Claude Code understands one repo at a time. Most teams have thirty. Microservices, shared libraries, infrastructure-as-code, frontend apps, data pipelines, all in separate git repos. Start Claude Code in one and ask about another, and it has no context. It doesn’t know the workspace exists. Here’s how I’ve been setting...

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Production agentic systems decompose problems and use the right tool for each step. Most developers hand the AI the whole problem. That’s the gap. Teams building production AI workflows have developed patterns for making AI reliable. Developers using AI coding assistants like Claude Code, Cursor, or Copilot mostly haven’t adopted...

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Developers using AI estimate they’re 24% faster. A randomised controlled trial measured them at 19% slower. That’s from METR’s 2025 study. These were experienced open-source developers working on their own codebases with tools they chose. Their self-assessment was off by over 40 percentage points. If your perception of AI’s impact...

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Principles are easy. Application is hard. I’ve written about intelligent Engineering principles and the skills needed to build with AI. But I kept getting the same question: “How do I actually set this up on a real project?” This post answers that question. I’ll walk through the complete setup, using...

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Principles are useful, but they don’t tell you what to practice. In my previous post on intelligent Engineering principles, I outlined the ideas that guide how I build software with AI. Since then, I’ve had people ask: “Where do I start? What skills should I build first?” This post answers...

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Same model, different tools, different results. If you’ve used Claude Sonnet in Claude Code, Cursor, Copilot, and Windsurf, you’ve noticed this. The model is identical, but the behavior varies. This isn’t magic. It’s context engineering.

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Software engineering is changing. Again. I’ve spent the last two years applying AI across prototyping, internal tools, production systems, and team workflows. I’ve watched it produce an elegant solution in seconds, then confidently generate code calling APIs that don’t exist. I’ve seen it save hours on boilerplate and cost hours...

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