Tagged “ai-engineering”
4 posts
Typed judgments inside data tools: five Jev demos
Most LLM features in data tools generate text you then have to parse. I built five demos around a model that returns typed judgments instead (probabilities, choices, scores), so English becomes a column you can filter, test and sort.
|9 min readHow I build AI-native
Building AI-native isn't about writing code faster. It's about thinking in systems and moving your engineering effort to where it survives contact with production. Here's the method, and the work that proves it.
|5 min readBuilding agentic workflows with Claude Code
An LLM can do almost anything once. Getting it to do the right thing every time is an engineering problem. Here's the architecture I use, drawn from a skill that audits websites for GDPR end to end.
|7 min readDesigning a RAG and embeddings backend
RAG demos are easy and RAG in production is hard, and the reason is always the same: retrieval, not generation, is the bottleneck. Here's how I designed the embeddings backend for a multi-agent system where the retrieval layer is the difference between agents that remember and agents that hallucinate.
|6 min read