learnship

Learn as you build. Build with intent.

What is learnship?¶

learnship is an agent harness for anyone who wants to build, learn, and ship real products using AI agents. It's the scaffolding that makes your AI coding agent actually reliable across real projects.

Every serious AI coding tool (Claude Code, Cursor, Manus, Devin) converges on the same architecture: a simple execution loop wraps the model, and the harness decides what information reaches the model, when, and how. The model is interchangeable. The harness is the product.

learnship gives you that harness as a portable, open-source layer that runs inside your existing AI tool and adds three things your agent doesn't have by default:

• Persistent memory. An AGENTS.md file is loaded into every session so the agent always knows the project, current phase, tech stack, and past decisions. No more repeating yourself.
• Structured process. A repeatable phase loop (Discuss → Plan → Execute → Verify) with spec-driven plans, wave-ordered execution, and UAT-driven verification. The harness controls what context reaches the agent at each step.
• Built-in learning. Neuroscience-backed checkpoints at every phase transition so you understand what you shipped, not just that you shipped it.

What problem does it solve?¶

If you've used AI coding assistants for more than a few sessions, you've hit this wall:

The agent forgets everything. Each session starts from scratch. Decisions get repeated. Code quality drifts. You ship fast but understand less. The more you rely on the AI, the less you own the outcome.

This is a harness problem, not a model problem. Research shows the same model on the same benchmark scores 42% with one scaffold and 78% with another. Cursor's lazy context loading cuts token usage by 47%. Vercel deleted 80% of their agent's tools and watched it go from failing to completing tasks. Same model. The only variable is the harness.

learnship solves this with progressive disclosure, the pattern that separates working agents from impressive demos. Context is revealed incrementally, not dumped upfront. The right files, decisions, and phase context reach the agent exactly when needed, nothing more.

Who is it for?¶

learnship is built for anyone who wants to build and ship real products with AI agents, not just developers. If you're a founder, designer, researcher, or maker who uses AI tools to build things, this is for you.

It's the right tool if:

• You're building a real project (not just experimenting) and want the AI to stay aligned across sessions
• You're learning while building and want to actually understand what gets shipped
• You care about code quality and UI quality beyond "it works"
• You want parallel agent execution on Claude Code, OpenCode, or Gemini CLI to ship phases faster
• You've felt the frustration of context loss: repeating yourself every session while the agent forgets past decisions

It's probably overkill if you just need one-off scripts or quick fixes. Use /quick for that.

Install in 30 seconds¶

npx learnship

The installer auto-detects your platform. Then open your AI agent and type:

/ls

That's it. /ls tells you where you are, what to do next, and offers to run it.

Three layers that ship real products¶

Works on 6 platforms¶

npx learnship --all --global   # all CLI platforms at once
/add-plugin learnship           # Cursor marketplace

See the Platform Guide for platform-specific setup and capabilities.

What makes this different¶

Where to go next¶