Claude-Code

A 2-post collection

Proactive Context Injection with Claude Code Hooks

By Matthew Hunter |  Mar 24, 2026  | claude-code, mcp, memstore

Claude Code sessions start with amnesia. Every conversation begins cold — no memory of what you worked on yesterday, what invariants matter in the file you’re about to edit, or what tasks are still pending from last week. CLAUDE.md helps by injecting static project context, and MCP tools let the model search for facts on demand. But both of those require something to go right first: either the static file happens to cover the relevant topic, or the model decides to search before acting. In practice, the model often doesn’t search. It plows ahead with what it has, and the most valuable context — the constraint you documented last Tuesday, the task you left half-finished — stays in the database unsurfaced. This post is about closing that gap with hooks: small scripts that fire at specific points in the Claude Code lifecycle and inject relevant context automatically, before the model even knows it needs it.

Building Persistent Memory for AI Agents

By Matthew Hunter |  Mar 23, 2026  | memstore, mcp, claude-code, sqlite

AI coding assistants are goldfish with a PhD. They can solve complex problems within a single session — refactoring a module, debugging a race condition, designing an API — but the moment the conversation ends, everything they learned about your project evaporates. After months of building software with Claude Code, I found myself re-explaining the same project conventions, the same architectural decisions, the same mistakes we’d already caught and fixed, at the start of every session. CLAUDE.md files help, but they’re static and they don’t scale. You can’t stuff a dozen projects’ worth of design context into a single markdown file. So I built memstore: a persistent memory system that gives AI agents durable, searchable knowledge across sessions, projects, and machines.

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