Context
Key constraints included multi-environment delivery from CI through production, strict functional parity, and strong security and compliance expectations.
Delivery leadership / AI-enabled execution
Yevgeniy Gavrilov
Enterprise delivery, modernization, and practical AI enablement for distributed teams.
GenAI-assisted development case study
A public-safe snapshot of an enterprise modernization program in the Tax and Accounting domain, focused on migrating a large legacy API surface from Groovy and Grails to Java Spring Boot under strict functional parity requirements.
Problem
Baseline delivery was limited by analysis overhead, repeated implementation patterns, and rework risk caused by framework differences. The program needed to scale execution while keeping review quality and parity stable.
Approach
- Strict task decomposition.
- Standardized briefs and templates.
- PR size constraints.
- Parity and regression checklists.
- Mandatory human self-review.
- Iterative refinement based on sprint retrospectives and metrics.
What worked
- Smaller work items reduced review friction and rework.
- Clear templates improved consistency of outputs.
- Guardrails prevented over-generation and AI drift.
Where it struggled
- Deep analysis and novel libraries.
- Non-determinism and context contamination.
- Subtle logic drift risks in migrations, mitigated through parity checks.
Search topics
- GenAI-assisted development case study
- AI SDLC
- modernization
- API migration
- parity testing
- guardrails
- developer productivity