Architecture

A new model called Jev has recently taken the AI world by storm. It’s rapidly become one of the most popular models in the agentic space, and for good reason. In this post I’ll share my thoughts on why I think that is, where this really should fit in your agentic architecture. To understand Jev’s behavior, I also experimented with creating a self-improving prompt injection detector, where the detector is a Jev call. I might talk more about that in a future post, but this post is based on a reading of the docs, and on trying it out with the detector. ...

Three places this claim-triage POC would break at enterprise scale The first two posts in this series covered where I draw the line between deterministic code and LLM judgment in a claim-triage agent, and the infrastructure that makes a “pause for a human” step durable enough to survive a process restart. Those were about what the system does and how it stays reliable. This one is about what it deliberately doesn’t do yet — because a proof of concept that only shows what works is a demo, and I want this repo to signal architectural judgment, not just implementation competence. ...

Reliability is an infrastructure problem, not a prompt problem In the first post of this series, I focused on where to draw the line between deterministic code and LLM judgment. Once those boundaries were set, the next challenge was making the system actually reliable. In the context of a claim triage agent, reliability isn’t just about the model giving the right answer—it’s about the system surviving the reality of how humans actually work. ...

I’ve been trying to build an agentic app, to understand the various trade offs design considerations involved. One thing I decided early on was to focus more on the design decisions and architecture, while letting Claude Code handle the coding bit. 🏢 Business Context In the insurance industry, the triage phase of a claim—determining coverage, verifying identity, and assessing eligibility—is often a primary operational bottleneck. Traditionally, this process relies on manual review or rigid legacy rules that fail when faced with the nuance of unstructured policy documents. The business challenge is balancing high-throughput processing with the absolute necessity of accuracy; in a regulated environment, a single “hallucination” in a coverage determination can lead to significant financial leakage or regulatory non-compliance. ...

This is a personal site — somewhere to write, and somewhere people can find out who I am and what I work on. The constraint I gave myself was no hosting bill. That turned out to be a useful forcing function: it pushed everything toward clean, minimal architecture, where each component has exactly one job. The about page has a chatbot on it. That was a deliberate choice, not a novelty — if someone wants to know whether I’ve worked with Kubernetes or led a platform team, they can just ask rather than scanning bullet points. It also gave me something interesting to build. ...