Exploring AI agents and LLM systems, grounded in architecture, observability, and governance, to drive organizational efficiency.
Kubernetes was built on decade-old assumptions, and its networking model still reflects that history. Modern identity-first networking approaches expose how much operational complexity we've normalized — and offer a path to simpler systems with lower human cost.
AI coding agents can write code, but each session starts without knowledge of your repo structure, conventions, or prior work. Scaffold is an open-source tool that gives agents persistent, machine-readable project context through structured briefing files, with explicit controls to detect and limit drift.
Memrun is a Python SDK and platform for deploying data-intensive services that need warm memory, sticky routing, and bounded concurrency. Deploy a handler with a decorator. The platform handles NVMe caching, locality-aware routing via Kafka, and worker lifecycle on commodity hardware.
Serverless platforms optimized for stateless, elastic compute. But memory-bound workloads need the opposite: warm RAM, fast local disk, and sticky routing. This isn't better serverless. It's a different abstraction entirely. We describe the programming model, the platform mechanics, and how memrun implements it.
Serverless removed servers from the developer's mental model, but it also removed state from first-class support. For data-intensive workloads, that tradeoff is increasingly costly. We built memrun to prove that warm, locality-aware workers can remain serverless in feel while eliminating the state tax that stateless platforms impose.