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AI Insights & Tutorials Practical guides on MCP, tool routing, and cutting your LLM costs in production.
All (8) AI AI Agents AI Architecture AI Infrastructure Agentic AI Anthropic Architecture Benchmark Best Practices Claude Cost Optimization Dashboard Getting Started LLM MCP Token Cost Tool Architecture Tool Retrieval Tool Routing Tutorial
512K lines of production AI agent code: a rare opportunity. Five lessons from the Claude Code leak that should shape how you build AI agents.
The Anthropic leak is a blueprint for how production AI agents handle tools. We built the same system with one key change: retrieve first, inject second.
The Anthropic leak exposed Claude Code's 29,000-line tool definition. Here's the engineering problem this reveals — and why it doesn't scale.
From account creation to your first tool retrieval call — a step-by-step guide to the Agent-CoreX dashboard, MCP marketplace, and retrieval API.
Tool definitions are expensive at scale. Benchmark: traditional tool loading vs Agent-CoreX's semantic retrieval, using data from the Anthropic leak.
Claude Code's 512K-line agentic harness was accidentally leaked. Here's what the TypeScript codebase reveals about how production AI agents work.
Learn how to browse, install, and connect MCP servers using the Agent-CoreX dashboard — then call Claude with only the tools it actually needs.
Every tool definition costs tokens. Learn how Agent-CoreX's retrieve_tools API cuts waste by selecting only the tools relevant to each query.
512K lines of production AI agent code: a rare opportunity. Five lessons from the Claude Code leak that should shape how you build AI agents.
The Anthropic leak is a blueprint for how production AI agents handle tools. We built the same system with one key change: retrieve first, inject second.
The Anthropic leak exposed Claude Code's 29,000-line tool definition. Here's the engineering problem this reveals — and why it doesn't scale.
From account creation to your first tool retrieval call — a step-by-step guide to the Agent-CoreX dashboard, MCP marketplace, and retrieval API.
Tool definitions are expensive at scale. Benchmark: traditional tool loading vs Agent-CoreX's semantic retrieval, using data from the Anthropic leak.
Claude Code's 512K-line agentic harness was accidentally leaked. Here's what the TypeScript codebase reveals about how production AI agents work.
Learn how to browse, install, and connect MCP servers using the Agent-CoreX dashboard — then call Claude with only the tools it actually needs.
Every tool definition costs tokens. Learn how Agent-CoreX's retrieve_tools API cuts waste by selecting only the tools relevant to each query.