Build Your AI Agent Team with Claude Code Sub Agents скачать в хорошем качестве

Build Your AI Agent Team with Claude Code Sub Agents

I've built a fully autonomous AI agent team using Claude Code's new subagent architecture. This isn't just another AI tool - it's a command-line system that lets multiple specialised agents work together in parallel. This is the next BIG opportunity for building AI growth systems (sales & marketing) and wider, as it can really used to build any agent team. Here's what I'll cover this video: → Multi-Agent Architecture: Build primary agents that delegate to specialized subagents, create parallel workflows with separate context windows, implement autonomous decision-making systems - all through natural language commands. → Content Creation System: Research trending topics using Apify LinkedIn scraper, analyze top-performing posts automatically, generate content in your exact writing style, create matching images with Fal AI integration. → Autonomous Workflows: Set up agents that work without supervision, program specific workflows for consistent results, access any API or MCP integration directly, scale operations across multiple tasks simultaneously. → Real Implementation: Watch me build a complete LinkedIn content agent live, see the exact prompts and structure needed, understand how to train agents on your data, learn to connect multiple tools seamlessly. Everything runs autonomously once configured - imagine having an AI team that never stops working. 📌 Join the Community: https://www.ghostteam.ai/community 📩 Newsletter: https://elliotgarreffa.beehiiv.com/ Follow for More AI Content: ➡️ LinkedIn: /elliotgarreffa ➡️ X: https://x.com/elliot_garreffa ➡️ TikTok: /elliotagarreffa ➡️ Instagram: /elliotagarreffa Timestamps 00:00 – Intro: Claude Code Subagents overview 00:42 – Understanding the agent architecture 02:15 – Primary agents vs subagents explained 03:30 – Building a LinkedIn content agent system 04:45 – Research agent with Apify & Perplexity 06:20 – Content creator agent with training data 07:35 – Image generator integration 08:50 – Live demo: Creating content autonomously 15:30 – Reviewing generated research 17:45 – Content output and image generation 19:20 – Workflow sequencing and automation 21:00 – Use cases and future possibilities 22:30 – Getting started with your own agents