BuildTwin

Modern software projects depend on many interconnected files, APIs, database models, functions, and tests. A change that looks small, such as renaming a field or modifying a shared function, can unexpectedly break other parts of an application. Developers often discover these problems only after changing the actual codebase and running tests, which can make debugging slower and changes riskier. BuildTwin addresses this problem by creating an isolated, disposable twin of a GitHub repository before applying a risky change. The developer provides a repository and describes the proposed change. BuildTwin profiles the repository, detects its technology stack, package manager, and available test workflow, then creates a sandbox where the experiment can happen safely. BuildTwin first runs the existing tests to establish a baseline. It then applies the proposed mutation only inside the sandbox and runs the tests again. When real failures appear, BuildTwin analyzes the affected files, call sites, errors, and execution results to show what the change actually broke. The next step is IBM Bob. Bob receives the real regression context, analyzes the affected code, and prepares a focused remediation patch. BuildTwin applies that patch only inside the isolated sandbox and runs the tests again. BuildTwin does not assume that a fix is correct just because an AI generated it. The fix must pass real verification. Only when the verification succeeds does BuildTwin report SAFE TO DEPLOY. The original repository remains untouched throughout the simulation. The target users are software developers, engineering teams, and teams working with large or interconnected codebases who want to understand the impact of risky changes before merging them. What makes BuildTwin different is the combination of repository isolation, real change simulation, evidence-based regression detection, IBM Bob remediation, and post-fix verification in one workflow. Instead of asking AI whether a change looks safe, BuildTwin actually tests the change in a controlled twin of the application.