Stop Staring at the Cursor: How to Build a Video-First Content Pipeline Using Brand and Concept

Author's): Anna Her

Originally published in Towards Artificial Intelligence.

A pragmatic guide to turning raw video rants into polished SEO articles without writing a single word from scratch.

We've all been there. It's 9:00. You have a fresh cup of coffee. You have a great idea for an article that can establish your authority in your niche. You open a blank document. And then you freeze.

The flashing cursor is mocking you. The sentence that sounded so smart in your head five minutes ago now seems clunky. You write a paragraph, delete it, check your email and suddenly it's noon. You produced zero content.

This is not a problem of creativity; it is a friction problem.

Most professionals – whether you're a project manager, consultant, or junior developer – are better speakers than writers. When you talk to a client on Zoom, insights flow naturally. When explaining a concept to a junior colleague, you are eloquent and precise. But the moment your fingers touch the keyboard, this state of fluidity evaporates.

The solution is not to force yourself to become a better writer overnight. The solution is to change the input mechanism.

We need to stop writing from scratch and start “producing” content.

In this guide we will build a file Video content pipeline. We'll build a “No Code” automation system where you simply drop your raw video file (Loom, Zoom clip, or voice memo) into a folder in Google Drive, and a few minutes later, a fully formatted, SEO-optimized blog post will appear in your Notion workspace.

We don't use AI to “generate ideas” or hallucinate. We use artificial intelligence to translate your actual voice into text.

Here's how to build the machine.

The “lazy” stack: what you really need

Before we start connecting the wires, let's take a look at the tool kit. We avoid expensive enterprise software in favor of tools you probably already use, connected by a powerful automation center.

Here is the stack:

1. Google Drive: Release. It's reliable, handles large files well, and syncs with your phone.
2. Brand (formerly Integromat): Nervous system. For this particular version, we choose Make over Zapier because its visual interface allows for better data manipulation (particularly JSON parsing, which we'll talk about later).
3. OpenAI API (Whisper + GPT-4o): Brain.

• Note: You need a paid API account with credits loaded, not just a ChatGPT Plus subscription.

1. Concept: Destination. Your content calendar is here.

Cost Note: This workflow isn't free, but it is cheap. Processing a 10-minute video through the OpenAI API costs pennies. Compare this to an hourly rate where you stare at a blank screen for two hours and the return on investment is mathematical, not theoretical.

Step 1: Trigger Mechanism (Google Drive & Make)

The goal here is simplicity. You don't need to log in to the dashboard to start this workflow. You should be able to drag the file to the folder and go.

Set up Google Drive

1. Go to your Google Drive.
2. Create a new folder. Name it exactly: _INPUT_RAW_VIDEO.
3. (Optional) create a subfolder named Processed where we will later transfer the files so that the system does not boot twice on the same video.

Set up Make.com

Log in to Make and create a new scenario.

1. Click the big plus button and search Google Drive.
2. Select trigger: View Files in Folder.
3. Connect your Google account and select yours _INPUT_RAW_VIDEO folder.

Hidden Gem Setting: By default, this trigger can attempt to process everyone the file you drop there, including a PDF or image. This will break our automation.

• Right-click on the Google Drive module.
• Settings Filter.
• Tag it: Media Files Only.
• Condition: disease: MIME Type contains audio OR MIME Type contains video.

Now, if you accidentally drop a spreadsheet into this folder, the automation will simply ignore it. It's a small detail, but it prevents 90% of error messages.

Step 2: From sound to text (whisper model)

Most people try to use standard dictation tools for this purpose. This fails. Always. Standard dictation creates a wall of text without punctuation and usually destroys technical terms.

We will use OpenAI Whisper model. This is shockingly good. He understands strong accents, speaks quickly, and even ignores “ums” and “ahs” to some extent.

Configuration

1. In Make, add a new module connected to the Drive trigger: OpenAI.
2. Select an action: Create Transcript (Whisper).
3. In the “File” field, map the file from the Google Drive module.

“Hidden Gem”: Context parameter

Here's the secret that most tutorials miss. In the OpenAI module settings there is a field called Hint (optional).

Don't leave this blank.

Whisper uses this prompt to understand context AND spelling your sound. If you work in a niche industry, this is mandatory.

For example, if I'm recording a rant about automation, I'll paste this in the Hint box:

Transcription covers No-Code automation, SaaS, API integration, JSON scripting, Make.com, Zapier and Python.

By giving him these keywords, Whisper knows that when I say something that sounds like “Jason” I really mean it JSON. This simple step saves you 20 minutes on editing later.

Step 3: Intelligence Layer (Context Injection)

Now we have the raw record. It's accurate, but it's dirty. It reads like a spoken conversation – full of associations and repetitions. We need to turn this into an article.

Add another one OpenAI module, but this time select Create follow-up (chat). We want to use the model GPT-4o Or GPT-4-Turbo.

