Application modernization has always been hard. The hardest cases combine decades of complexity with missing knowledge, proprietary technology, hardware dependencies, unclear requirements, and systems that cannot simply be switched off. Agentic AI gives us a new chance to make these projects technically and economically viable. It can reconstruct knowledge, explore unfamiliar systems, and support modernization at a previously unrealistic scale. But producing modern code does not prove successful modernization.
Agentic engineering is only as good as its verification mechanism. This talk shows how to assess a candidate, build the right context, define what good looks like, and modernize in controlled increments. We will examine a framework combining human judgment, AI based evaluation, and deterministic tests to create credible evidence that the new system actually works. The question is not whether agents can modernize a legacy system. It is whether we can prove that they did.
This talk has been presented at AI Coding Summit Berlin, check out the latest edition of this Tech Conference.






















