Essays on AI, engineering and Rails
Honest takes on code, AI, and what actually works
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Latest ·
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5–7 minutesThe Rise of Wasteful Resources
Read essay →: The Rise of Wasteful ResourcesWe used to be proud of making things small. Now the default is to throw more tokens, more context and more compute at every problem. Why AI waste became normal, what it really costs, and how to get the craft…
Recent essays
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The AI-Native Rails App: What a 2025 Architecture Looks Like
Introduction For the first time in decades of building products, I’m seeing a shift that feels bigger than mobile or cloud.AI-native architecture isn’t “AI added into the app” it’s the app shaped…
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The Two Hardest Problems in Software Development: Naming Things & Cache Invalidation
The post discusses the common struggles developers face with naming conventions and cache invalidation, humorously portraying them as universal challenges irrespective of experience or technology. It emphasizes that while AI and Ruby…
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PgVector for AI Memory in Production Applications
PgVector is a PostgreSQL extension designed to enhance memory in AI applications by storing and querying vector embeddings. This enables large language models (LLMs) to retrieve accurate information, personalize responses, and reduce…
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Saving Money With Embeddings in AI Memory Systems: Why Ruby on Rails is Perfect for LangChain
In the exploration of AI memory systems and embeddings, the author highlights the hidden costs in AI development, emphasizing token management. Leveraging Ruby on Rails streamlines the integration of LangChain for efficient…
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The SaaS Model Isn’t Dead, it’s Evolving Beyond the Hype of “Vibe Coding”
The article critiques the rise of “vibe coding,” emphasizing the distinction between quick prototypes and genuine MVPs. It argues that while AI can accelerate product development, true success relies on accountability, stability,…
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Artisanal Coding (職人コーディング): A Manifesto for the Next Era of Software Craftsmanship
Artesanal coding emphasizes the importance of craftsmanship in software development amidst the rise of AI and “vibe coding.” It advocates for intentional, quality-driven coding practices that foster deep understanding and connection to…
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Brainrot and the Slow Death of Code
The rise of AI tools in software development is leading to a decline in genuine coding skills, as developers increasingly rely on automation. This reliance dampens critical thinking and creativity, replacing depth…
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The Art of Reusability and Why AI Still Doesn’t Understand It
AI can generate code but lacks understanding of design intent, making it struggle with reusability. True reusability involves encoding shared ideas and understanding context, which AI cannot grasp. This leads to overgeneralized…
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The AI Detox Movement: Why Engineers Are Taking Back Their Code
In 2025, AI tools transformed coding but led developers to struggle with debugging and understanding their code. This sparked the concept of “AI detox,” a period where developers intentionally stop using AI…
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