reversa

Reverse engineering a legacy system with AI agents involves orchestrating a multi-agent plan to analyze the system, extract executable specifications, and track progress across sessions. This approach coordinates discovery, scoping, and validation tasks end-to-end.

AI agent orchestration for executable specifications coordinates multiple agents to analyze legacy code, extract logic, and validate outputs. It applies structured workflows across discovery and extraction phases to produce machine-readable system documentation.

Start a reverse engineering workflow by invoking the orchestrator at session start to begin the reconnaissance phase. The workflow loads instructions and persists state in a local JSON file to guide subsequent agent activities and maintain continuity.

Yes, you can resume legacy system analysis across multiple sessions. The orchestration workflow preserves checkpoints and loads state from local JSON files, ensuring subsequent agent activities maintain continuity and track progress.

Multi-agent reverse engineering operates without external dependencies. The workflow references internal state files and instruction documents to drive agent activities, requiring only the legacy system source code as input for analysis and specification generation.

Orchestrating reverse engineering with AI agents is limited by the need to manually invoke the orchestrator at session start. It relies on structured state persistence in local files, meaning unstructured legacy codebases may require preliminary scoping before agent extraction.