If you have subscribed to my newsletter, you may know that my previous post explained the basics of what Nano Banana Pro can do and shared a number of mind-blowing use cases.
It went viral (and even ranked on Google) because people are tired of hearing "it can make a picture of a cat".
Later, I wrote a post explaining how Nano Banana can specifically help if you are a designer, a teacher, or a founder, and I shared practical workflows for each.
Seeing the hype around Nano Banana Pro, I spent another 50+ hours going deeper and found 7 advanced, profession-specific use cases that actually justify the "Pro" in the name.
And that's what I'm going to share with you today.
Note: If you enjoy reading this type of practical and informative content, and want to get my best AI insights straight to your inbox, consider subscribing to my newsletter, AI Made Simple. It's free.
With that said, let's get started.
1. Generate Isometric Game Environments & Assets
You know, I started my career as a web developer, spent a good amount of time playing some of the best games in my early days, and even have solid experience working in the gaming industry, like writing code, designing consistent game assets, and so on.
I know how difficult it is, and how much time game developers spend building all of it.
Even many AI tools struggle to keep the consistency right.
But after using Nano Banana Pro, I found that it creates perfect isometric grids and doesn't skew the angles. This means you can generate assets that actually fit together on a map.
Here's the prompt I tried:
Create a stylized low-poly isometric view of a fantasy "Potion Shop" on a floating island. The building should have a purple thatched roof, a glowing sign that reads "Potions", and barrels of colorful liquid outside. The ground is grass with small stone paths. The background is a clean solid color. The lighting should be warm and cozy, resembling a high-quality mobile game asset. 3D render style, Blender Cycles.
Here's another prompt to generate the complete game visual:
Create a cinematic buyer persona poster for "The Reluctant CTO".
Key attributes:
- Hates risk, loves reliability
- Trusts benchmarks, not promises
- Wants tools that integrate seamlessly
Render a dramatic portrait with dim server-room lighting, blue-green hues, reflective glasses showing code, and the tagline: "If it doesn't scale, it doesn't exist."
Include bullet points as minimal typography on the side. Aspect ratio 3:2.
And here's what it generated:
Insane, right?
This can be useful for:
Indie Game Devs: rapidly prototyping levels or creating UI icons.
Web Designers: creating trendy isometric illustrations for landing pages (which usually cost a lot on stock sites).
2. Generate Labeled Synthetic Data for Computer Vision Training
You know, collecting and labeling real-world training data for object recognition models is tedious, expensive, and often biased.
And that's where Nano Banana Pro helps.
It can generate high-fidelity, synthetically labeled images based on complex probabilistic constraints, allowing you to create edge-case scenarios that would be impossible to photograph.
This is a workflow few people talk about, but it's a killer feature for machine learning engineers.
Here's the prompt:
Generate a hyper-realistic image of a retail shelf display for a new energy drink brand. The image must contain precisely 12 units of the product bottle (green label with black cap) scattered semi-randomly on the top two shelves. The lighting should simulate poor, low-light retail conditions (ISO noise visible, warm orange ambient lighting). Crucially, the final image must also contain bounding boxes around each of the 12 product bottles and be overlaid with a JSON-like text output in the corner listing the coordinates and class label: {"object": "energy_drink", "count": 12, "labels": [ (x1, y1, x2, y2), … ] }. The perspective should be a slightly downward, high-angle shot.
And here's what it generated:
Just try counting the bottles manually, and you'll see that it actually generated 12 bottles in one go with a precise labeled image that you can use for training data.
This can be useful for:
Machine Learning Engineers / Data Scientists: Generating vast datasets of corner-case images (e.g., obstructed views, bad lighting, unusual angles) to robustly train models for inventory management, quality control, or autonomous vehicle object detection.
Robotics Engineers: Creating complex visual environments to test robot navigation and object grasp prediction.
3. Create Cinematic Storyboarding With Camera Direction
We all know that even today generating realistic, long videos isn't possible with AI tools.
So think about how difficult it is to generate a cinematic storyboard with every small detail and camera direction included.
If you work in video, you know the pain, and hiring a storyboard artist is expensive.
That's where you can use Nano Banana Pro, since it understands cinematic terminology and you can talk to it like a Director of Photography (DoP). It even knows what "depth of field", "bokeh", and "Dutch angle" mean.
Here's a prompt I tried:
Hyper-realistic architectural render of a massive organic-tech research facility built inside the hollow trunk of a colossal, ancient bioluminescent tree in an alien jungle at twilight. The exterior blends smooth dark metal panels with translucent, pulsating bio-luminescent membranes emitting a soft inner glow. Polished dark-wood pathways and glowing vine-bridges wrap around the tree's interior. In the foreground, a detailed multi-limbed robotic drone with glowing sensors tends to exotic alien flora in a hydroponic garden. Above, glowing spore-like organisms drift through humid mist, reflecting the tree's light and the setting alien sun. Emphasize ancient bark texture, sleek metal surfaces, and translucent membranes. Volumetric lighting, extreme depth of field, cinematic cool blues, deep greens, subtle purples. Octane render, 16k, photorealistic.
And here's what it generated:
This can be useful for:
- Filmmakers/YouTubers: planning shots before picking up a camera.
- Advertising Agencies: pitching a TV commercial concept to a client.
- Writers: visualizing a scene to help describe the atmosphere better in a script.
