Introduction

Generative AI is reshaping how we interact with creative tools. From content generation to visual editing, the shift from manual workflows to prompt-based editing workflows is opening new possibilities for developers and product designers alike. Instead of relying on complex layers or pixel-by-pixel adjustments, creators can now direct AI models with natural language — “remove this object,” “change the background to blue,” or “make the image brighter.”

In this blog, we’ll explore how to build a prompt-driven image editor using Nano Banana Templates, demonstrate how to remix Google AI Studio templates for common editing tasks like object removal and background change with AI, and provide a step-by-step guide to AI image editing apps that can be deployed as editable applications.

Why Prompt-Driven Editing Matters

Traditional image editing requires technical knowledge: understanding layers, masks, brushes, and plugins. For developers and designers, this creates a steep learning curve and limits rapid experimentation. By contrast, a prompt-driven image editor allows users to describe changes in plain English (or any supported language) — reducing complexity and expanding accessibility.

For example:

• Instead of spending minutes erasing a background manually, you can simply type:
  
  “Remove the chair from the background and replace it with a plain white wall.”
• Rather than applying multiple filters for a mood shift, you could write:
  
  “Make the photo look like a cinematic night scene.”

This shift empowers both AI tools for product designers and generative AI for developers, making it possible to deliver flexible, intuitive apps with less effort.

What Are Nano Banana Templates?

At the heart of this workflow are Nano Banana Templates — modular, developer-friendly templates built for remixing and rapid deployment of AI-powered image editors. Think of them as starter kits: instead of writing model integration code from scratch, you can plug in ready-to-use blocks for object removal, background replacement, or inpainting, then customize the UI and logic to suit your application.

Key benefits include:

• Speed to market: Rapidly prototype and launch editable AI apps deployment without reinventing core infrastructure.
• Consistency: Pre-tested flows ensure smoother performance across tasks.
• Flexibility: Easily swap models or integrate new APIs.
• Accessibility: Designed as developer-friendly AI tools, even for teams without deep ML expertise.

This makes using Nano Banana Templates for AI editing a natural choice for startups, agencies, or individual developers experimenting with applied AI.

Remixing Google AI Studio Templates

While Nano Banana offers a developer-focused layer, Google AI Studio templates provide access to pre-trained generative models. These can be remixed into Nano Banana flows for specific editing features:

1. Object Removal

• Template used: Inpainting/removal models.
• Example prompt: “Erase the person on the left side of the photo and fill in the background seamlessly.”
• Outcome: A clean, natural-looking edit without manual retouching.

This effectively turns your app into an object removal AI editor, ready for creative and commercial use.

2. Background Replacement

• Template used: Segmentation + generative fill models.
• Example prompt: “Replace the background with a tropical beach at sunset.”
• Outcome: Quick background change with AI, suitable for product photos, marketing visuals, or design mockups.

3. Style & Enhancement

• Template used: Diffusion or enhancement models.
• Example prompt: “Make this image look like a watercolor painting.”
• Outcome: Adds creative flair without needing design plugins.

These Google AI Studio image editing examples can be embedded into Nano Banana flows, giving you a powerful foundation for remixing AI templates into production-ready editors.

Step-by-Step Guide to Building Your Editor

Now, let’s walk through a practical framework — a developer guide to prompt-driven workflows that can be implemented with Nano Banana:

Step 1: Select Your Template

Choose the Nano Banana base template (e.g., object removal, background replacement).

1import { loadTemplate } from 'nano-banana';
2
3const editor = loadTemplate('object-removal');

Step 2: Connect Google AI Studio

Integrate the desired Google AI Studio templates to handle the core model logic.

1editor.useModel('google-ai-studio/inpainting-v2');

Step 3: Add Prompt Input

Enable natural language prompts as the editing control mechanism.

1editor.addPromptField({
2  placeholder: "Describe the edit you want..."
3});

Step 4: Test Common Workflows

• Object removal: “Remove the lamp on the right.”
• Background swap: “Set background to a professional office.”
• Creative effect: “Apply cyberpunk neon glow.”

Step 5: Deploy the App

Package and deploy your app via Nano Banana’s deployment tools or standard web hosting.

1nano-banana deploy --template editor

This makes deploying custom AI image editors straightforward, with minimal setup.

Applied AI in Product Design

The implications for applied AI in product design are significant:

• E-commerce: Quickly generate product photos with consistent backgrounds.
• Marketing: Adapt assets across channels using prompts.
• UX/UI: Create tools where non-technical team members can handle image edits directly.

For design teams, generative AI for creators means faster iteration cycles and reduced reliance on specialized staff for basic editing tasks.

Best Practices for Developers

To maximize the impact of your AI image editing tools, consider these best practices:

• Clarity of prompts: Guide users to be specific in their requests.
• Fallbacks: Provide default images or undo features for failed generations.
• Performance tuning: Cache results of repeated edits.
• User education: Include inline examples like “Try: remove the logo from top left.”
• Scalability: Build with cloud-based developer-friendly AI tools for handling larger user bases.

Future of Prompt-Driven Image Editing

The rise of building with AI templates is part of a broader trend: making advanced generative models accessible for everyday applications. With frameworks like Nano Banana, developers no longer need to build from scratch — they can remix, extend, and ship products at startup speed.

In the near future, we can expect:

• Richer AI-powered object removal tutorials and libraries.
• Cross-platform integrations (web, mobile, plugins).
• Improved deployment options for editable AI apps deployment in enterprise workflows.

Conclusion: Start Building Today

A prompt-driven image editor is no longer a futuristic concept — it’s a practical project you can start today with Nano Banana Templates and Google AI Studio templates. Whether you’re a developer exploring generative AI for developers, a designer seeking AI tools for product designers, or a startup looking to streamline creative workflows, this approach offers both speed and flexibility.
By following this step-by-step guide to AI image editing apps, you can quickly build and deploy powerful, intuitive editors that respond directly to natural language.