A deep dive into the architecture of autonomous memory systems for distributed AI agents, covering tiered storage, consistency models, and real-world orchestration patterns.
A practical tour of nine distributed systems patterns that show up in real production stacks, from leader election to the Saga pattern, with concrete examples from Kafka, Postgres, and large web services.
How to design a double-entry ledger that stays correct under concurrency: event-sourced schema, Postgres constraints, and append-only audit trails.
Calling an LLM API is the easy part. Shipping reliable AI features in production demands evaluation pipelines, retrieval layers, observability, cost controls, and guardrails. Here is what real AI engineering looks like in 2026.
Build a production-flavored job queue on Postgres from scratch: schema, worker loop, retries with exponential backoff, and a dead-letter queue. A portfolio project that demonstrates real distributed systems thinking.