Some of the most critical systems in government run on software older than the people trying to maintain them. The systems processing unemployment claims, tax returns, and benefits eligibility were built decades ago in programming languages that universities no longer teach, by people who have long since retired. These systems work, after a fashion. But they are fragile, poorly understood, and increasingly dangerous to change. The people who know how they actually work are leaving, and their knowledge is leaving with them.
This is not a new problem. What's new is the convergence of two forces: the accelerating retirement of the workforce that understands these systems, and the emergence of AI tools capable of analyzing legacy code at scale.
The SpecOps Method introduces a different approach to legacy modernization, one that treats specifications rather than code as the source of truth. AI assists in extracting what legacy systems actually do. Domain experts verify that understanding is correct. Modern implementations are then generated from verified specifications. The result is modernization that preserves institutional knowledge rather than losing it.
This book provides both a conceptual framework for thinking about legacy modernization differently and practical guidance for putting that framework into action. You will learn:
Why traditional modernization approaches consistently fail How AI coding assistants change what's possible The six phases of the SpecOps methodology How to select a pilot project and build your team How to work effectively with both AI tools and human experts
Written for government technology leaders, digital service teams, and anyone responsible for systems that have outlived their creators, The SpecOps Method offers a path forward for the quiet crisis hiding in plain sight across government.
