AI Context Engineering
Technical articles on persistent AI context, semantic search, cross-IDE workflows, and making your AI coding tools actually remember what matters.
Why Your AI Coding Tools Forget Everything (And How to Fix It)
AI coding assistants lose context every session. Learn why context amnesia happens, how it costs developers hours per week, and what persistent context means for AI-assisted development.
What Is the Model Context Protocol (MCP)? A Developer's Guide
A technical guide to the Model Context Protocol (MCP) — the open standard enabling AI coding tools to communicate with external services. Learn how MCP works, which IDEs support it, and why it matters.
How Semantic Search Powers AI Memory: Vector Embeddings Explained
A technical deep-dive into how vector embeddings and semantic search enable AI tools to find past decisions by meaning, not keywords. Learn about 768-dimensional vectors, cosine similarity, and pgvector.
Cross-IDE Context Engineering: Making Your AI Tools Work Together
A practical guide to sharing context between Cursor, Claude Code, and Windsurf. Learn how context engineering bridges siloed AI tools with setup walkthroughs and real examples.
Swylink vs Built-in IDE Memory: Why Cross-Tool Context Matters
A comparison of Swylink with built-in memory in Cursor, Claude Code, Windsurf, and Copilot. Learn why siloed IDE memory fails for multi-tool workflows and how cross-tool context bridges the gap.