Developer-Tools on Corey Daley

Catching Twilio SMS Locally: MessagePit Extends Mailpit

Mon, 27 Apr 2026 14:25:00 -0400

Most teams have a tidy local story for email and a weird one for SMS. Mailpit catches every transactional email in dev — clean web UI, nothing leaks. For SMS, the usual options are stub the Twilio client, disable sends in dev entirely, or eat the cost of real messages during CI runs. None of those are good.

MessagePit is a fork of Ralph Slooten’s Mailpit that closes the gap. It exposes a Twilio-compatible HTTP endpoint at the real /2010-04-01/Accounts/{AccountSid}/Messages.json shape, validates X-Twilio-Signature if you opt into it, and surfaces every captured SMS in the same web UI Mailpit ships for email. Point your Twilio SDK at http://localhost:1775 instead of api.twilio.com and the rest of your code stays exactly the same.

What other third-party integrations in your stack would get dramatically easier if you stopped mocking them and started catching them locally?

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?

Bring Your Own Key: Why Customers Are Tired of Paying Twice for AI

Sat, 07 Mar 2026 12:00:00 -0500

There’s a quiet frustration building across developer tools right now. You already pay $20/month for Claude Pro or ChatGPT Plus. Then your IDE wants another $10 for AI. Your project management tool wants $8 more. Your Git client wants its cut too. The bill isn’t for one AI — it’s for the same AI, billed by a dozen different gatekeepers.

The Bring Your Own Key (BYOK) model is the industry’s response: connect your existing API keys and skip the markup. But it’s not a clear-cut win. Managed AI subscriptions offer real value — simplicity, support, compliance, and no API wrangling.

The real question isn’t which model is better. It’s which model fits you — and whether the tools you’re using have even given you a choice. Have you audited how many separate AI subscriptions you’re paying for lately?

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?

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?

How GitKraken Simplified My Git Workflows and Boosted Productivity

Wed, 04 Feb 2026 12:05:00 -0500

Git is powerful but complex—until you add GitKraken. After years of command-line Git, switching to GitKraken completely transformed how I work. The interactive commit graph alone is worth it: complex branch structures become instantly clear, and you can navigate your entire repository history with simple clicks.

But it’s not just pretty visualization. GitKraken’s merge conflict resolution is intuitive, the built-in code review tools streamline collaboration, and integrations with GitHub, GitLab, and Bitbucket make everything seamless.

Whether you’re a Git beginner finding your footing or a pro looking to boost productivity, GitKraken removes the intimidation factor and makes version control visual and accessible. Have you tried visual Git clients? What’s been your experience with GitKraken or similar tools?