LENA AI

Getting Started with LENA AI

For Studio Haze internal developers. Set up your environment and run your first workflow in minutes.

Overview

LENA AI complements CSKernel™’s code semantic extraction engine. Powered by Semantic Paradigm Projection (SPP), it maps language-specific concepts to equivalent structures and provides migration proposals with rationale.

Public Scope

  • This page offers a public overview and onboarding flow.
  • Detailed specs, internal APIs, and distribution paths are available only in Studio Haze internal docs.
  • Access to internal docs requires Studio Haze SSO/VPN.

Prerequisites

  • Studio Haze account and SSO access
  • VPN or internal network access
  • macOS, Linux, or Windows workstation

Installation

LENA AI and CSKernel are distributed via Studio Haze channels. Use one of the following:

  • Dev Portal: SSO login → Tools → CSKernel/LENA → Install
  • Internal docs: Engineering Wiki “Workstation Setup” guide
  • Platform support: request access via the platform ticket queue if needed

Note: External package managers may not be provided; OS builds are served from internal registries.

10‑Minute Quick Start

  1. Install and update the CSKernel CLI; sign in with your account.
  2. Enable the LENA AI component in your workspace and approve permissions.
  3. Prepare the project: connect the target repository and set language/runtime info (auto-detect or manual).
  4. Run semantic analysis (SPP) to interpret lifetimes, type classes, and metaprogramming concepts.
  5. Review proposals with trace-based rationale and migration plan.

Sample Workflow

# Initialize workspace (internal CLI)
csk init --workspace ./demo

# Enable LENA AI (+ consent flow)
csk lena enable --scope project

# Run analysis and generate proposals (SPP)
csk lena analyze --target src/ --emit plan.json --explain

# Optionally apply proposals: dry-run to review impact, then merge gradually
csk lena apply --plan plan.json --dry-run

Commands are illustrative; actual flags may differ on internal channels.

Next Steps

  • Guides: language-specific migrations and best practices
  • Tutorials: step-by-step application on real repositories
  • API Docs: internal endpoints and schemas