Claude on Corey Daley

Why I Left Notion and Built My Own AI Agent Plugin for Obsidian

Mon, 09 Mar 2026 11:45:00 -0400

I was already paying for Claude, Codex, and several other AI services when Notion started pushing its own AI add-on. The problem wasn’t just the price — it was that Notion AI couldn’t talk to any of the tools I already had, and my workflow had become a copy-paste treadmill between my notes and my agents. So I switched to Obsidian and hit the same wall: no native way to use your own AI.

I built the Obsidian AI Agent Sidebar plugin — an open source tool that brings Claude Code, OpenAI Codex, Google Gemini, GitHub Copilot, and any OpenAI-compatible server directly into your Obsidian sidebar, with real vault read/write access. Developed using agentic engineering and the dark factory method, it’s the integration I needed and couldn’t find.

What would you build if the tool you needed simply didn’t exist yet?

Automate Your Blog with Notion and AI: A Self-Demonstrating Workflow

Tue, 10 Feb 2026 21:41:59 -0500

This post you’re reading right now? It was created by an AI reading a to-do item from my Notion database. That’s the power of combining Notion with AI assistants. The problem every blogger faces: brilliant ideas die in the gap between inspiration and execution.

My solution: a Notion to-do list where I capture ideas, and AI assistants (Claude Code and ChatGPT) read from it via Model Context Protocol, generate complete posts, publish them to my Hugo blog, and mark the to-dos complete. It’s self-demonstrating—this very post was created that way. The workflow transforms content creation from manual drudgery into an automated pipeline.

If you’re drowning in blog ideas but low on execution energy, this might be your answer. Are you using Notion for content management? Have you explored AI integrations for your blog?

The Art of Iterative Cycles with AI: Why Your First Prompt is Never Your Best

Wed, 04 Feb 2026 19:50:00 -0500

Here’s something I’ve learned about AI coding assistants: the first response is rarely perfect—and that’s actually a good thing. When I started using GitHub Copilot and Claude, I expected instant perfect code. Reality? AI interprets your instructions based on patterns and context, so the first attempt is often close but not quite right.

The key is treating AI like a junior developer: start with clear instructions, review the result, provide feedback, and iterate. Each cycle gets closer to what you need. This isn’t a limitation—it’s how effective collaboration works.

The developers who succeed with AI aren’t the ones with perfect prompts; they’re the ones who embrace refinement. Have you experienced this iterative dance with AI tools? How many rounds does it usually take you to get the result you want?

Building with AI: Copilot and Claude

Tue, 03 Feb 2026 21:02:25 -0500

Building websites has changed dramatically—I’m no longer staring at code for hours. Instead, I’m collaborating with Claude and GitHub Copilot to build this Hugo blog. Here’s what I’ve learned: Claude is my architect. When I need structural changes or new layouts, Claude generates complete solutions and explains every decision.

GitHub Copilot is my coding assistant, finishing my thoughts as I type and handling routine tasks. Together, they create a powerful workflow where Claude handles the big picture and Copilot speeds up execution. The result? I spend less time debugging and more time creating.

If you’re curious about AI-assisted development or wondering which tool does what, this post breaks down how they complement each other. Are you using AI tools in your workflow? How do you divide the work?