AI is graduating from experimental feature to production infrastructure, with Cypress AI eliminating test maintenance overhead and Meta's autonomous agents delivering 5x engineering output. The teams treating AI integration as an engineering discipline are pulling ahead while others debug RAG pipelines by hand.
The industry is shifting from treating AI as features to treating it as infrastructure problems, with Kubernetes absorbing LLM workloads while compliance frameworks scramble to catch up. Meanwhile, the open-source ecosystem is growing faster than its governance structures can handle - a pattern that historically ends badly.
Architecture, platform and delivery practice: modernization, DevOps and SRE, AI in delivery, and pattern updates.