Introduction Last year, I spent some time studying Oracle Banking Microservices Architecture (OBMA), together with enterprise schedulers and orchestration platforms such as Control-M . Part of the work involved understanding how to convert traditional Control-M jobs into Airflow DAGs. During this process, I started to observe an important architectural distinction: Not all workflows are the same. While studying OBMA, I noticed that Netflix Conductor was used as the workflow engine inside the architecture.

Introduction When working with AMD GPUs and ROCm-based AI workloads, one common issue appears when using uv for Python dependency management. The problem becomes especially visible when setting up projects like ComfyUI on Linux with ROCm-enabled PyTorch builds. Although ROCm-specific wheels are manually installed, running commands such as uv add or dependency synchronization may silently replace ROCm-enabled packages with standard PyPI versions that only support CUDA. This leads to broken GPU acceleration and unexpected runtime failures.

Introduction Spec-driven development is becoming increasingly popular in the era of AI-assisted software engineering. Instead of starting directly from implementation, teams define specifications, domain rules, contracts, and architectural intentions first, allowing Large Language Models (LLMs) and automation tools to generate significant parts of the system. This approach can dramatically improve development speed, documentation quality, and alignment between business and engineering. However, one important challenge emerges quickly: Architecture drift.