Production Architecture
Agentic AI Needs Workflow Architecture, Not Just Prompts
Why production AI agents need permissions, state machines, audit trails, approval gates, retries, and recovery paths before they can safely act inside real systems.
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Engineering Lab
Observability Before Autoscaling For AI Workloads
Why AI and cloud-native systems need clear pressure signals, traces, metrics, logs, queues, and cost visibility before scaling decisions can be trusted.
Application Engineering
Offline-First Mobile Apps In The Age Of On-Device AI
Why local state, sync queues, privacy boundaries, background processing, and conflict handling still matter as mobile apps adopt more AI-powered workflows.