Ai-Agents on Corey Daley

The Rise of the Agent Wrangler

Tue, 10 Mar 2026 11:55:00 -0400

People keep asking if AI is going to replace software engineers. Better question: who can still be trusted to ship production software when most implementation is delegated to agents? That role is the Agent Wrangler — and it isn’t a step down from engineering, it’s a different kind of engineering.

You spend your day directing Claude Code, Codex, and similar tools through feature work, bug hunts, security audits, and codebase exploration. The job sounds easier than traditional engineering. It isn’t — at least not for the people who do it well. Because when you’re orchestrating agents, your technical depth is the control surface. CS fundamentals don’t disappear; they become the language you use to catch when an agent is wrong.

Software engineers aren’t going away. They need to adapt — like they always have. Maybe the real new title is ‘Adaptability Engineer.’ Are you ready to stop coding and start wrangling?

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?

Attractor: When Chaos Theory Meets AI Pipeline Orchestration

Fri, 06 Mar 2026 12:00:00 -0500

Most AI automation breaks for the same reason: the workflow is hidden inside scripts, prompts, and tribal knowledge. Attractor takes a different path — one borrowed from chaos theory. In dynamical systems, an attractor is a state a system naturally converges toward even through turbulence.

Apply that to AI workflows, and you get directed graphs that pull multi-LLM execution through branching, retries, human review gates, and failure recovery toward a defined goal. The entire codebase is AI-generated, which makes it a working proof-of-concept of the Software Factory philosophy.

If we can declaratively orchestrate AI agents today, what should we still insist on owning as humans?

Beyond LeetCode: How AI is Transforming Technical Interviews

Sun, 15 Feb 2026 17:46:25 -0500

The coding interview landscape is shifting dramatically as AI tools become standard in software development. Rather than memorizing algorithms, candidates may soon demonstrate their ability to work effectively with AI agents—breaking down projects, creating tasks in Jira, and collaborating to solve real-world problems.

This shift raises important questions about what skills truly matter and how we evaluate engineering talent in an AI-augmented world.

What does this mean for the future of technical hiring?