Making content easily discoverable for AI search engines is crucial for broader reach. Here's how we improved the accessibility of our tenant portfolio content.

The Goal

Our primary objective was to enable AI search engines to easily discover and consume tenant portfolio content. This involved providing machine-readable endpoints that expose content in a structured and easily parsable manner.

When dealing with multi-tenant applications, handling tenant removal gracefully is crucial for user experience and data integrity. This post discusses a strategy for tenant dissolution with a focus on minimizing disruption and providing users with options.

The Challenge

In a multi-tenant system, deleting a tenant can have significant implications for its users.

Introduction

When presenting data to users, accuracy and clarity are paramount. This post addresses a recent adjustment made to improve the transparency of data displayed within our application, specifically concerning aggregated statistics.

The Challenge of "Total" Counts

Initially, our application displayed aggregate counts of items, such as commits and code reviews, with the label

Managing resource quotas across multiple tenants can be challenging, especially when the need for manual overrides arises. This post explores how we refactored our token usage service to implement a tenant-centric quota system with support for manual adjustments.

The Challenge

Previously, our token quota management was user-based. This created inefficiencies when the context already provided

Introduction

Maintaining data consistency across distributed systems and applications often requires careful management of caches. Stale data in caches can lead to unexpected behavior and inconsistencies. We recently implemented several enhancements to our application's caching strategy, focusing on proactive invalidation to ensure data accuracy and prevent outdated information from impacting

During a recent update, we encountered an issue where partial failures during data synchronization could lead to data loss. This post details the problem and the solution implemented to ensure data integrity.

The Problem

Our application relies on synchronizing data from an external source. The synchronization process involves fetching and updating various data points.

Optimizing AI Token Usage Queries

We've recently refactored and optimized our AI token usage tracking to improve performance and maintainability. This involved extracting duplicated queries and enhancing user filtering.

The Changes

The primary focus was on improving the efficiency of retrieving daily and monthly tenant AI usage data. This was achieved through two key changes:

Introduction

In the realm of automated content creation, achieving variety and maintaining engagement are key challenges. This post explores a technique for enhancing the dynamism of auto-generated posts by introducing an element of randomization into the content selection process.

The Challenge: Monotony in Automated Content

Automatically generating posts can become repetitive if the

Introduction

This post explores several strategies for optimizing data access within an application, focusing on caching and query reduction techniques. Efficient data handling is crucial for maintaining performance, especially as application scale.

Caching Strategies

Caching is a fundamental technique for reducing database load and improving response times.

This post discusses a recent update to our post generation process, shifting from hardcoded sections to a more adaptable, example-driven approach.

The Old Approach

Previously, our post generation system rigidly enforced a predefined structure: Introduction, Development, Examples, and Conclusion. This inflexible format ignored the nuances and varied structures of different example posts,