Building a Viral Meme Generator with Next.js and Google's Nano Banana Pro API

How I turned a trending internet meme into a full-stack AI-powered web app (and why Nano Banana Pro is a game-changer for face manipulation)

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If you've spent any time on Twitter or Reddit lately, you've seen them: the "kirkification" memes. Pictures of politicians, celebrities, or random people with Charlie Kirk's distinctively proportioned face seamlessly swapped onto them. They're hilarious, they're viral, and they're surprisingly hard to make well.

I wanted to create these memes. But every time I tried, I hit the same wall: manual face-swapping in Photoshop took 20+ minutes per image, online meme generators produced low-quality results, and I never quite nailed the subtle facial proportions that make a kirkification truly cursed.

So I did what any developer would do: I built Kirkify AI, a web app that generates photorealistic Charlie Kirk face swaps in seconds using Google's Nano Banana Pro API. Here's how I went from frustration to a working product, and why Nano Banana Pro turned out to be the perfect tool for this absurdly specific problem.

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The Problem: When Memes Take Longer Than They Should

I wanted to create quality kirkification memes, but every approach had major drawbacks:

Option 1: Photoshop Manual Labor

• 15-20 minutes per meme masking, aligning, and blending
• Required significant design skills
• Results often looked fake despite the effort

Option 2: Existing Online Tools

• Generic face-swap apps that didn't understand kirkification
• Low-quality results with obvious cutout edges
• Often watermarked or paywalled

Option 3: Manual AI Prompting (Midjourney, DALL-E)

• Wildly inconsistent results
• No reference image support for consistent likeness
• AI didn't understand Charlie Kirk's specific proportions

The fundamental issue? A speed versus quality trade-off that felt impossible to resolve. I wanted a tool that could generate photorealistic kirkifications in under 30 seconds without requiring Photoshop expertise or AI prompting knowledge.

That's when I started looking into AI image APIs specifically designed for face manipulation, and that's how I discovered Nano Banana Pro.

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Discovering Nano Banana Pro: The API I Didn't Know I Needed

My requirements were clear: handle face manipulation with high fidelity, support reference images (not just text prompts), process requests asynchronously, and deliver photorealistic results consistently.

I explored OpenAI's DALL-E, Replicate's Flux models, and Stability AI—all excellent for general image generation, but face-swapping is a specialized task requiring precise facial feature mapping and seamless blending.

Then I discovered Google's Nano Banana Pro. Here's what made it stand out:

Why Nano Banana Pro Won:

• Face manipulation as core functionality - Not an afterthought, but engineered specifically for this
• Native reference image support - Feed it Charlie Kirk's actual face for consistent results
• Async callback architecture - Perfect for time-intensive operations
• Photorealistic quality - Outputs indistinguishable from real photographs
• Intelligent context preservation - Maintains hair, clothing, lighting, and backgrounds automatically
• Granular facial proportion understanding - Actually understands facial geometry, not just overlaying faces

That last point was crucial. Charlie Kirk's face has very specific proportions that make the meme work. Nano Banana Pro understands facial geometry—the spatial relationships between eyes, nose, mouth—and maps them accurately while adapting to different angles and lighting.

Even complex costumes and comic book characters work flawlessly—Deadpool gets the full kirkification treatment

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Building Kirkify AI: Tech Stack & Architecture Decisions

Tech Stack:

• Next.js 16 (App Router) - Server-side rendering, API routes, React 19
• TypeScript - Type safety for async operations and API contracts
• PostgreSQL + Drizzle ORM - Track generation tasks and status
• TailwindCSS + Radix UI - Fast, accessible UI components
• Vercel AI SDK - Multi-provider support foundation

The Async Architecture Challenge:

Nano Banana Pro takes 10-30 seconds per face manipulation. I needed a system that could handle this without blocking the UI or timing out. Here's the flow:

1. User submits image → Frontend calls /api/generate-images
2. Backend creates task → Saves to database (status: "queued"), returns run ID
3. Backend calls Nano Banana Pro → Via APImart with callback URL, then moves on
4. Nano Banana Pro processes → Async on their infrastructure
5. Webhook receives result → /api/ai-callback/apimart updates database (status: "success")
6. Frontend polls status → /api/ai-task-status with exponential backoff (1s → 2s → 4s → 10s max)
7. User sees result → When polling detects "success" status

This webhook + polling hybrid gives real-time feedback without hammering the API. The exponential backoff keeps it responsive early on but backs off for longer operations.

