Learning Layer
Four tracks, real build source.
No 16-course catalog. The first Academy surface stays narrow: coding workflow, agent systems, operating workflows, and public build systems.
How we actually use Claude Code to build AI-native products, debug production issues, ship with GitHub + Vercel, and turn coding agents into a real operating workflow.
- 01Why Claude Code matters for AI-native builders
- 02Local dev workflow: from idea to working project
- 03GitHub + Vercel: shipping without friction
- 04Context overflow and how to control it
- 05Multi-agent coding workflow
- 06Debugging AI-generated code
- 07Claude + OpenRouter workflow
- 08Real build teardown: OPCEO / Makox / Nomiluo
A practical introduction to designing agent systems that do real work - main agents, subagents, routing, delegation, memory, and failure recovery.
- 01Agent is not chatbot
- 02Main Agent / SubAgent architecture
- 03Routing and delegation
- 04Memory layer basics
- 05Workflow engine basics
- 06Explosion logs: what happens when agents crash
Real workflows for AI-native OPC operators - content factory, sales workflow, Feishu + n8n automation, SOP design, and context engineering.
- 01What is an AI-native OPC?
- 02One-person company workflow
- 03AI content factory
- 04AI SOP design
- 05Feishu + n8n automation
- 06Agent team collaboration
- 07Context engineering
- 08From workflow to organization
04
Build in Public Systems
OPCIn Progress
How to turn real builds, failures, workflows, and experiments into audience, trust, and long-term leverage.
- 01Why build in public is changing
- 02Explosion logs as public learning assets
- 03How to publish workflows
- 04AI-native company dashboard
- 05Content system from build logs
- 06OPCEO's public build system