Sidekick: Technical Case Study

Introduction

Sidekick is a comprehensive AI productivity suite that combines multiple AI capabilities into a single, user-friendly platform. This case study explores the agent architecture, multi-modal AI integration, and real-time processing challenges.

Tech Stack Deep Dive

AI Agent Architecture

We built a modular agent system where each agent specializes in a specific task:

interface Agent {
  name: string;
  capabilities: string[];
  process(input: AgentInput): Promise<AgentOutput>;
}

class ChatAgent implements Agent {
  name = 'chat';
  capabilities = ['conversation', 'question-answering'];
  
  async process(input: AgentInput): Promise<AgentOutput> {
    const response = await this.llm.generate(input.message);
    return { type: 'text', content: response };
  }
}

class ScreenTutorAgent implements Agent {
  name = 'screen-tutor';
  capabilities = ['screen-analysis', 'guidance'];
  
  async process(input: AgentInput): Promise<AgentOutput> {
    const screenshot = await this.captureScreen();
    const analysis = await this.analyzeScreen(screenshot);
    return this.generateGuidance(analysis);
  }
}

Multi-Modal AI Integration

Sidekick integrates multiple AI models:

1. Language Models: For chat and text generation (GPT-4, Claude)
2. Vision Models: For screen analysis and image understanding
3. Image Generation: For creating images from text prompts
4. Video Generation: For creating short video content

class MultiModalProcessor {
  async processRequest(request: UserRequest) {
    if (request.type === 'image') {
      return await this.imageModel.generate(request.prompt);
    } else if (request.type === 'video') {
      return await this.videoModel.generate(request.prompt);
    } else if (request.type === 'screen-help') {
      return await this.visionModel.analyze(request.screenshot);
    }
  }
}

Real-time Screen Sharing

Implementing screen sharing with real-time guidance required:

import { ScreenCapture } from 'screen-capture-api';

class ScreenTutorService {
  private capture: ScreenCapture;
  
  async startSession(userId: string) {
    this.capture = new ScreenCapture({
      frameRate: 2, // 2 FPS for efficiency
      quality: 0.7
    });
    
    this.capture.on('frame', async (frame) => {
      const analysis = await this.analyzeFrame(frame);
      this.sendGuidance(userId, analysis);
    });
  }
  
  async analyzeFrame(frame: ImageData) {
    // Use vision model to understand screen content
    const result = await this.visionModel.analyze(frame);
    return this.generateInstructions(result);
  }
}

Challenges & Solutions

Challenge 1: Agent Orchestration

Problem: Coordinating multiple AI agents to work together on complex tasks.

Solution: We implemented a task decomposition system where a master agent breaks down complex requests into subtasks and delegates to specialized agents.

class MasterAgent {
  async handleRequest(request: UserRequest) {
    const plan = await this.createPlan(request);
    
    for (const task of plan.tasks) {
      const agent = this.selectAgent(task);
      const result = await agent.process(task);
      plan.results.push(result);
    }
    
    return this.synthesizeResults(plan.results);
  }
}

Challenge 2: Latency Optimization

Problem: Real-time screen analysis requires low latency, but AI models can be slow.

Solution: We implemented a multi-tier approach:

• Fast local models for simple tasks
• Cloud models for complex analysis
• Caching of common screen patterns
• Progressive enhancement (show quick results, refine later)

Use Cases & Impact

Sidekick has enabled users to:

• Get instant help with computer tasks through screen sharing
• Generate images and videos for creative projects
• Have natural conversations with AI assistants
• Learn complex software through guided tutorials

The platform processes over 1 million AI requests monthly with an average response time of 2.3 seconds.

class MasterAgent {
  async handleRequest(request: UserRequest) {
    const plan = await this.createPlan(request);
    for (const task of plan.tasks) {
      const agent = this.selectAgent(task);
      const result = await agent.process(task);
    }
    return this.synthesizeResults(plan.results);
  }
}