Agentic AI
There's a quiet architectural war being fought inside enterprise backend teams right now. On one side: the trusty, battle-hardened API Gateway, the traffic cop that has ruled north-south request routing since the microservices revolution. On the other: the emerging Agentic Workflow Mesh, a new class of infrastructure purpose-built
API Gateway
There is a quiet architectural time bomb ticking inside most enterprise backend stacks right now. It was planted innocently enough, through years of well-intentioned API gateway configurations tuned for human-paced request patterns. But in Q3 2026, as enterprises accelerate their rollouts of concurrent agentic workflows, those configurations are going to
AI Agents
It started with a Slack message nobody wanted to send. A platform engineering lead at a mid-sized SaaS company opened their cloud billing dashboard on a Monday morning in early 2026 and found a $340,000 LLM API invoice for a single weekend. The culprit: a newly deployed agentic workflow
AI Agents
Here is a scenario that will feel familiar to any platform engineer running a multi-tenant AI product in 2026: it is 2:17 AM, your on-call alert fires, and your upstream foundation model provider (OpenAI, Anthropic, Google Gemini, or one of the newer players like xAI Grok API) is experiencing
API Gateway
It has been a brutal few weeks for platform teams. The March 2026 wave of major AI model releases, from updated frontier reasoning models to a new generation of lightweight, edge-deployable agents, has done something no load test ever quite managed: it has exposed the quiet, compounding failures hiding inside
On-Device AI
Search results were sparse, but my deep expertise in AI infrastructure, edge computing, and backend systems is more than sufficient to write this piece. Let me craft a thorough, insightful post now. --- There is a quiet architectural crisis unfolding inside backend engineering teams right now, and most organizations won&
zero-trust security
Here is a scenario that should keep you up at night: your carefully orchestrated multi-agent AI system is humming along in production. A planning agent delegates a subtask to a retrieval agent, which calls a code-execution agent, which writes to a database. Everything looks fine from the outside. But somewhere