In this issue of AIBytes, Rajesh Sampath breaks down the real reason legacy modernization programs keep stalling, even as AI writes code in minutes. It’s not a delivery problem. It’s that “too risky” stands in for four unanswered concerns, from where to start to whether testing will eat the timeline. The article shows how a behavior-first, agentic approach turns modernization from a high-stakes, one-time project into a repeatable, evidence-driven capability that de-risks cutover and keeps every future change on track.
Download the article to learn:
- Why faster AI-generated code hasn’t made core system changes faster or safer
- How a portfolio-first assessment identifies which applications to retire, retain, rehost, replatform, or rewrite
- What a seven-stage, behavior-driven method looks like when it locks in today’s behavior before any code changes
- How an agentic development lifecycle, a context lake, and an agent-based test harness prevent repeat modernizations and prove every change with evidence
Don’t let “too risky” keep critical systems frozen and costly to change. Learn how a behavior-first, AI-driven approach helps teams modernize safely, cut delivery time, and keep every future change faster than the last.
Get the full article now.