Kamal Reader

You just doubled the RAM on your database server to handle a climb in p95 latency. You expect the extra memory to absorb your growing dataset and bring those 45ms spikes back down to 8ms. Instead, the dashboard shows minimal improvement. Write latency remains high, and query response times stay variable. The problem isn’t that … Read more

Modern enterprise AI and data platforms are becoming too operationally complex for traditional reactive monitoring systems. This article explores how self-healing infrastructure architectures can combine telemetry, anomaly detection, autonomous remediation, governance-aware orchestration, and operational learning to create adaptive enterprise reliability systems.

From the Gobi Desert to the Arctic Circle, a generation of private rocket startups is finally bending metal. 2026 is the year they either reach orbit—or run out of cash. (title image credit: Rockets of the World by Nick Stevens) The Monopoly in the Sky Look up on a clear night in 2026 and you’ll … Read more

The next enterprise AI risk is not that a chatbot writes a bad email. It is that an AI agent quietly enters the operational layer of the company and starts ranking priorities, routing approvals, classifying risk, delaying purchases, escalating tickets, flagging customers, and shaping managerial decisions before anyone calls it management. Companies still describe these … Read more

Most AI products don’t fail because the model is bad. They fail because the product decisions around the model are wrong — or absent. Activation looks healthy in week one, then collapses in week two. Generation counts climb while export and approval rates stay flat. Users try the AI feature once, mark it as “interesting,” … Read more