I benchmarked 9 implementations across 7 AI approaches for streaming classification on Kafka — 5,000 real UK procurement tenders, same stream, same clock. Accuracy, latency, and cost compared across hardcoded
It started as a two-day notebook A live-esports company wanted a raw match stream turned into real-time AI-generated content — produced live, the instant the action happens. Picture a live
10 weeks from notebook to production EKS. A multi-agent AI crisis simulator built with LangGraph and Terraform for $0.02 per game. No hype, just engineering. From Notebook to Production EKS
As the 2026 CNIL fines prove, modern social engineering detection is no longer optional. I’ve spent the better part of the last decade staring at dashboards that say ‘All Green’
Stop overpaying for data. Learn to build a production-grade streaming analytics platform using Kafka, Flink, and Spark ML for under $300/month. Why Your Real Time Data Pipeline is Bleeding Cash
Runway burning, features piling up, product-market fit still elusive. The engineering teams that find fit fastest share specific mindsets — skateboard methodology, rapid iteration, and knowing when to ship ugly.
A regional manufacturer running a 2000s Java ERP. Server crashes costing thousands. Design files with no backup. Stock management in Excel. This case study walks through migrating legacy infrastructure to
OLTP vs OLAP. Row vs column storage. B-trees vs LSM-trees. Relational vs document vs graph. The fundamentals of distributed systems and database management — distilled from an Oracle learning book
Scala vs Java vs Python — benchmarked on a Monte Carlo stock prediction microservice. Looking at latency, throughput, lines of code, and cognitive complexity. Which one actually wins for streaming,
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