ELBO Platform: AI-Powered Training for Critical Thinking and Communication Skills

Platform Overview
ELBO is a training platform designed to help users develop skills that AI cannot easily replicate: critical thinking, persuasion, negotiation, and public speaking. The platform was built using Claude Code over four months by a developer in Quebec, with Claude Code responsible for approximately 70% of the 96 components.
Technical Implementation
The platform integrates seven Claude capabilities:
- Argument analysis
- AI debate opponent
- Content generation
- Moderation
- Coaching feedback
- Debate scoring
- Translation across 11 languages
Core Training Features
ELBO provides AI-powered practice scenarios where users interact with AI opponents that:
- Listen to arguments and challenge logic
- Push back on weak points
- Provide real-time constructive feedback
- Adapt to user skill levels
Specific training scenarios include:
- Job interview preparation with tough AI interviewers
- Delivering bad news to employees with emotionally reactive AI
- Critical thinking practice where AI argues opposite positions
Platform Structure
ELBO organizes training into four distinct worlds:
- Public Arena: Open training for all users
- NOVA: Educational training environment
- APEX: Corporate training programs
- VOIX: Civic democracy and public speaking practice
All worlds connect through a unified profile system that tracks demonstrated skills rather than claimed abilities.
Access and Development
The platform is free to try without requiring an account at elbo.world. The developer built the platform solo using Claude Code and is available to discuss technical architecture or Claude development questions.
📖 Read the full source: r/ClaudeAI
👀 See Also

Claw Code Agent: Python Reimplementation of Claude Code Architecture for Local Models
Claw Code Agent is a Python reimplementation of the Claude Code agent architecture that runs with local open-source models through OpenAI-compatible backends like vLLM and Ollama, featuring tool calling, slash commands, and tiered permissions.

Implementing AI Checks with Continue for Source-Controlled PR Reviews
Continue integrates AI checks directly into your pull request workflow by using markdown files as source-controlled checks, visible through GitHub status checks.

altRAG: Replace Vector DB RAG with 2KB Pointer Files for AI Coding Agents
altRAG is a Python tool that replaces vector database RAG with lightweight pointer files. It scans Markdown/YAML skill files to create a 2KB skeleton file mapping sections to exact line numbers and byte offsets, allowing AI agents to read only needed sections instead of entire files.

Spectral: Capture App Traffic to Generate MCP Servers for OpenClaw Agents
Spectral is an open-source tool that captures traffic from any application, analyzes it with an LLM, and generates a working MCP server, allowing OpenClaw agents to call the app's real API directly instead of relying on browser automation.