"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."
"The virtual panel " AI in the Trenches: How Developers Are Rewriting the Software Process," moderated by Arthur Casals, featuring Mariia Bulytcheva, Phil Calçado, Andreas Kollegger, and May Walter, shifts the focus to hands-on experience. The panelists share essential insights on AI successes and failures within daily workflows, underscoring the need for context, validation, and cultural adaptation to ensure AI becomes a sustainable element in modern engineering."
AI moving from proof of concept to production requires addressing architecture, processes, accountability, and delivery integration rather than focusing only on model metrics. Teams must design systems where parts of workflows learn, adapt, and interact with human judgment, supported by agentic MLOps, context-aware automation, and robust evaluation pipelines. Adoption demands validation practices, clear business objectives, and cultural shifts so AI assistance becomes sustainable in engineering practice. Common production failures stem from weak problem framing and the prototype-to-production gap. Practical guidance includes framing business goals, building evaluation and deployment pipelines, and adapting team practices for continuous learning and responsibility.
Read at InfoQ
Unable to calculate read time
Collection
[
|
...
]