Welcome back to Staying Ahead 👋

If you’ve ever tried to make a product lookbook, you know the pain of having to shoot photos in one place, edit them somewhere else, generate AI mockups in a third tool, write video prompts in a fourth, and pray that the final output looks coherent.

Flora AI kills that workflow. It’s an infinite canvas where you upload assets, generate AI images, write video prompts, and produce the final output, all in one connected space.

In this guide, we’ll walk through exactly how to use Flora to create model mockups and a visual branding video for a Rajasthani jacket, with me as the model. By the end, you’ll have a repeatable workflow for any product shoot.

Time required: ~5 minutes.

Flora (flora.ai) is an AI-powered creative workflow system. Think of it as a cross between Figma’s design canvas and Miro’s whiteboard, but with AI generation models baked directly into the interface.

Three things make it different from juggling separate tools:

Everything stays connected. Your text prompt, reference images, generated shots, and video output all live on one canvas. Nothing gets lost in a downloads folder.

Start by creating a new Flora project and uploading your raw materials. For this campaign, we need four things: a photo of me (the model), the two jacket variants we want to showcase, and a reference image of a Rajasthani turban for styling context.

Drag and drop them onto the canvas. Flora automatically creates an Assets panel, a vertical stack of labelled image nodes. Name each one clearly: “Vaibhav,” “Jacket,” “Jacket 2,” and so on. These labels help you stay oriented when the canvas fills up.

Now we turn these raw assets into polished product shots. Click the + button on any asset node to create a new generation node connected to it.

Here’s the key concept: you can connect multiple asset nodes to a single generation node. Flora’s AI will use all of them as reference inputs. So we connect my photo + the first jacket + the turban image to one node, and write a prompt like:

Flora takes the model’s face, the jacket’s pattern, and the turban’s style, and composites them into a new image set in the specified scene. The toolbar at the top lets you pick which AI model to use (set to Auto by default) and access additional tools.

Repeat for the second jacket. This time, try a different scene and different styling cues:

Zoom out on the canvas and you’ll see the full picture. Your Assets panel on the left connects via curved lines to the Shots panel on the right. Each line represents which inputs fed into which output.

This is where Flora’s node-based approach really shines. Instead of a flat folder of images with no context, you have a visual map of your entire creative pipeline. You can see that the “Embroidered Jacket” shot drew from Me + Jacket, while the “Rajasthani Outfit Scene” drew from Me + Jacket 2 + the turban image.

This view is also useful for team collaboration. If a colleague opens the project, they don’t have to guess what reference material was used for each shot — the connections make it self-documenting.

Time to go from still images to video. Pick your best generated shot (we’ll use the camel scene) and create a new text generation node from it.

This time, instead of generating an image, you’re asking Flora’s text model to write a video prompt based on the photo. Something like:

Flora’s text model returns a rich, cinematic video prompt describing camera movements, lighting, and atmosphere — golden hour desert light, a slow 360-degree pan, sand particles drifting in the breeze, the camel swaying its head naturally.

Connect the text prompt node and the reference image to a new video generation node. Flora sends both to the video model (Kling, Higgsfield, or whichever is set), and you get back a short branding clip.

The result, titled “Rajasthani Joy” is a cinematic clip with the aspect ratio, camera movement, and mood defined by the prompt. The toolbar shows you can adjust the aspect ratio (we used 16:9), access additional tools, and download the final video.

From here you can iterate: try different prompts, different aspect ratios, different jacket combinations. Everything stays on the same canvas, so your creative history is always visible and traceable.

Flora isn’t the simplest tool to learn. The node-based system takes a bit of getting used to, and there are no pre-built templates to lean on. But once you internalise the workflow, it’s genuinely faster than bouncing between four separate tools.

The visual lineage feature (seeing exactly which inputs created which outputs) is something no other tool in this category does well. For teams working on campaigns with multiple product variants, that alone justifies the learning curve.

Try it with your own product this week. Upload three assets, generate two mockups, and make one video.

TLDR: it can yet make humans look artificial, but once that’s fixed, this will be dope. 

Reply and tell me what you think.

I sat down with Josh Woodward, the man behind Google Gemini AND Google Labs and got him to demo 7 Google AI tools LIVE, including one the world hasn’t seen yet. If you have 30 mins, it’s a must watch!

That's it for this week.

If you try one of these prompts, reply and let me know what you got. The most interesting results I hear about will make it into a future issue.

Vaibhav🤝

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