Your roadmap to real skills.

Low-Code Platforms Overview: LangFlow, Flowise, Dify, Relevance AI

Compare the four major low-code agent platforms and choose the right one for your use case based on hosting needs, features, and technical depth.

LangFlow: Visual LangChain Workflow Builder

Set up LangFlow, build a RAG pipeline visually, connect memory and tools, and run a multi-turn conversational agent, all from the drag-and-drop UI.

Flowise: Self-Hosted Open-Source Agent Platform

Deploy Flowise locally or on a VPS, build a document Q&A agent, integrate a vector store, and expose your agent via a REST API or embeddable chat widget.

Dify: Prompt IDE + Workflow Orchestration

Use Dify's prompt editor and workflow canvas to build multi-step AI pipelines, manage prompt versions, evaluate outputs, and integrate external API tools.

Relevance AI: Agent Teams Without Infrastructure

Build a team of specialised AI agents in Relevance AI that collaborate on complex tasks: assigning roles, sharing context, and producing a unified output.

Memory, Tools, and RAG in Low-Code Agents

Add persistent memory, web search, code execution, and document retrieval to low-code agents using built-in connectors and vector store integrations.

Self-Host Flowise via Docker on a VPS

Run Flowise locally with Docker Compose, then deploy to Railway (or equivalent) with a public URL.

RAG Pipeline Design: Chunking, Embeddings, Vector Stores

Design a Retrieval-Augmented Generation pipeline end-to-end and measure retrieval quality with precision@5.

Low-Code Agent Capstone: Production-Ready Agent Pipeline

Build a fully featured agent pipeline that ingests documents, answers questions, calls external APIs, and exposes a polished interface, using your platform of choice.

Low-Code Agent Job Readiness

Translate low-code agent skills into a resume, portfolio plan, and interview prep for AI builder / consultant roles.