An agriculture technology company built a crop yield prediction model that combined satellite imagery, soil sensor data, weather forecasts, and historical yield records. The model predicted per-field

A pharmaceutical company I consulted for was three months into a project to fine-tune a large language model on their internal research corpus. The project had a team of four engineers, a budget of $8

A model registry is the version control system for your trained models. Without one, teams track model versions by filename, store artifacts in ad-hoc cloud storage locations, and discover which model

The regulatory landscape for AI safety has fractured along jurisdictional lines. The EU has taken a prescriptive, risk-based approach. The US has taken a sector-specific, agency-led approach. The UK h

Your office building has one electricity meter. At the end of the month, you get a bill for the whole building. You know the total cost of electricity for the month. You do not know which floor consum

When producers and consumers share a Kafka topic without agreeing on the data format, things break in production. A producer adds a field. A consumer expects the old schema. The deserialization fails,

The headline numbers are familiar. Women represent roughly a quarter of AI and data science professionals globally. At senior levels, the proportion drops to the low teens. At the C-suite level of AI-

A consumer goods company built an AI system that recommended reorder quantities for 12,000 SKUs across 340 distribution points. The system optimized for a multi-objective function that balanced invent

Code completion gets the attention, but it is the narrowest part of what AI can do in a development workflow. Walk into any team that has shipped software for a few years and they will tell you: writi