When I first started working with multi-agent systems, I was fascinated by how independent agents coordinate with each other, how did independent entities communicate? Then I came across a 50-year-old mathematical framework of concurrent computation called Actor model. This blog I’ll walk you through how I built a multi-agent system using the Actor Model from scratch. Introduction This project implements a Multi-Agent System (MAS) designed to orchestrate multiple AI agents to solve complex, multi-step problems.

If you are planning to upgrade your Rails app, which has a lot of active development. Let’s say your current rails version of your app is 6.1.7 and you are planning to upgrade it to 7.1.1. The default upgrade strategy that most people use when updating their Rails apps is called the Long Running Branch strategy, which means creating a separate branch from the main, which provides a dedicated environment for developers to work on the upgrade.

Concurrency handling is an essential aspect of any multi-user application. For example, consider a situation where two users attempt to modify the same data fields in an application concurrently. In such cases, you must decide which update is valid and which one should be discarded, which is a pretty challenging task. This is where locking mechanisms come into play. Locking ensures that only one user can modify a resource at a time, preventing conflicts and maintaining data integrity.