize this process into a skill package. Once you've done it three to five times, you'll start to see your knowledge base take shape.