“System Hints” strategy.

We won't just ask him to “write a blog post.” This results in general robotic fluff. We have to use Context injection.

We need to tell AI Who is and How to write.

Copy this into the System Message box:

You are a content strategy expert and technical writer. You prefer short, punchy sentences. You avoid corporate jargon like “unbundling,” “leverage,” and “digital landscape.”

Your goal is to take the provided transcript and turn it into a high-value educational article.

• Maintain the author's original opinions and strong stance.
• Use analogies to explain complex topics.
• Use Markdown formatting (H1, H2, bold).

Copy this into the User Message box:

Here is the transcript: {{text_from_whisper_module}}

By explicitly banning specific buzzwords and defining personas, the results change from “general AI” to “professional draft.”

Step 4: JSON secret (data structuring)

If you stop at step 3, ChatGPT will spit out a long block of text. You will then need to copy the title and paste it into Notion. Copy the content and paste it into Notion. Copy your LinkedIn signature and paste it onto LinkedIn.

That is, manual work. We hate manual work.

We will force artificial intelligence to give us data in a format that computers can understand: JSON.

Advanced prompt

Return to the OpenAI module (step 3). We need to change the instructions. We don't just want an article; we want a data object.

Add this to your user message:

IMPORTANT: The response must be output in strictly valid JSON format. Do not add any conversational text before or after the JSON. Use this diagram:

{ “blog_title”: “catchy, SEO-optimized title”, “blog_body_markdown”: “Full article content in Markdown”, “linkedin_post”: “A short, engaging LinkedIn post summarizing the article”, “tags”: (“tag1”, “tag2”, “tag3”) }

Parser

Now the AI ​​will return code, not text.

1. Add JSON module in Make.
2. To choose Parse the JSON.
3. Map the output content from the OpenAI module to this parser.

Now Make.com sees blog_title AND linkedin_post as separate variables that can be dragged around. This is the difference between “using AI” and “developing software.”

Step 5: Landing (concept database)

Finally, we need to park this content somewhere where it can actually be viewed.

1. Add Concept module: Create a database item.
2. Select your Content Calendar database.
3. Map fields:

• Name (title): Drag in blog_title variable from the JSON module.
• Page content: Drag in blog_body_markdown variable.
• Status: Set it to “Design”. (Never set automation to “Publish” automatically. You are the editor and the AI ​​is the author).
• Signature on LinkedIn: Map linkedin_post variable to text property in Notion.

Result

Here's the real-life workflow:

1. You are finishing a conversation with a client during which you explained a complex topic perfectly.
2. You save the recording.
3. You drop the MP4 into yours _INPUT_RAW_VIDEO folder.
4. Go eat lunch.
5. When you return, you open Notion. A new page has appeared in the “Drafts” column. It includes the title, the full article, and pre-made social media snippets.

80/20 reality check

Let's be honest about what we just built.

This system will not replace you. It replaces the first 80% of the work. The output you get from Notion will be good, but it won't be perfect. This may misinterpret the joke. Maybe he's using a metaphor that doesn't quite hit the mark.

Your job is no longer “writer.” Your title is “Editor-in-Chief”.

You have to read the project. Add your personal style. Fix the rhythm. But editing a 1,500-word draft takes 15 minutes. It takes 4 hours to write it from scratch. This is a victory.

This workflow eliminates the “blank page syndrome.” This way, your best ideas won't die in your head just because you didn't have time to type them out.

Next 15 minutes

Don't try to build the entire spaceship at once. Start small.

Now go to Google Drive and create it _INPUT_RAW_VIDEO folder. Then log in to Make and simply configure Step 1 (Trigger) i Step 2 (Transcription).

Even if you receive an automated email transcribing your voice notes, you're already ahead of the 99% of people who rely solely on memory.

Automation of your visual presence

We solved the problem text contents. We took your voice and turned it into blogs and LinkedIn posts. But in 2025, SMS is only half the battle.

The “Video-First” philosophy assumes that video is the most important asset. However, creating a high-quality video for every use case – such as a tailored CV video for a specific application or a tailored pitch video for each investor – cannot be done manually. You can't sit in front of a camera 40 hours a week.

Just as we used Make and OpenAI to automate the writing process, there are tools designed for automation visual efficiency.

If you want to scale your personal brand beyond what you can physically capture, it's worth exploring PortfolioVideo. It is a platform that allows you to transform documents – CVs, presentations, scripts – into professional videos using AI avatars.

Imagine the workflow we just built, but in reverse: you enter a script into the system and instead of a blog post, you get a studio-quality video with an avatar showcasing your ideas, or a cinematic “Vibe Motion” headline for your LinkedIn profile.

Automation is not about laziness. The idea is to let your ideas travel further than physical time allows.

Now go record your rant. Your system is waiting.

Published via Towards AI