Designing an accessibility system for component libraries turns accessibility from a checklist item into a repeatable engineering and design practice. […]
Building an Accessibility System for Component Libraries Read Post »
LLM latency is the bottleneck that turns promising AI prototypes into frustrating user experiences. When a language model takes hundreds
Optimizing LLM Latency with Hybrid Retrieval–Generation Architectures Read Post »
Model incidents happen: models degrade, predictions stray, and monitoring alerts that data has shifted. A repeatable, practical playbook for responding
Model Incident Playbook: Responding to AI Model Failures and Drift Read Post »
Multimodal search has moved from research demos to products. