Project

I’m excited to announce that Inboxer, a small Obsidian plugin I created for my own workflow, is now available in Obsidian through Community Plugins. As an ML engineer, I spend a lot of time in Obsidian managing research notes, and I kept running into an annoying workflow issue. The Problem I’d found there was a lot of friction when trying to add details to a note, say a project or an idea, in a structured way. I’m in the habit of keeping an ‘INBOX’ heading where I can append random thoughts, links, websites etc, and for projects a ‘TIMELINE’ heading to record events and progress. It became annoying switching to a note, finding the heading and adding a subheading whenever I had new information. Context switching kills my flow, and those small interruptions add up. ...

I’ve been investigating multi-agent systems and their applications in development workflows. After reading Anthropic’s recent guide to agent coordination patterns, I wanted to experiment beyond established patterns like Evaluator-optimizer and Orchestrator-worker workflows. For this exploration, I’ve chosen automated code review as a sufficiently complex problem domain. I’m building a multi-agent system structured according to the Viable System Model (VSM) – a cybernetics framework that provides an elegant organizational structure for complex systems. This post explores how VSM can serve as a foundation for implementing a multi-agent code review system that’s both effective and adaptive. ...

TL;DR This is a quick write-up of RetentionCast, a system I built to predict customer churn in real-time using Change Data Capture. The system processes live transaction data through Kafka and Debezium to calculate churn probability and Customer Lifetime Value. Check out the GitHub repo The Churn Problem If you’ve worked in e-commerce or SaaS, you know customer churn is the silent killer of growth. Traditional approaches to churn prediction often involve batch processing - running models overnight on yesterday’s data. But by the time you’ve identified that a customer is at risk, they might already be gone. ...