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From Vibes to Durable Context
AI can speed up implementation, but it does not remove the need for good engineering. This article looks at how planning, human judgment, useful documentation, and a well-structured codebase can help coding agents make better decisions with less guesswork.
·4 min readarticle
Where AI Actually Helps Quality Engineering
AI-assisted QA is not just about generating tests faster. By carrying product context through planning, development, review and release, AI can shorten feedback loops, surface risks earlier and help teams make better decisions, provided its output is supported by clear specifications, guardrails and human judgement.
·3 min read
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Is Your Design System Ready for AI?
AI can generate convincing interfaces, but it struggles when a design system’s decisions live in team knowledge rather than its components, documentation and defaults. Preparing a design system for AI means making those decisions discoverable, explicit and verifiable.
·6 min readBuild vs buy: AI code review for teams that have opinions
There’s a good chance that somewhere in your org, someone is trialling an AI code review tool right now, and at the same time someone else is pasting agent output into PRs under their own name.
·6 min readOptimise Your Context, Not Your Prompts
AI makes better engineering decisions when it can understand a project’s architecture, conventions and shared knowledge. Making that context clear and discoverable helps it produce software that fits the wider system.
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