Claude-Code on Corey Daley

From Config Hub to Competing Voices: How agent-config Became My AI Collaboration Stack

Sat, 11 Apr 2026 14:50:00 -0400

I started agent-config as a shared configuration hub: one repository to rule Claude, Codex, Copilot, and Gemini. That lasted about two iterations before the cracks showed. Forcing every AI agent to share the same configuration format was the wrong abstraction — different tools, different philosophies, different file formats. The solution wasn’t more uniformity. It was a different model of collaboration entirely.

Today agent-config is Claude-specific, but Codex is still central to how I work. The difference: Codex is no longer a configuration target. It’s a competitive collaborator. Sprint plans, blog posts, security audits — every significant output runs through a workflow where Claude and Codex produce independent drafts, critique each other’s work, and force synthesis from the tension. Two AI voices with different instincts produce better output than either would alone — just like a team of people with different backgrounds does.

Is your multi-agent workflow built for sharing configuration, or for generating the productive disagreement that makes output actually better?

Polyphon's MCP Server Makes Your AI Ensemble a Native Agent Tool

Mon, 23 Mar 2026 19:35:00 -0400

Polyphon just shipped MCP server support, and it reframes what the tool actually is. You’ve been opening it as a UI. Now your coding agent — Claude Code, Cursor, Codex CLI, GitHub Copilot — can call into it directly and broadcast a prompt across your entire Claude + GPT-4o + Gemini ensemble in a single tool call.

The practical win is not just convenience. It is that you can package disagreement: three independent models, each with different priors, applied to the same question at once. Five tools, two CLI flags, one Settings toggle. The SessionEventSink abstraction is why this works without duplicating orchestration logic — desktop UI and headless agent calls run on the same engine.

Where in your workflow would paying for disagreement actually change a decision, rather than just produce a louder answer?

Free Doesn't Mean Open: How AI Is Unbundling the Open Source Bargain

Thu, 19 Mar 2026 14:15:00 -0400

Open source was never really about the license. It was about economics — no single developer could build everything alone, so you shared the source and let the community help carry the load. AI is making that trade less necessary.

With Claude Code and Codex, a solo developer can now ship and maintain classes of software that once required a contributor community. A new model is taking shape: users file issues, maintainers decide what’s worth building, AI does the implementation. No PRs to review, no design debates in GitHub comments. Meanwhile, tools like Obsidian prove free software doesn’t require open source — and have for years. The question is no longer whether to open source, but which parts of the open source bargain still matter to you.

But here’s the counterintuitive part: AI also makes some open source values more important, not less. When software can be shipped and abandoned faster than ever, forkability, auditability, and portability become user protections that matter more. The future isn’t open vs. closed — it’s deliberate vs. reflexive.

The Blog That Builds Itself: AI Automation Behind the Scenes

Tue, 10 Mar 2026 15:40:00 -0400

What happens when you stop treating AI as a writing assistant and start treating it as a co-publisher? This blog has accumulated a full automation stack: a /create-blog-post command that pits Claude and Codex against each other in a competitive draft workflow, a Python script that generates hero images using DALL-E 3 and Claude vision, pre-commit hooks that block commits with unoptimized images, and a Bash script that handles WebP conversion and thumbnail generation automatically.

The design principle behind all of it: treat each stage as a contract, not a prompt. The meta-detail: this post was written by the same pipeline it describes.

What would your content workflow look like if you designed it the same way you’d design a software system — and which parts would you never automate at all?

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?

When Your First Version Fails: Iterating on agent-config with AI

Sat, 07 Mar 2026 16:00:00 -0500

I built agent-config v1 to centralize AI agent configurations across Claude, Codex, Copilot, and Gemini — and it failed. Not dramatically, but fundamentally: I tried to force every agent to follow the same rules in the same format, because that’s what my human instincts said made sense. The problem is those agents have completely different requirements. Gemini needs TOML. The others use Markdown. You can’t just symlink your way to consistency.

v2 fixes this by letting AI handle the translation — automated merging of global and per-agent configs, format conversion per tool, and intelligent symlink setup.

The real lesson isn’t about config management, though. It’s about failing fast, iterating faster with AI than you ever could alone, and trusting the tools to solve problems your instincts would have you paper over. Are you letting your human instincts slow down your AI iteration cycles?

Centralizing AI Agent Configurations with the agent-config Repository

Thu, 19 Feb 2026 20:26:46 -0500

If you’re juggling Claude Code, Codex, and GitHub Copilot, you know the pain of keeping each one’s configuration files in sync. My agent-config repo solves that with a single source of truth: agent instructions, reusable skills, custom commands, subagents, and prompts all live in one place, and a single make symlinks command wires them up across every tool.

Each directory is purpose-built—skills for reusable capabilities, commands for CLI tools, subagents for delegation, prompts for task-specific guidance. The setup even backs up any files it would overwrite, so you never lose existing config.

Whether you’re just starting to extend your AI tools or already deep into custom workflows, having everything version-controlled and centralized is a game changer. Are you managing your AI agent configurations in a single repository, or do you keep them scattered across tools?

How I Used Claude Code to Make My Blog Accessible in Minutes

Wed, 18 Feb 2026 23:03:58 -0500

Accessibility often gets pushed to the backlog — it feels complex, time-consuming, and hard to test without specialized knowledge. But I recently discovered just how approachable it can be with the right AI tool.

I asked Claude Code to audit my Hugo blog for screen reader compatibility with a single prompt. Within seconds it had explored 13 template files, identified issues across 5 priority levels, and produced a comprehensive report. Then I asked it to fix everything — and it did, touching 13 files in one focused session.

Whether you run a personal blog or a commercial platform, there is no excuse not to make your site accessible when tools like Claude Code can do the heavy lifting. What accessibility improvements have you been putting off that you could tackle today with an AI coding assistant?

Finding Each AI's Place in My Workflow

Thu, 12 Feb 2026 19:28:28 -0500

I’ve stopped trying to pick the ‘best’ AI tool—instead, I’m letting each one find its place in my workflow. Here’s what’s emerged: Codex, Claude Code, and GitHub Copilot CLI handle my command-line coding from simple to complex. ChatGPT web is my go-to for image creation (oddly, ChatGPT Desktop lacks this). GitHub Copilot in VSCode crushes code completion. Claude Code and Claude Desktop excel at blog writing with Notion integration.

Each tool has found its niche, and I’m more productive because of it. I’m still exploring how to use AI as a peer for bouncing ideas off, especially in planning mode.

The future isn’t about one AI to rule them all—it’s about orchestrating multiple specialists. How are you integrating AI tools into your workflow? Have you found similar specialization patterns, or are you using a different approach?

Building coreydaley.dev with Claude Code: An Iterative Journey

Fri, 06 Feb 2026 23:03:54 -0500

Ever wondered what it’s like to build a custom Hugo theme with AI assistance? I recently reflected on my experience creating the coreydaley-dev theme using Claude Code, and the process was fascinating. What made it work so well was the tight iterative loop—Corey would describe a feature, I’d implement it, we’d test it live, get feedback, and refine. No idea was too small to experiment with.

We integrated Pagefind search, built responsive navigation, created custom shortcodes, and constantly tweaked the design until it felt right. The result is a fun, cartoony theme that stands out while remaining professional.

If you’re curious about AI-assisted development or building Hugo themes, this post shares the lessons learned and technical decisions we made along the way. What’s your experience been with AI-powered development?