AI Tutorials

A practical AI engineering tutorials monorepo focused on real workflows, production trade-offs, and runnable local-first projects.

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Quick Start

Research Agent

cd topics/research-agent
make run

Codebase Documentation Agent

cd topics/codebase-doc-agent
make setup
make lab

What This Repo Focuses On

• Local-first, runnable AI tutorials
• Production-oriented architecture and implementation patterns
• Reusable utilities for LLM calls, logging, MCP, and tool abstractions
• Documentation-first project structure for easier scaling

Topics

• Research Agent
• Codebase Documentation Agent
• Multi-Agent Asyncio Job Copilot

Shared Libraries

libs/ai_core is intended for reusable utilities across projects:

• llm/: provider wrappers and model routing
• mcp/: MCP integration helpers
• tools/: shared tool abstractions
• logging/: consistent structured logging
• console/: terminal output helpers
• config/: settings and environment loading
• telemetry/: tracing and instrumentation hooks

Documentation

• Project docs: topics/<project>/docs/
• Standards: docs/standards/
• Architecture notes: docs/architecture/

Scaling Rules

1. Keep project-specific logic inside each topics/<project> directory.
2. Move shared code to libs/ai_core only when reused by 2+ projects.
3. Keep project README and docs current with runnable commands.
4. Avoid committing local virtualenv/cache artifacts.

License

MIT. See LICENSE.