33 stories
Hermes + Claude Code + Telegram on a cheap always-on thin client. Hi, I'm Amir 👋 I'm a DevOps engineer, and a surprising amount of my time goes into work that is important but repetitive. A server needs patching. A CI/CD pipeline fails. A script needs a small change.
A facilities coordinator in Dubai types a sentence into a company support portal: the checkout page keeps timing out near month-end. That sentence is about to be read by a system with access to your codebase.
For the past few weeks I've been building Aegis-DevOps, an open-source check that sits in front of the shell commands an AI coding agent runs. Before Claude Code, Codex, Copilot, Cursor or Gemini CLI runs kubectl, terraform or aws, a hook hands the command to Aegis, and Aegis blocks it if your…
Launching five agents on one large issue does not create five independent units of progress. If all five edit the same module, interpret the same vague requirement, and compete for one integration decision, the team may have created a queue of conflicting patches.
Every component worked to spec. The system broke anyway. I run a fleet of AI agents at home: several machines, a shared knowledge base in Obsidian, Syncthing keeping it all in one shape. Last week the fleet started getting dumber.
MLOps Best Practices 2026 This article explores key concepts and practical implementations. Overview Detailed content coming soon. Published by Engr. Hamza, AI & MLOps Engineer
I’ve spent the last few months building projects instead of just following tutorials. And honestly, I’ve learned something important: Building a real project teaches you things that tutorials simply can’t.
When we look at modern manufacturing plants and semiconductor fabrication cleanrooms from the outside, we see automated machinery running smoothly. But under the hood, engineering teams deal with massive distributed systems challenges: thousands of edge sensors, high-frequency RFID/BLE tracking,…
Beyond Basic MLM Software: What Delhi Businesses Need for Faster and Smarter Network Growth For many direct selling and network marketing businesses in Delhi, basic MLM software may be enough during the early stage of operations.
When people hear MVP development services, they often think it's just about building a basic version of an app. In reality, a good MVP is about answering one question: Will people actually use and pay for this product?
Every ticket on our board gets its own stack: a branch in every repo, its own services, its own copy of the dev database and its own preview URL. We built it because coding agents made my developers faster, and the mistakes moved out of the code and into the branches around it.
Step-by-Step Walkthrough: Building a 30-Day Autopilot Video Queue on Shadow 1. The Core Bottleneck Most creators hit the same wall by week three. They script, render, caption, schedule, then repeat. The bottleneck is not creativity.
You know the feeling. Pager goes off at 2 AM. You stumble to your laptop, open the terminal, and stare at a PostgreSQL stack trace you've seen before — but can't remember exactly what fixed it last time. You dig through Slack threads, closed Jira tickets, and a half-finished runbook.
The useful part of a deployment agent isn't telling me what a PostgreSQL upgrade is. It's remembering what happened the last time I tried one. That became the central idea behind DeployMind, a DevOps pipeline agent I built around Hindsight.
I built an incident-diagnosis agent that remembers every outage we've resolved. The interesting part isn't the diagnosis. It is the persistence boundary I ended up drawing, and how much of the system's value lives on one side of it.
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