I also built multi-provider support (OpenAI, Replicate, FAL) for flexibility and redundancy, though Nano Banana Pro became the star performer for face manipulation.

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The Prompt Engineering Journey: Less Work Than Expected

I expected this to be the hardest part—getting AI to consistently understand "kirkification" while preserving context seemed like weeks of work.

Here's what actually happened: Nano Banana Pro just worked. After a few test runs, I landed on this prompt:

A photorealistic face swap based on this reference image.
Replace the face of the person in the image completely with
the face of Charlie Kirk. Capture Charlie Kirk's distinct
facial features, proportions, and likeness. Crucially,
maintain the exact original context: keep the same hair,
clothing, body pose, background setting, lighting conditions,
and film grain. Seamless blending, highly detailed,
realistic photograph.

That's it. No complex parameter tuning, no multi-step pipelines, no special case handling. This single prompt works reliably across all scenarios.

Why This Worked:

• Natively understands facial geometry and proportions
• Handles context preservation holistically without explicit per-element instructions
• Performs seamless blending across different lighting conditions automatically
• Renders photorealistic results without over-processing

Nano Banana Pro reduces complex face manipulation to a simple, descriptive prompt. The API handles the hard parts—facial geometry mapping, lighting adaptation, edge blending, context preservation.

The same prompt works across wildly different scenarios—Spider-Man in action

From superheroes to mech suits, consistent quality across all inputs

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The Result: From Idea to Production

After integrating everything, I had a working product: upload any image, wait 20-30 seconds, and receive a photorealistic Charlie Kirk face swap.

The user experience is deliberately simple. Upload a photo, and within half a minute you get back a seamless face swap with no cutout lines, no weird blending artifacts, and the original context perfectly intact. Everything except the face—hair, clothing, background, lighting—remains untouched.

Here are some real examples:

A majestic lion gets the kirkification treatment—notice how Charlie Kirk's facial proportions are preserved while maintaining the original lighting and mane

Even complex facial expressions and professional photography lighting are handled seamlessly

Animals work particularly well—this fox demonstrates perfect facial proportion mapping

The results speak for themselves. These look like actual photographs that could plausibly exist.

Key Learnings:

• Choosing the right API saves months - Nano Banana Pro's specialized capabilities eliminated the need to build face-swapping logic from scratch
• Async architecture is essential - Quality face manipulation takes time; trying to force sync would cause timeouts and frustrated users
• Invest in prompt templates upfront - One well-crafted prompt has powered thousands of generations with ~95% success rate
• Multi-provider redundancy works - Fallback providers keep the app reliable during peak loads

Performance-wise: most generations complete in 15-25 seconds, and based on the increasingly cursed memes being created, user satisfaction is high.

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Try Kirkify AI (and Let the Cursed Memes Begin)

Kirkify AI is live at ai-kirkify.com. Upload any photo—friends, celebrities, even pets—and watch the face-swapping magic happen.

For Developers:

The architecture patterns here—async callbacks, webhook handling, polling with exponential backoff—apply to any long-running API operations. If you're building with AI image generation or video processing, these patterns are broadly applicable.

Nano Banana Pro is accessible through APImart, an AI API marketplace. The documentation is clear, the API is straightforward, and the results deliver on the promise of photorealistic face manipulation.

What's Next:

I'm exploring batch processing for multiple images, style transfer options, and expanding to other viral meme formats. The multi-provider architecture makes adding new capabilities relatively painless.

The Takeaway:

Sometimes the best way to learn a technology is to build something absurd with it. Kirkify AI started as "I want faster Charlie Kirk memes" and evolved into a robust AI-powered web app with proper architecture and production-grade error handling. If you're curious about AI image generation, pick a ridiculous idea and start building. You'll learn more from shipping than from tutorials alone.

Now go forth and kirkify responsibly. Or irresponsibly. I'm not your boss.

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Want to see the code or contribute? Check out the GitHub repository or try the tool at ai-kirkify.com.

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