In this issue, “AI Assisted Development: Real World Patterns, Pitfalls, and Production Readiness”, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline.
As AI transitions from proof of concept to production, teams are discovering that the challenge extends beyond model performance to include architecture, process, and accountability. Developers are learning to integrate AI into their delivery pipelines responsibly, designing systems where part of the workflow learns, adapts, and interacts with human judgment. From agentic MLOps and context-aware automation to evaluation pipelines and team culture, this transition is redefining what constitutes good software engineering.
This issue captures that evolution, with experimentation becoming engineering and AI assistance becoming a core part of modern software practice.
Free download
