Tag: context-engineering
All the articles with the tag "context-engineering".
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The Great Agent Tooling Debate
Load 84 MCP tools and 15,540 tokens are gone before you ask a question; after thirty minutes you've burned 40% of your context on tool definitions you didn't use. Holmes and Yilmaz make the case for CLI-first, and I've mostly come round: CLIs are debuggable, composable, and 92-98% cheaper in tokens. MCP still earns its keep for a few tools, but the default should flip.
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Surviving the Context Window in Practice
The context window is a budget, not a feature. Auto-compaction hides the bill until the agent starts hallucinating. Practical tactics for staying under budget: scope per session, offload to disk, dispatch subagents for research, and clear aggressively between phases. The goal isn't a bigger window; it's needing less of it.
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Context Engineering: The Skill That Replaced Prompt Engineering
Your prompt is 0.1% of what the model sees; the other 99.9% is context engineering. A four-layer framework for thinking about prompts, practical guidance on what belongs in context and what doesn't, the invisible context problem from a million-line codebase, and why agent-controlled retrieval beats RAG for cross-file reasoning.
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Building Agent Memory That Survives Between Sessions
Every Claude Code session starts from scratch. Teresa Torres's three-layer context system and Patrick Zandl's claudecode-kb offer two practical approaches to the same insight -- memory is a design problem, not a tooling problem. The key habit is stop and capture, turning every repeated explanation into a reusable context file.
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The One File That Makes or Breaks Your AI Workflow
CLAUDE.md is the single file that determines whether your AI coding agent shines or flounders. Research shows auto-generated context files hurt performance — what works is a minimal, human-curated briefing containing only what the agent cannot discover on its own.