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BMC AMI Tech Talk: Expand the Analyze Phase with Application Analysis & Program Requirements

Last year we showed how BMC AMI DevX Code Insights turns opaque COBOL into something a developer can read. Real-time execution visualization mapped what programs do at runtime. GenAI-driven code explanation translated the logic into natural language. That work lives at the program level.

Speakers

Eric Fuld Lead Product Manager, BMC Software

Mark Sigler Senior Director Product Management, AMI DevX, BMC

Nick Guillemette Solution Engineer, BMC

event summary

AI-driven application intelligence is reshaping how enterprises modernize legacy software systems

As legacy systems grow more complex, enterprises are turning to AI-driven analysis to uncover hidden logic, dependencies, and risks. Industry experts share how structured insights are redefining modernization strategies and developer efficiency.

core insights

From code complexity to intelligent modernization

The session highlights how AI-powered analysis is transforming how organizations understand, refactor, and evolve legacy applications.

1

Insight 1: Legacy systems lack accessible, reliable program understanding

Many enterprise applications evolved without consistent documentation, leaving critical business logic embedded in code. This creates onboarding challenges and risks during change initiatives, requiring new methods to reconstruct system intent.

2

Insight 2: AI enables multi-layered analysis across portfolio and code levels

Modern analysis spans portfolio-wide insights down to individual program logic. AI-driven tools now surface dependencies, risks, architecture patterns, and runtime behavior—bridging the gap between architects and developers.

3

Insight 3: Structured requirements are becoming foundational for modernization

Generating standardized requirements (e.g., EARS format) from code introduces clarity and consistency. This enables better refactoring, compliance readiness, and smoother transitions to modern languages and architectures.

Modernization is shifting from ad hoc refactoring to structured, insight-led workflows. Organizations are aligning architectural planning with developer execution, enabling faster, lower-risk transformation decisions.

Key takeaways:

  • Adopt layered analysis to connect portfolio-level insights with developer-level code understanding
  • Generate structured requirements directly from code to standardize documentation and decision-making
  • Break down monolithic systems into modular components before pursuing language conversion
  • Leverage runtime and dependency visibility to reduce risk during refactoring efforts
  • Embed analysis tools into developer workflows to accelerate onboarding and execution

“Analyze, understand what you've got, build, break things down into fit for purpose, and then convert.”

Mainframe code explained. Finally

See how BMC AMI DevX Code Insights uses AI to explain complex code, map runtime behavior, break down monoliths, and generate EARS-format specifications so your team can modernize with confidence
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