Company lore and the 'why' behind technical decisions often disappear when employees leave. An AI agent can analyze the entire codebase and its commit history to answer questions and reconstruct narratives, effectively turning your repo into a searchable archive.

For years, updating legacy systems like bank mainframes running COBOL was prohibitively expensive. Modern AI agents are now so proficient at code migration that these projects are finally feasible. One engineer migrated the entire Bun codebase to a new language in just 11 days, a task that previously would have taken a team a year.

For PE firms buying founder-owned software companies, AI is a game-changer. It dramatically accelerates paying down the technical debt and modernizing the tech stack—often the biggest hurdles to growth post-acquisition. This allows firms to unlock value faster and more efficiently than ever before.

The initial step in modernizing is not to rebuild, but to understand. AI can ingest source code, user manuals, and even screen recordings to map existing processes and identify optimization opportunities, ensuring the new system improves upon the old rather than just replicating it.

Migrating from legacy enterprise systems was once a multi-year ordeal, creating powerful vendor lock-in. AI now automates the process by analyzing environments, converting code, and validating results. This has reduced migration timelines to as little as 30 days, dramatically lowering switching costs for large companies.

AI-driven approaches dramatically reduce the time and cost of modernizing legacy systems. What was once a multi-year, multi-million dollar mainframe project can now be completed in as little as 90 days, fundamentally altering the ROI for tackling technology debt.

Enterprises are trapped by decades of undocumented code. Rather than ripping and replacing, agentic AI can analyze and understand these complex systems. This enables redesign from the inside out and modernizes the core of the business, bridging the gap between business and IT.

Enterprises are finding immediate, high return on investment by using AI to port legacy codebases (like COBOL) to modern languages. This mundane task offers a 2x speed-up over traditional methods, unlocking significant infrastructure savings and even driving new developer hiring.

With AI commoditizing code creation, the sustainable value for software companies shifts. Customers pay for reliability, support, compliance, and security patches—the 'never ending maintenance commitment'—which becomes the key differentiator when anyone can build an initial app quickly.