From the Kite blog
Deep dives on multi-agent coordination, autonomous AI architecture, and building production MCP systems with Claude.
How I Built a Persistent Memory System for AI Agents (And What It Changed)
AI agents forget everything when the session ends. Here's the architecture I built to fix that: a vector search memory vault that auto-extracts knowledge from conversations and injects relevant context into every new session.
Claude Agent Architecture: How to Build Autonomous AI Agents That Don't Go Rogue
A concrete guide to Claude agent architecture with tool-use loops, human-in-the-loop approval gates, semantic memory, and task decomposition — the stack that makes autonomous AI agents safe to deploy.
Claude Code Solo vs. Multi-Agent: What 224 Completed Tasks Taught Me
A concrete comparison of raw Claude Code sessions versus orchestrated multi-agent Claude Code. Real numbers, real tradeoffs: 224 tasks completed, 515 pruned, 0 failures.
Claude Code Multi-Agent Systems: Coordinating AI Without the Chaos
A technical guide to building reliable Claude Code multi-agent systems with file locking, task queues, and conflict-free coordination using Unix sockets.
Autonomous AI Agent Architecture: The Stack That Makes Agents Self-Running
How to architect autonomous AI agents with persistent memory, heartbeat loops, and self-directed research cycles using Claude and the MCP protocol.
MCP Server Orchestration: Building Claude Tool Networks That Scale
A deep dive into Model Context Protocol server architecture — how to design, compose, and orchestrate MCP tools for production Claude agent systems.