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How to Build a Custom AI Code Reviewer using Gemini 3 Pro and Laravel

Apr 17, 2026

In 2026, manual code reviews are becoming the bottleneck of rapid development cycles. While tools like PHPStan catch syntax errors, they often miss architectural flaws or "smelly" logic. Enter Gemini 3 Pro—Google's most advanced reasoning model. By integrating it with the official Laravel AI SDK, you can build a custom reviewer that understands your team's specific coding standards and provides instant feedback.

Why Gemini 3 Pro for Code Reviews?

Unlike previous models, Gemini 3 Pro features "Deep Think" capabilities and a massive 1-million token context window. This allows the AI to analyze not just a single snippet, but your entire repository structure, ensuring that suggestions are contextually aware of your existing design patterns.

Prerequisites

Before we begin, ensure you have the following:

PHP 8.3+ and Laravel 13 installed.
A Google AI Studio API Key (Gemini 3 Pro).
The official Laravel AI package.

Step-by-Step Implementation

We will create a service that takes a code string, sends it to an AI Agent, and returns a structured JSON report.

Step 1: Install the Laravel AI SDK

Open your terminal and run the following command to install the official AI integration package:


composer require laravel/ai

Step 2: Configure your .env file

Add your Gemini credentials to your environment file to allow Laravel to communicate with Google's models.


GEMINI_API_KEY=your_actual_api_key_here
AI_DEFAULT_PROVIDER=gemini

Step 3: Create the Reviewer Agent

In Laravel 13, we use "Agents" to define AI behavior. Create a new agent using the Artisan command:


php artisan make:agent CodeReviewAgent

Now, open app/AI/Agents/CodeReviewAgent.php and define the system prompt to act as a Senior Developer.


<?php

namespace App\AI\Agents;

use Laravel\AI\Agent;

class CodeReviewAgent extends Agent
{
public function instructions(): string
{
return "You are a Senior Laravel Architect. Review the provided code for:
1. Security vulnerabilities (SQL injection, XSS).
2. Use of latest Laravel 13 features.
3. Performance bottlenecks.
Provide feedback in structured JSON format.";
}
}

Step 4: The Controller Logic

Create a controller to handle the code submission. This file will be app/Http/Controllers/ReviewController.php.


<?php

namespace App\Http\Controllers;

use App\AI\Agents\CodeReviewAgent;
use Illuminate\Http\Request;

class ReviewController extends Controller
{
public function __invoke(Request $request, CodeReviewAgent $agent)
{
$request->validate(['code' => 'required|string']);

    // Sending code to Gemini 3 Pro
    $review = $agent->prompt($request->code)
                    ->asJson()
                    ->send();

    return view('review.results', ['feedback' => $review]);
}
}

Step 5: Create the Frontend Interface

In resources/views/review/index.blade.php, create a simple form to paste the code.


<form action="/review" method="POST">
<h2>Paste your PHP/Laravel Code</h2>
<textarea name="code" class="code-editor"></textarea>
<button type="submit">Analyze with Gemini 3 Pro</button>
</form>

Step 6: Displaying AI Feedback with JavaScript

To make the results look professional, use a small script in your results view to highlight findings.


document.addEventListener('DOMContentLoaded', () => {
const feedback = JSON.parse(document.getElementById('ai-data').textContent);

console.log("AI Review Score:", feedback.quality_score);
// Logic to highlight code lines based on AI suggestions
});

Conclusion

By leveraging Gemini 3 Pro and the Laravel AI SDK, you’ve built a tool that does more than just find typos—it thinks like an architect. This custom reviewer can be hooked into your GitHub Actions to automatically comment on Pull Requests, ensuring that only high-quality code reaches your production branch.

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