The tools you actually need, and the ones you don’t.
A curated guide to the platforms, frameworks, and infrastructure that make AI deployments work in practice.
Tool Guides
- n8n — Workflow automation and AI agent orchestration
- Ollama — Local open-source LLM serving
- vLLM — Production-scale inference
- Zapier — No-code automation; cloud-only, per-task pricing
- Open WebUI — Browser chat interface for self-hosted LLMs
- LiteLLM — Unified API gateway with fallback and cost routing
- Langfuse — LLM observability, cost tracking, and evaluation
- Flowise — Low-code agent builder for RAG pipelines and multi-agent workflows
Core Concepts
- Self-Hosted AI — When to run models on your own hardware
- Vector Databases — The storage layer for retrieval
- MCP — The protocol for tool connections
Layer Hubs
- Integration Layer — MCP, APIs, workflow tools
- Infrastructure Layer — Self-hosting vs cloud
Each tool guide will include: what it does, what it costs, where it breaks, and how to recover.