4. Convert Confusing Career Paths Into Visual Skill Maps
Let's be honest, we all want to learn new skills today because we're seeing AI eliminating many low-end jobs.
And naturally, we're worried about the future.
But the main problem is that we don't know the right roadmap to learn some complex skills faster and actually understand the core concepts.
Sure, you can ask ChatGPT or any other AI model, and it will generate a roadmap, but it will always be in text form.
And that's where you can use Nano Banana Pro to generate a visual career roadmap for any skill.
Here's the prompt I wrote:
Create a career roadmap for "Become a Senior Data Analyst in 18 months" as an RPG skill tree.
Use an isometric game-map aesthetic with branching paths.
Each node must include:
- Skill name
- Tool (SQL, Excel, Tableau, Python)
- Time required
- A tiny icon representing the skill
Use a dark fantasy style, glowing node connections, and readable small text. Include a starting point "Zero Experience" and final node "Senior Data Analyst at $100K+". Use subtle neon accents. Aspect ratio 16:9.
And based on that, here's what it generated:
This use case is relevant for everyone, so there's no need to specifically mention where it can be useful.
5. Generate a Full "Inside-Out" Product Breakdown
Let me be honest, even today, most AI image generators hallucinate when generating complex visuals.
No doubt, I tried generating some complex mechanics with different AI image generators, and they placed gears where they don't belong.
But Nano Banana Pro's reasoning engine is different, it understands complex concepts and can generate them visually with accuracy.
So instead of hiring a 3D illustrator for a preliminary manual, you can generate an exploded view to visualize the assembly.
Here's the prompt I tried:
Create a technical, isometric exploded view of a vintage mechanical camera in dark mode. Separate the lens assembly, shutter mechanism, and body casing. Label the three major components with floating text lines. Style: Clean vector line art, white background, blueprint blue accents. High mechanical accuracy.
And here's what it generated:
Here's another example:
Generate a photorealistic 3D exploded view of a high-tech professional camera drone. The components (propellers, camera sensor glass, lithium battery block, and internal logic board) should be hovering vertically in mid-air, separated to show the internal engineering stack.
Materials should look premium: matte black plastic, brushed aluminum, and copper wiring accents. Use dramatic studio lighting with cool blue rim lights against a dark grey background.
Add floating text labels pointing to specific parts: Label the lens 'OPTIC SENSOR', the battery 'Li-ION CORE', and the motor 'MAGLEV DRIVE'. Ensure the text is sharp and futuristic.
And based on that, here's the output:
This can be useful for students to understand complex visuals, for teachers to explain concepts more easily, and for other similar purposes.
6. Turn a Rough Floor Plan Into a Trade Booth Layout
In my last post, I showed you how to generate a cozy minimalist design from a room plan, but let's get specific for professionals.
If you are planning a pop-up store, a trade show booth, or a coffee shop layout, you can upload a rough sketch of the floor plan and ask it to generate the layout you want.
Let's take an example.
Suppose you have a 10x10 booth at a conference and you need to see how it looks with your branding colors, a counter, and a TV screen.
Here's the prompt I tried:
Visualize a trade show booth design for a tech company. The space is small (10x10 feet). Include a back wall with a large screen displaying a 'Cloud Graph'. Use a minimalist white and orange color palette. Place a high table in the front right. Realistic lighting.
And here's the output:
You see, by providing a more detailed prompt like this, you get a clear output and a complete idea of whether to move forward with the design.
And thanks to this, you can visualize anything you need, whether it's a pop-up store, a trade show booth, a coffee shop layout, or something entirely different.
This can be useful for:
- Event Planners: To visualize venue layouts.
- Retail Owners: To plan seasonal window displays.
- Real Estate Agents: To virtually stage empty commercial offices for listings.
7. Create a Hyper-Realistic Product Photography
We all know that studio photography is expensive because controlling liquids, smoke, and gravity is hard.
And companies don't really have alternatives, so they end up paying a hefty fee for product photography.
That's where Nano Banana Pro can save you money and generate exactly what you need.
And yes, you can ask for a liquid splash that looks frozen in time, and the light refraction through the liquid will be physically accurate. This is the "money shot" for marketers.
Here's the prompt I tested:
Commercial product photography of a luxury perfume bottle made of amber glass, placed on a dark reflective surface. The bottle is surrounded by splashing water and swirls of golden smoke. The lighting is backlit to make the liquid inside the bottle glow. The text on the bottle label reads "Eternity". Macro lens details, water droplets on the glass, 8k resolution, unreal engine 5 render style.
And here's the output:
This can be useful for:
E-commerce Owners: creating seasonal variance for products (e.g., your product in snow for Xmas, or on sand for Summer) without a reshoot.
Social Media Managers: creating high-end aesthetic posts for brands with zero budget.
Hope you like it.
That's it, thanks.
Here are some more valuable post you can read to learn how to use AI in practical ways:
99% of People Use AI Wrong - Here's How I Actually Learn and Remember Faster
I Used Google’s NotebookLM for 2 Years and It Changed the Way I Learn Forever
AI Can Do More Than You Think - The Most Practical Ways to Use AI Every Day
I Use These 5 AI Workflows for My Creative Edge (and They're Changing Everything)









Top comments (1)
Thanks for sharing these use cases. I can now see more such use cases that I can implement inside my workflow.
Thanks a lot.