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Have you ever felt that mental fatigue? The one that happens when you open an 80-page supplier technical PDF to find a product dimension? Or when you need to migrate a PrestaShop 1.6 module to 8.1 and spend your afternoon juggling between Symfony docs, old legacy documentation and StackOverflow?

We’re living in a fantastic era with AI, that’s undeniable. But if you use ChatGPT or Claude for these specific tasks, you’ve surely already hit a wall: hallucination.

Ask ChatGPT to generate a complex override for PrestaShop 8, and there’s a fifty-fifty chance it’ll give you obsolete code from version 1.7. Why? Because it’s trained on “all of the internet”, not on your specific context.

Today, I want to talk to you about a tool that has changed the way I work in recent months. It’s not a creative text generator, it’s a contextual data analyst.

Its name? NotebookLM.

If you’re a module developer or e-merchant, this tool isn’t an option. It’s your future competitive advantage. Let’s dive in.

Part 1: The Problem with Generic AI (and the RAG Solution)

To understand why NotebookLM is a game changer for us, we need to understand a major limitation of classic LLMs (Large Language Models).

When you talk to ChatGPT, you’re talking to an encyclopedist who has read everything up to a certain date. It knows Shakespeare, the penal code, and the recipe for quiche lorraine. But it doesn’t know:

  • Your confidential supplier catalogs.
  • The technical documentation of the specific module you’re debugging.
  • The latest PrestaShop updates released last week.

The “Grounding” Revolution

NotebookLM is based on a technology called RAG (Retrieval-Augmented Generation). To put it simply: instead of asking the AI to make up an answer based on its (sometimes fuzzy) memory, we ask it to read your documents and respond only based on them.

For an ecosystem as technical and precise as PrestaShop, this is the difference between an intern who guesses and an expert who checks their sources.

The issue is twofold:

Reliability: If the info isn’t in your documents, NotebookLM will tell you “I don’t know”, rather than inventing a PHP function that doesn’t exist.

Confidentiality: This is the critical point for merchants. Your source data remains in your private instance (Google assures they’re not used to train the global model).

Part 2: NotebookLM, Your New Digital Brain

Concretely, NotebookLM presents itself as a workspace where you create “Notebooks”. In each notebook, you import sources.

This is where the magic happens. You can “feed” the AI with:

  • PDFs (catalogs, terms and conditions, invoices).
  • Text files (error logs, source code).
  • Google Drive files.
  • Website URLs (official documentation).

Once the sources are ingested (and it’s almost instantaneous), the AI instantly becomes an expert on this corpus of data.

Why is this vital for the future of PrestaShop dev?

We’re reaching a point of technical complexity where it’s impossible to remember everything by heart. Between Symfony architecture, legacy controllers, modern APIs and front-end constraints, our developer profession is evolving.

We are no longer simple “code monkeys”. We’re becoming knowledge orchestrators.

NotebookLM allows you to reduce cognitive load. You no longer need to remember the exact syntax of a specific Symfony service in PrestaShop 8. You just need to know where the documentation is and give it to the AI.

Part 3: Concrete Use Cases (Hands-on)

Enough theory. How can you use this tomorrow morning to make money or save time on a PrestaShop store? Here are two scenarios I’ve tested and validated.

Scenario A: The PrestaShop Developer (“Super-Debug” Mode)

Imagine: you need to take over maintenance of an old module coded poorly 5 years ago. There are no comments, and it crashes on the latest PHP version.

The NotebookLM Workflow:

  1. Create a notebook “Migration Module X”.
  2. Source 1: Import the main .php file of the module.
  3. Source 2: Copy-paste your PHP/Apache error logs into a text file and import it.
  4. Source 3: Add the URL of the official PrestaShop documentation on version 8 “Breaking Changes”.

The Prompt:

Analyze the stack trace provided in the error_log.txt file.
Identify the obsolete function in my code (source module.php) and
propose a PrestaShop 8 compatible rewrite based on the provided
documentation. Explain why the old method no longer works.

