Software Engineer & AI Enthusiast
11 posts in category "Best Practices"
Mailpit solved local email testing years ago. SMS testing never got the same treatment — most teams either disable SMS in dev or eat the Twilio bill. MessagePit is a fork of Ralph Slooten's Mailpit that adds a Twilio-compatible ingest endpoint, an SMS inbox, and signature validation, so your existing Twilio SDK can point at localhost during development and CI without sending a single real message.
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Most personal sites have two versions: the rendered page humans see, and the raw HTML machines read. CSS flexbox makes the sidebar appear left and the article appear right — but the source order tells a different story. Here's why that gap matters more than it used to, and three practical fixes any static site can adopt.
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A multi-agent sprint planning workflow ran against a simple Go REST API project and caught three critical security findings before a line of code was written — a logical contradiction in the auth design, a data model bug that would have broken token rotation, and a SQLite gotcha that silently disables foreign key enforcement under connection pooling. Here's what the full planning session produced, and why the review phases are where the value lives.
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Polyphon is now open source under Apache 2.0. The reason isn't contributor growth or community optics — it's that local-first AI software can't ask users to accept privacy and control claims on faith alone. Open source gives users two things: the ability to inspect the architecture and verify what the tool is actually doing, and a real exit if the project ever changes direction.
For decades, 'free software' and 'open source' were nearly synonymous — because building something worth sharing required a community. AI has dissolved that constraint. But the story isn't that open source is dying. It's that open source used to do five jobs at once, and AI is separating those threads. Some become less necessary. Others become more critical than ever.
AI agents can write code, fix bugs, and ship features — but who can be trusted to ship production software when most implementation is delegated? Meet the Agent Wrangler: the engineer who decomposes work, directs multiple agents, validates output, and owns the outcome. Deep technical foundations matter more than ever. The keyboard gets less important. Judgment gets everything.
Understanding how large language models actually work under the hood removes some of the wonder — but it also replaces irrational fear with informed clarity. AI isn't magic, it isn't plotting against us, and knowing why might just change how you think about your own brain.
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Accessibility is something every website owner should care about, yet it's easy to deprioritize. I asked Claude Code to audit my Hugo blog for screen reader compatibility and was amazed at both the depth of its findings and how quickly it fixed every issue — from missing skip-navigation links to unlabeled SVG icons to dynamic search results that screen readers couldn't detect.
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Is it ethical to use AI coding agents like GitHub Copilot and Claude Code to write open source contributions? This post explores both sides of the debate—from democratizing contributions and amplifying productivity to concerns about misrepresenting skills and undermining community trust. We examine when AI assistance crosses the line, what transparency means in practice, and what consequences, if any, should apply when developers build their reputation on AI-generated code they don't fully understand.
Learn how to build a custom search experience using Pagefind's API instead of its default UI. This technical deep-dive covers loading Pagefind as a JavaScript module, querying for JSON results, and rendering search results with custom HTML that matches your site's design system. Discover how to maintain visual consistency across post lists and search results, including proper date formatting, taxonomy chips, and seamless Hugo integration. Perfect for developers who want full control over their static site search UI while leveraging Pagefind's powerful indexing capabilities.
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Discover why AI-assisted development thrives on iteration rather than one-shot solutions. This post explores how to work effectively with GitHub Copilot and Claude by embracing refinement cycles, providing better context, and treating AI like a smart junior developer who needs guidance. Learn practical strategies for iterative prompting, understanding when the first response is good enough versus when to refine, and how to build better results through continuous collaboration rather than expecting perfection from initial attempts.
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