#atom

Subtitle:

An all-in-one product analytics platform with LLM observability capabilities

Core Idea:

PostHog is a comprehensive product analytics platform that helps developers track usage, implement feature flags, and monitor LLM costs and performance across applications.

Key Principles:

1. All-in-One Platform:
   • Combines multiple product development tools (analytics, feature flags, experiments, LLM observability) in a single solution.
2. Developer-Focused:
   • Built specifically for engineering teams to implement and maintain without requiring dedicated data analysts.
3. Open Architecture:
   • Provides integrations with various AI providers through direct connections or via frameworks like Vercel AI SDK.

Why It Matters:

• Cost Transparency:
  • Prevents unexpected AI expenditures by tracking LLM usage costs in real-time.
• Resource Optimization:
  • Helps identify inefficient AI usage patterns and opportunities for cost reduction.
• Performance Monitoring:
  • Provides insights into LLM response times, error rates, and other performance metrics.

How to Implement:

1. Initial Setup:
   • Create a PostHog client and integrate it with your application.
2. API Integration:
   • For OpenAI, pass the PostHog client directly into the OpenAI constructor.
   • For other LLM providers, implement through wrappers like Vercel AI SDK's tracing function.
3. Custom Analytics:
   • Develop SQL queries within PostHog to analyze specific metrics not available out-of-the-box.

Example:

• Scenario:
  • Tracking Gemini API costs across an application.
• Application:

import { withTracing } from 'posthog-js';
import { generateObject } from '@vercel/ai';

// Wrap Vercel AI SDK functions with PostHog tracing
const generateWithTracking = withTracing(generateObject, {
  distinctId: userId,
  properties: {
    model: "gemini-2.0-flash",
    // Additional properties
  }
});

// Custom SQL query for cost calculation
// SELECT 
//   date_trunc('day', timestamp) as day,
//   sum(properties.$input_tokens) * 0.00001 as input_cost,
//   sum(properties.$output_tokens) * 0.00004 as output_cost
// FROM events
// WHERE event = 'ai_generation'
// GROUP BY day
    ```
    
- **Result**:
    - Accurate daily tracking of LLM usage costs, preventing surprise bills at month-end.

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### **Connections**:

- **Related Concepts**:
    - LLM Cost Tracking: PostHog provides specialized observability for LLM costs.
    - Vercel AI SDK: Common integration method for non-OpenAI models with PostHog.
- **Broader Concepts**:
    - Product Analytics: PostHog is a comprehensive platform in this space.
    - Feature Flagging: Another core capability of the PostHog platform.

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### **References**:

1. **Primary Source**:
    - PostHog Documentation (posthog.com)
2. **Additional Resources**:
    - "How to set up LLM analytics" tutorials on PostHog website
    - Vercel AI SDK documentation for integration methods

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### **Tags**:

#analytics #LLM #observability #costTracking #developerTools #productAnalytics #featureFlags

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**Connections:**
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**Sources:**
- From: Your Average Tech Bro - Cómo hago un seguimiento del uso de LLM en mis aplicaciones para no quedarme sin dinero