Improving the auditability of AI interactions is crucial for maintaining security and control. A recent update focuses on preventing the exposure of raw code to AI models, enhancing data security, and providing better insights into flagged code changes.

The Challenge of Raw Diffs

Previously, raw git diffs were sent to AI models for analysis. This approach, while providing detailed context,

Introduction

Ensuring application stability and দ্রুত problem resolution hinges on effective error logging. Silent catch blocks, while seemingly benign, can mask critical failures, making them invisible to monitoring systems. This post outlines a strategy for replacing these silent catch blocks with proper logging mechanisms, enhancing overall application observability.

The Problem with

Introduction

Effective logging is crucial for monitoring and debugging applications, especially in multi-tenant environments. This post explores how to enhance application logging by incorporating tenant-specific context, enabling better isolation and analysis of log data.

The Importance of Tenant-Aware Logging

In a multi-tenant system, logs from different tenants are often interleaved,