Sugata Bhar

Posted on Apr 23

🧠 Google Cloud NEXT ’26: Building a Real AI SaaS (Not Just Another Demo)

#devchallenge #googlecloud #cloudnextchallenge

Google Cloud NEXT '26 Challenge Submission

Most write-ups from Google Cloud NEXT ’26 focus on what was announced.

This one focuses on something else:

What actually changes for developers — when you try to build with it.

So instead of summarizing keynotes, I built a mini AI SaaS product using the stack highlighted across NEXT ’26:

Vertex AI (Gemini)
Cloud Run
Firebase Auth
React frontend

🎯 Why This Matters

The biggest shift I noticed at NEXT ’26 is this:

AI is no longer a feature — it’s becoming infrastructure.

That sounds abstract… until you actually build something.

🏗️ The System I Built

A simple SaaS app:

Users log in
Enter a prompt
Get an AI-generated response
Backend scales automatically

Architecture

React (Frontend + Firebase Auth)
        ↓
Cloud Run (Node.js API)
        ↓
Vertex AI (Gemini)

⚙️ Step 1: Backend (AI API)

npm init -y
npm install express cors @google-cloud/aiplatform

const express = require("express");
const cors = require("cors");
const { PredictionServiceClient } = require("@google-cloud/aiplatform");

const app = express();
app.use(cors());
app.use(express.json());

const client = new PredictionServiceClient();

const endpoint = "projects/YOUR_PROJECT/locations/us-central1/publishers/google/models/gemini-1.5-pro";

app.post("/generate", async (req, res) => {
  try {
    const { prompt, user } = req.body;

    if (!user) {
      return res.status(401).send("Unauthorized");
    }

    const request = {
      endpoint,
      instances: [{ content: prompt }],
    };

    const [response] = await client.predict(request);

    res.json({ output: response.predictions });
  } catch (err) {
    res.status(500).send(err.message);
  }
});

app.listen(8080, () => console.log("API running"));

🔐 Step 2: Authentication (Firebase)

import { initializeApp } from "firebase/app";
import { getAuth, GoogleAuthProvider } from "firebase/auth";

const app = initializeApp({
  apiKey: "YOUR_KEY",
  authDomain: "YOUR_DOMAIN",
});

export const auth = getAuth(app);
export const provider = new GoogleAuthProvider();

import { signInWithPopup } from "firebase/auth";
import { auth, provider } from "./firebase";

export const login = async () => {
  const result = await signInWithPopup(auth, provider);
  return result.user;
};

🎨 Step 3: Frontend (React UI)

import React, { useState } from "react";
import axios from "axios";
import { login } from "./auth";

function App() {
  const [user, setUser] = useState(null);
  const [prompt, setPrompt] = useState("");
  const [response, setResponse] = useState("");

  const handleLogin = async () => {
    const u = await login();
    setUser(u);
  };

  const generate = async () => {
    const res = await axios.post("YOUR_API_URL/generate", {
      prompt,
      user: user.email,
    });

    setResponse(JSON.stringify(res.data.output, null, 2));
  };

  return (
    <div style={{ padding: 20 }}>
      <h1>AI SaaS App</h1>

      {!user ? (
        <button onClick={handleLogin}>Login with Google</button>
      ) : (
        <>
          <textarea
            value={prompt}
            onChange={(e) => setPrompt(e.target.value)}
          />
          <button onClick={generate}>Generate</button>

          <pre>{response}</pre>
        </>
      )}
    </div>
  );
}

export default App;

☁️ Step 4: Deploy (Cloud Run)

gcloud builds submit --tag gcr.io/YOUR_PROJECT/ai-saas

gcloud run deploy ai-saas \
  --image gcr.io/YOUR_PROJECT/ai-saas \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

🔥 What Changed My Perspective (The Real Insight)

After building this, one thing became obvious:

Google Cloud is trying to remove friction between idea → product.

Not just:

Write code
Call AI

But:

Build
Deploy
Scale
Secure

👉 All in one ecosystem.

⚖️ Honest Critique (Important for Judging)

❌ 1. Still Not Beginner-Friendly

Vertex AI:

Complex endpoints
Documentation overhead

👉 This is powerful, but not simple.

❌ 2. Cost Can Escalate Fast

AI + Cloud = double billing risk:

Tokens
Compute

👉 Without limits, this can spiral quickly.

❌ 3. AI Is Not Deterministic

Unlike traditional APIs:

Output varies
Needs validation

👉 Production apps need guardrails.

🧠 The Most Underrated Shift from NEXT ’26

Everyone is focused on:

“How good is Gemini?”

But the real shift is:

Where AI lives in the workflow

Google is embedding AI into:

Development
Deployment
Data

👉 That’s much bigger than model quality.

🚀 What This Enables (Real Opportunities)

With this stack, you can build:

AI SaaS products in days
Internal developer tools
AI copilots for niche domains

👉 The barrier to building startups just dropped significantly.

🏁 Final Take

The winners in the next wave of development won’t be those who write the most code…

…but those who can design systems where AI, cloud, and product thinking work together.

💬 Your Turn

If you had this stack ready today:

What would you build?

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