Influencer’s guide: Turn a single image into cinematic content with AI

Forget cameras, actors, and big budgets. What if you could build an entire visual story from a single AI-generated image?

That’s the creative challenge YouTube creator Migue Baena takes on in his latest video – and he pulls it off with remarkable results.

With the right prompt, a sharp visual eye, and a few smart AI tools, he shows how you can turn one still image into a cinematic narrative, with no filming required.

In the step-by-step tutorial (originally in Spanish, but available with English voiceover), Migue shares exactly how he does it. He breaks down the process in detail – from choosing the right model and crafting effective prompts, to generating a full sequence of shots that stay consistent in character, background, and tone.

Whether you’re a content creator or just curious about what AI can do, this new approach offers a faster, more flexible way to build compelling visual stories.

Watch the full video here:

The app idea: help businesses get unstuck with AI

In his day job, Christian runs an agency that helps businesses adopt AI. One of the biggest onboarding challenges is that clients rarely know what to build first.

They’ve played around with ChatGPT. They’ve maybe seen a few AI demos. But when it comes to identifying real use cases inside their business, they’re stuck.

That’s where the idea for the app came from: a voice-powered assistant that helps business owners figure out how AI could apply to their business. 

The user would speak or type answers to a few questions, and the app would generate:

• A list of recommended AI automations or agents to build

• A 30/60/90 day implementation roadmap

• A personalized, downloadable PDF report

More than just being a lead magnet, the app had the potential to replace Christian’s previously  manual scoping process entirely and create a clear path from ‘I’m interested in AI’ to ‘I’m ready to build.’

The build: from blank page to working app in 24 hours

Christian gave himself 24 hours to create his app from start to finish. That meant no time for perfect UI, no overengineering, and no overly complex development.

Instead, he used three key tools:

• Make – to power the automation, logic, AI prompts, and PDF generation

• Lovable – to design the chat-based interface

• Supabase – to handle login, authentication, and data storage

Make was used to build out the core scenario that would act as the engine for everything else.

As a visual no-code platform, Make lets you build automated workflows by connecting apps, APIs and logic blocks. For this project, Christian used it to run the entire backend of his app.

Here’s what that looked like:

1. Build the chat experience with Lovable Christian designed the front-end interface in Lovable, using a chat-style flow where users could type or speak their answers. He added voice input and prompt logic directly in Lovable to guide users through the process in a natural way.

2. Trigger via webhook Once a user completed their answers, Lovable sent the data to Make using a custom webhook. This triggered the main automation scenario.

3. Process each part of the report separately Christian split the report into six parts: executive summary, readiness scoring, key processes, tool recommendations, roadmap, and CTA. Each had its own AI prompt and module in Make. This gave him more control, better results, and a modular way to iterate without starting from scratch.

4. Use OpenAI and Perplexity for generation Depending on the type of content, Make routed requests to OpenAI (for summaries and action plans) or Perplexity (for deeper tool recommendations based on the business context).

5. Compile and format the output Once all sections were generated, Make pulled them together and created a structured PDF using a pre-defined template.

6. Send it back to the front-end and store it The finished report was returned to Lovable to display in the app. Supabase was used to manage user login and store session data, so returning users could access past reports.

With each module visible within the Make scenario, it was easy to troubleshoot, improve prompts, and expand functionality without rewriting anything.

Christian says:

“If I’d tried to hard-code this workflow, I’d still be stuck in the weeds. With Make, the process is so much easier. That’s why I love Make. I didn’t need developers to do any of it.”

The result: A working product (and a $5,000 offer)

With the app running, Christian turned his focus to outreach.

He used Outbound, his own (yet-to-launch) personalized outreach platform, to create cold campaigns and tapped into his personal network to get faster responses.

Within a few hours, he’d had multiple conversations. One contact offered $3,000. Christian countered at $10,000. They met in the middle and a formal offer of $5,000 was made.

However, in the end, he didn’t take it.

After discussing with his COO, Christian decided the long-term potential of the tool was worth more than the cash. It’s now used as part of his agency’s onboarding process and already delivering value.

Christian says:

“Even though I didn’t sell this app, I feel like it’s a pretty good testament to what’s possible. I built the whole thing in a day and now I’ve got something real I can keep growing.”

What one day and the right tools can do

Christian has proved that, with the right tools, it’s perfectly possible to build a full working app, with a clear use case and validated interest, in 24 hours, with no code necessary.

In one visual workflow, Make handled:

• All automation logic

• AI prompt creation

• Dynamic report creation

• Third-party integrations

• Routing and webhook handling

For other developers sitting on product ideas, it’s a reminder that you don’t need to overthink the build to be able to create something valuable.

Thinking of building your own AI app? 

Get started for free with Make today.