Agentic AI · Engineering · CTO topics
What we learn in client engagements, what works and what doesn’t. Field reports, patterns, architecture decisions for engineering teams.
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Claude Code · Command Cheat Sheet
Every built-in slash command, grouped by purpose — with the one question that matters day to day: when do I reach for which?
Open article →Code was never the job
The senior-engineering reset in the age of agentic AI — ten shifts that define the next five years. With numbers, not hot takes.
Open article →How to actually build an AI agent
An agent is a loop, not an 8-step pipeline. Why the viral infographic shows a parts list — and what the real architecture is.
Open article →MCP Tunnels & Self-Hosted Sandboxes
From demo to proof of concept: run agents without handing your internal networks and data to the public cloud.
Open article →Obsidian as the brain of Claude
A Markdown vault becomes persistent memory — shared between Claude Desktop and Claude Code, versioned through Git, under compliance control.
Open article →Hello, blog · Why we're launching one now
Field reports from real engineering engagements — no generic AI content. We write about what we build at DANIC and which patterns hold up.
Open article →Agentic dev setup · 10-point checklist
What a 2026 engineering team should have nailed down in its IDE, CI and sandbox strategy before the first agent gets to write to main.
Open article →The AI market just inverted — May 2026
Anthropic overtakes OpenAI on private valuation and Q1 enterprise revenue share for the first time.
Open article →Pick the right memory for your AI agent
Three retrieval architectures. Three shapes of data. A decision guide for Vector RAG, Knowledge Graphs and Tabular/SQL memory.
Open article →Why agentic-coding agencies are the next lock-in
Faster delivery with AI — or a new lock-in? How proprietary agentic stacks and retainers echo the traditional agency model.
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Prefer step-by-step guides over articles? Browse the playbooks — beginner guides with 60+ prompts →