Blog
Articles, insights, and deep dives from the Arcanada team.
AI Agent Model Connector Benchmark: CLI Subscriptions vs API Providers
I benchmarked 20 AI models across 5 connectors. CLI tools score 100% accuracy but are forced to run sequentially — 20x slower than parallel API calls. Here are the numbers, the architectural tradeoffs, and my decision for the Arcanada ecosystem.
Scrutator: Building the Knowledge Engine Behind Arcanada
We built Scrutator — an open-source search, retrieval, and meaning engine. Dense + sparse + ColBERT embeddings, hybrid search, and a Dreaming module that reorganizes knowledge while you sleep. All five layers are live in production.
How I Picked an Embedding Model for Arcanada
Benchmarked 7 multilingual embedding models on CPU, no GPU. bge-m3 won with 0.887 cross-lingual similarity — 45% higher than the nearest competitor. Here's the full breakdown.
Datarim: Do Agents Dream of Electric Sheep?
AI agents can write code. They can't run projects. Datarim is an open-source framework with 15 agents, 18 skills, and a 9-stage pipeline that gives AI agents project execution structure. 1,000+ tasks closed in one year by one person.
Claude Code Memory Optimization: Auto Memory, Auto Dream, and the Bugs Documentation Doesn't Mention
Claude Code has a problem you'll only discover after 20-30 sessions: its memory degrades. Here's how Auto Dream is supposed to fix it — and why the /dream command doesn't actually work.
Introducing Arcanada: A Comprehensive AI Agent Ecosystem
We are thrilled to announce the official launch of Arcanada — a comprehensive ecosystem for building, orchestrating, and scaling AI agents and swarms.
6 Local LLMs as Claude Code Backend: Why 4 Out of 6 Fail
Every model writes working code. Every model passes tests. But when you plug them into Claude Code as an agent backend — 4 out of 6 break.
Claude Code: Myths & Secrets from the Source Code
I fact-checked the most popular Claude Code "hacks" against the actual source code. Half are myths. Some actively break functionality.