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A Haystack pipeline can be perfectly wired and still unsafe. The retriever returns documents. Every component did its job. But if untrusted text moved through the pipeline as ordinary context, the trust boundary was lost. That is the problem this post is about. Not bad Python. A valid component connection only says: this value fits the next component It does not say: this value is safe to influen
Why Figma MCP Isn’t Enough Why Figma MCP Alone Can’t Guarantee Production-Ready UI — and What Product Teams Must Do Instead Extraordinary results require an extraordinary team. I’m surrounded by people who treat design and development like a mission. They are warriors in the tech trenches, and this win belongs to them. No fluff. No filler. Just the facts on how we shattered our veloci
Contè UI - A Dynamic CSS System for Advanced Styling. When CSS Frameworks Become Limiting — Meet Conté UI Traditional frameworks often lock you into predefined scales. Conté UI breaks these limits with a breakthrough approach to building modern UIs with fully dynamic values and intuitive class conventions. Faster, lighter, and more flexible than traditional frameworks. Released: May 1, 2026 https
If you spent any time on React Twitter or LinkedIn lately, you saw three names everywhere: shadcn/ui, Radix, and Base UI. People talk about them like they compete with each other, but they don't really. Let me explain what each one actually is, and when you should reach for which. Before we compare anything, you need this idea. A normal UI library like Bootstrap or Material UI gives you components
Strong image models can already produce polished game UI screenshots. The harder question is whether those screenshots are useful as production evidence. I tested six common game-screen cases two ways: a direct prompt baseline a controlled workflow using a screen brief, layout contract, style contract, IP/lookalike gate, locked prompt, review score, revision prompt, and implementation notes The si
Comparison: Haystack 2.0 vs. RAGatouille 0.3 for Building High-Accuracy RAG Pipelines for Developer Docs Retrieval-Augmented Generation (RAG) has become the standard for building LLM-powered tools that answer questions using private or domain-specific data. For developer documentation (dev docs) — which includes technical jargon, versioned APIs, code snippets, and structured reference material —