Build with context and proof

Software Change

Practical thinking for specifying, testing, reviewing and changing enterprise software with AI assistance.

Reading path

Move from the defining idea to practical decisions.

AI can accelerate delivery only when intent, boundaries, evidence and failure behavior are explicit enough to govern the work.

An AI-native lifecycle changes the system of work around evidence, review gates and accountability.

Generated tests create value when they challenge behavior, boundaries and failure using an independent definition of correctness.

As generation accelerates, review capacity, architecture coherence and accountable judgment become the constraints that matter.

The safest use of coding agents in mature systems begins with context recovery, a focused change and a tested path back.