The Multiverse School

- How to automate the entire SDLC with AI agents - Techniques for making AI agents feel natural in your workflow - Moving beyond test generation to full process automation - Strategies for shipping well-tuned processes instead of org charts - How to avoid common pitfalls when integrating AI into development

- Working Meshtastic mesh network (bring a friend or multiple nodes - mesh networking requires 2+ devices) - Local WiFi-hosted information hub - Solar-powered field node prototype - Resilience blueprint for scaling from garden to commune to neighborhood **Note:** Building a mesh network requires multiple nodes. We recommend either bringing a friend to the workshop or purchasing 2+ Meshtastic devices.

You'll learn to build prompts and agentic applications with Python, master context engineering techniques, and develop advanced AI integration skills for technical applications.

You'll build AI-powered business workflows including email triage automation, calendar/task management, data processing pipelines, and complete business automation systems. No coding required - learn to use AI and no-code tools to handle repetitive business tasks.

- How to build agents using the ReACT pattern (Reason, Act, Observe) - Request-response agents with Claude Agent SDK and OpenAI Agents SDK - RAG implementation with FAISS and pgvector for retrieval - Building your own minimal agent framework (~140 lines of code) - Multi-agent coordination patterns (sequential, parallel, hierarchical) - Framework comparison: Autogen, LangGraph, OpenAI Swarm - When to use agents vs. simple prompts and common pitfalls