A collection of field-tested insights on designing and scaling complex systems.
Covering distributed architectures, real-time data platforms, and AI-enabled systems—focused on trade-offs, failure modes, and what truly matters in production.
A deep dive into engineering a distributed, event-driven system capable of sub-100ms latency at scale using Kafka, Bloom filters, and in-memory caching.
Beyond basic rightsizing: A deep dive into data egress economics, compute arbitrage, and building self-healing FinOps loops into your infrastructure.
A deep dive into the reasoning cores, reAct loops, and topological patterns that define modern autonomous AI systems.