Swimm 2.0 is announced as an 'understanding platform' targeting enterprise legacy application modernization. The core argument is that AI agents fail at modernization not due to code generation limitations, but because they cannot reliably understand complex legacy codebases — citing tests showing Claude Code achieved only 35% code coverage and 70% accuracy on a COBOL codebase with 42% variance between runs. Swimm 2.0 addresses this with deterministic static analysis that extracts business rules, decision logic, and data flows directly from source code, then uses AI only as a translation layer into business language. New features include business-domain navigation, Collections for governing modernization plans, source-traced business rules, an MCP server for AI agents to consume pre-validated context, and broad legacy language support including COBOL, CICS, and JCL. The platform claims up to 90% reduction in manual reverse engineering time, 75% time savings, and 61% cost reduction when agents use Swimm's context versus raw code.
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AI agents aren’t good enough at understanding legacy applicationsSwimm 2.0: Understanding for the agentic ageThe vision: your AI modernization factoryUnderstanding that survives modernizationSort: