My job changed from watching the system to checking whether it is still doing what I expect. A tour of the three Mission Control tabs - Flow, Log, and Stats - plus stale cron detection, live architecture, and the moon-gravity Goblin.

A private assistant built into the ChatGPT app a customer already uses daily. No new app, no bot to learn. Per-task model routing across DeepSeek, Haiku and Terra puts 100 generated reports at about $2.00, with no vendor rate limits. Plus the vector database I deleted before building it.

I audited my own agent fleet and found that every report it sent me for two months was labeled with the wrong month. Real values pulled from a real file and attached to the wrong reality. What I built to fix it.

From pixel-art characters to a lean infrastructure dashboard - how I stripped down my Mission Control to only show what matters, let agents handle the work, and finally got a dashboard that reflects my actual infrastructure.

A pixel-art dashboard showing every AI agent working live - character sprites, server racks, live activity feeds, and customer support pipelines in action. Inspired by agent-town, Hermes Agent, and OpenClaw apps.

Six agents across two VPSs, 20+ automated pipelines, and a visual dashboard - all controlled from a single Telegram chat. The complete architecture: agents, services, infrastructure, pipelines, and design philosophy.

12 hours of non-stop agent work for $3. How Goblin orchestrates Ghoul across two VPSs - skills, commands, model routing, and watchdog scheduling without burning tokens.

How I built a multi-agent AI system on Hermes Agent that handles actor knowledge, monetization strategy, QA review, customer support drafts, and code builds - all from Telegram.

Stopping help desk impersonation with a low-code security bot built in a day using only what was already in the tenant -- Copilot Studio, Power Automate, Teams, and Entra ID.

Six months of agent deployment taught me about token economics, provider strategy, orchestration patterns, and why the playing field for building has fundamentally changed.

How a local Qdrant experiment became a cloud-hosted, x402-gated MCP server for AI agents.

How I moved from token-heavy planning workflows to a code-first approach using Claude Code, local RAG search, and intelligent model routing for 80% efficiency gains.

Why I stopped paying for premium AI subscriptions and switched to local models - and why you should too.

Building first, understanding as you go. How diving deep into RAG concepts - embeddings, vector spaces, and semantic similarity as geometry - is what actually unlocks building AI systems.

How I built a fully local RAG pipeline that indexes all my GitHub repos, embeds them with Ollama, stores vectors in Qdrant, and exposes semantic search through an MCP server -- no cloud APIs, no data leaving the machine.

How to setup your own VPN Server with Wireguard

How I built a token-aware chunking actor on Apify for RAG pipelines --- three splitting strategies, deterministic IDs, and zero API keys required.

How I built a translation skill that agents discover, call, and pay for -- no humans required.🦾

Plan to consolidate and take back control of you Email and Privacy

Part 2 reveals how a sloppy malware attempt failed due to poor execution and strong detection.

Real‑world RBCD breach: phishing entry, AD delegation abuse, detection queries, and hardening tips-all in a nutshell.

WEASEL Tools is my custom WSL2 setup that brings Linux efficiency and terminal superpowers to Windows 11. Built for speed, focus, and keyboard-driven productivity.

How I transformed a fresh Arch Linux install into a minimalist Hyprland desktop in 9 hours - Neovim, Waybar, and a fully keyboard-driven workflow.

Lessons learned building browser extensions for Chrome and Edge - Manifest V3, cross-browser compatibility, and navigating the store submission process.

How I applied the Zettelkasten method inside Obsidian to build a personal knowledge system - atomic notes, emergent structure, and my RatVault implementation.

Deep dive into Kusto Query Language - time series analysis, optimized joins, and building dynamic dashboards in Azure Log Analytics.