Context Engineering
Stale Context in AI Coding: When Yesterday's Knowledge Breaks Today's Code
Stale context causes AI coding bugs that look like hallucinations but aren't. Here's why it happens, why it's getting worse, and how to detect it.
Nicola·
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Context Engineering
Persistent Memory for AI Agents: Why Sessions Shouldn't Start from Zero
Every AI coding session starts blank. You re-explain the architecture, the constraints, the decisions. Here's what persistent memory changes and how it works.
Nicola·
Context Engineering
Your AI Coding Agent Reads Too Many Files — Here's the Fix
Without a code graph, AI agents navigate blind and read 15 files to answer a 3-file question. Here's why it happens and how graph-based context selection fixes it.
Nicola·
Context Engineering
How to Give Your AI Coding Agent Better Context (Automatically)
Your AI coding agent is only as good as the context it receives. Learn how CLAUDE.md files, memory dir, and graph-based retrieval to eliminate re-explanation overhead and boost first-attempt accuracy.
Nicola·
Context Engineering
The Token Waste Problem: 80% of AI Coding Tokens Are Irrelevant
Most AI coding sessions waste 80%+ of tokens on irrelevant context. Here’s why it happens, how it hurts cost and quality, and how dependency graphs fix it.
Nicola·
Context Engineering
Context Window Management for AI Coding: The Developer's Guide
Learn how AI context windows work, why long coding sessions degrade, and practical strategies and tools like vexp to keep Claude effective and costs low.
Nicola·
Context Engineering
What Is Context Engineering? Why It Matters More Than Prompt Engineering
Prompt engineering shapes intent; context engineering shapes what the model actually knows. For serious AI coding, context wins by a mile.
Nicola·
Context Engineering
Session Memory for AI Coding Agents: Why Your Agent Forgets
Why current AI coding agents forget your codebase between sessions, and how vexp’s session memory, staleness tracking, and cross-agent graph fix it.
Nicola·
Context Engineering
What Is a Dependency Graph for AI Coding? (And Why It Cuts Tokens by 63%)
AI coding agents waste tokens by loading hundreds of irrelevant files. Dependency graphs fix this with precise, structural context selection.
Nicola·