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PROJECT CASE STUDY / Development tooling

AI Development Workbench

A customized Wove environment links LLM sessions, project context and a real terminal to verifiable execution results.

Used in day-to-day developmentPortfolio case study
AI Development Workbench
Preview published in the repository · GitHub

The problem

AI-assisted development required moving terminal commands, errors and project context manually. Concurrent sessions created risks around stale or incorrectly associated output.

The solution

A working loop binds each LLM session to the appropriate terminal, correlates execution results and keeps acceptance or rollback under human control.

Implemented features

  • Browser LLM-to-terminal binding.
  • Multi-session isolation and request correlation IDs.
  • Execution-state tracking and stale-result protection.
  • Runtime validation and rollback-oriented change management.

Technical approach

Customized Wove · TypeScript · Electron · React · Node.js · terminal / PowerShell · runtime logs. The work builds on a third-party product, whose original licensing remains applicable.

Demonstration & validation

The README shows a real working screenshot and the verification loop, with documented request IDs, stale guards and session separation.

Scope & privacy

This is not an editor built from scratch or an unsupervised autonomous agent. The Wove base and third-party components retain their licenses; the customized working code remains private.

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