The best app for non programmers to learn Agentic AI
In my opinion Notion is the best app for non programmers who want to learn Agentic AI.
Here are some reasons
You will finally be able to define what an AI agent is
I know this might seem funny, but Simon Willison, who is a prolific blogger on the topic of LLMs wrote this recently.
Notice the date this was posted. It was only about a month back (I am writing this in October 2025).
Under the hood, Notion is a fairly complex system of tools.
In the past you were able to run all these tools to achieve your business goals, for example create a custom CRM. Now you can achieve similar results by writing a prompt, instead of using a (somewhat) tedious process of building out the database step by step by clicking on buttons.
Since you are achieving similar results by writing prompts instead of clicking on buttons, in my opinion this is a sufficiently good definition of “agentic AI”
Learn on a fixed budget
Notion is not free, but it is fixed budget. This means you can experiment to your heart’s content without accidentally over-running your budget.
To be clear, the reason you cannot overrun the budget is not because you have unlimited resources at your disposal, but rather Notion will take care of rationing your requests behind the scenes if you approach usage limits.
But you can do a LOT of stuff without hitting these limits, as I will explain in the rest of this article.
Supports hierarchical information
Since Notion supports hierarchical information – a page can have a set of sub-pages, which can themselves have their own sub-pages and so on – it is very easy to use Notion as a knowledge base.
An excellent contrast would be with NotebookLM, which is by any measure an excellent AI tool, but the lack of a multi-level hierarchy means you are restricted to the paradigm of a single hierarchy of Notebooks which contain sources.
Since NotebookLM has a generous free tier and excellent AI search capabilities, this simple hierarchy is still OK for beginners. But there is also another major challenge with NotebookLM.
Notion is primarily a note taking tool
In fact, it began its life as a note taking tool.
AI Summary Search is an example use case of AI where it is just unquestionably better than what it replaced (ten blue links), as long as you also have citations to source documents.
Speaking of source documents, cross checking any AI search summary requires that you must be able to quickly read the source documents in the same way you read web pages or Microsoft Word documents.
In most AI search tools, you can get your answers but it is very hard to use them in “browse” mode where you are just reading your notes. Since Notion is primarily a note taking tool, its documents are actually easy to read and skim.
For example, NotebookLM is great for getting AI answers, but you might have noticed that it is not very easy to just read the individual documents inside the NotebookLM interface.
Let us try and import an example article into both NotebookLM and Notion.
When you import it into NotebookLM, this is what the preview looks like.
As you can see, NotebookLM automatically strips out the images, and there isn’t any easy way to navigate within the document.
With Notion you need to do a two step process – save the source article as HTML first and then import the HTML.
But the results are much better, because the “preview” is very close to the source document.
While AI Summary Search itself is not considered agentic, it is often a core part of agentic workflows. And we need to have easy-to-read source documents to verify if the agent output is as expected, and this is very easy to do in Notion.
It has native databases
You can go much farther with learning Agentic AI if your app supports databases natively.
The reason for this is pretty simple – a lot of knowledge work happens in spreadsheet interfaces and a native database gives you almost all the capabilities of a spreadsheet tool like Microsoft Excel.
And you can even create and update these databases using Agentic AI, which I explain in the course.
However the Notion database has a very unique aspect which regular spreadsheet tools do not have, which is the next point.
Individual Notion database rows are also documents
This means each database row is also a “page” which has all the features of a regular Notion page.
This means
- You can add different content widgets to it, such as callouts
- You can embed audio and videos inside a page
- You can add MORE inline databases into the page
- You can have subpages with their own content
This design makes Notion extremely flexible when you start exploring Agentic AI.
Even if this is a counter intuitive feature (and it will take some time to really understand how it works) it could well turn out to be the biggest differentiator for Notion when it comes to Agentic Search.
From what I can see, Notion AI indexes only the document content for each database row and does not index text content inside columns.
In practice this means that AI search will work well only for the document content and not for the text inside your database (in fact I have tested this and it seems to be an important limitation in Notion AI, which I will discuss in a future point)
Provides a structured approach to learning Agentic AI
You can start with small agentic tasks and work your way up to more complex ones on a fixed budget.
In fact, given that you are paying for Notion AI anyway, it would even be a good idea to do small daily exercises and create your own library of agent prompts (which you can search using Notion AI in the future, of course!)
Most people would agree that learning how to create good prompts can help you design much better AI agents. In my opinion, a little bit of daily practice will help you really improve your prompting skills over time.
Learn the limitations of agentic AI
This might sound like a strange reason to use an app, but agentic AI has a LOT of limitations that most AI companies will never tell you about, since they benefit a lot from the AI hype.
For example I mentioned one such limitation – Notion AI is not able to index text content inside databases, so doing AI search over the text content inside a large database is probably infeasible.
I personally think this is just a result of imposing a fixed budget and Notion needs to carefully ration its LLM API requests behind the scenes. Whatever the reason, the end result is that you cannot perform long running agentic tasks over the text data in a large database.
But noticing the limitations is an important precursor to the next step.
Notion can avoid the all or nothing outcome of other agentic AI tools
If some task is too complex for an AI agent, you don’t have good workarounds in no code tools.
Notion avoids this problem by also allowing automation via its API.
Tip: where possible, use Python scripts (i.e. API automation) and avoid consuming the Notion AI agent resources so that you can use your daily quota for other tasks.
The end result of using more automation will be
a) a better understanding of how Notion works
b) more deterministic outcomes (AI Agents still produce strange nondeterministic errors on moderately complex tasks)
API support out of the box
Quite often you will find that writing some automation code makes Notion AI work better, as I will explain in the course.
This means even if the out of the box agentic AI in Notion is unable to perform some task, you might be able to fill in the gaps by writing some Python code.
Check out my Agentic AI for Non Programmers course
Want to learn about agentic AI using Notion?
I am creating a video course which will be completed by end of October 2025, and you can get a big early bird discount if you pre-order.