The Result:

Instead of a generic answer, you get a surgical correction. The AI will tell you:

“The error comes from line 142. You’re using Tools::getValue in an insecure or deprecated way in this specific context, here’s how to call the equivalent Symfony service according to the imported documentation.”

Scenario B: The E-merchant (“Catalog Productivity” Mode)

You receive the new “Winter Collection” catalog from your supplier. It’s a 200-page PDF, poorly formatted, with complex tables. You need to create 50 product sheets for your PrestaShop store.

The NotebookLM Workflow:

  1. Create a notebook “Winter Collection”.
  2. Source: Upload the supplier’s PDF.
  3. (Optional) Source: Add a text file with your editorial charter (“Fun tone, informal, HTML structure with H2 and H3”).

The Prompt:

Act as an e-commerce SEO expert. For products on pages 12 to 15
(Coat Category), generate a CSV file with columns: Name, Short
Description, Long Description (HTML), Price excl. tax, Weight.
Extract technical dimensions from the PDF but write descriptions
according to my editorial charter.

The Result:

In 30 seconds, you’ve structured unstructured data. What used to take a day of manual entry now takes 15 minutes of verification. That’s E-commerce Velocity.

The “Futuristic” Bonus: Audio Overview

This is my favorite feature for tech watch. Don’t have time to read the indigestible changelog of PrestaShop version 9?

Import the changelog into NotebookLM, click on “Generate audio”. The AI creates a 10-minute podcast (US radio style, now available in other languages) where two AIs discuss the new features.

I listen to it in the car. It’s amazingly realistic and allows you to learn “passively”.

Part 4: Vision & Future Impact

Why am I talking to you about this today? Because NotebookLM is only the first step in a profound transformation of our professions.

We’re moving from an era of search (Google Search) to an era of synthesis (Generative AI).

For tomorrow’s PrestaShop developer, the key skill will no longer be knowing by heart all the core classes. The key skill will be knowing how to build the right knowledge bases for their AI.

Your added value is shifting:

Before: “I know how to code this feature.”

Tomorrow: “I know how to architect the system and pilot AIs so they code this feature without security flaws and respecting standards.”

This is excellent news. It means fewer repetitive tasks (reading docs, copy-pasting CSVs) and more time for what really matters: user experience and business strategy.

Conclusion

For the PrestaShop ecosystem, NotebookLM is the ultimate assistant. It bridges the gap between the solution’s growing technical complexity and merchants’ need for speed.

It doesn’t replace your expertise; it multiplies it. It allows you to have an answer to everything, as long as you have the right documentation at hand.

My challenge for you this week:

Take that supplier PDF sitting on your desk, or that module documentation you never have the courage to read. Put it in NotebookLM. Ask a question. And watch your productivity soar.

Your move. 🚀

Questions Fréquentes

What is NotebookLM?

NotebookLM is a Google tool based on RAG (Retrieval-Augmented Generation) technology that allows an AI to analyze and answer your questions based solely on your source documents, without hallucinating. It’s like having an assistant who actually reads your docs before responding.

How is NotebookLM different from ChatGPT?

ChatGPT is trained on the entire internet and can make up answers based on its “memory”. NotebookLM, on the other hand, bases itself only on the documents you provide. If the information isn’t in your sources, it will say “I don’t know” instead of hallucinating.

What sources can I import into NotebookLM?

You can import PDFs, text files, Google Drive documents, and website URLs. For PrestaShop, this includes supplier catalogs, technical documentation, error logs, module source code, etc.

Is NotebookLM free?

Yes, NotebookLM is currently free and accessible via notebooklm.google.com. Google assures that your data is not used to train the global model.

Is my data confidential in NotebookLM?

According to Google, your sources remain in your private instance and are not used to train the global model. This is a critical point for merchants who import sensitive data.

What is RAG technology?

RAG stands for Retrieval-Augmented Generation. Instead of asking the AI to make up an answer based on its memory, we ask it to read your documents and respond only based on them. It’s the difference between an expert who guesses and an expert who checks their sources.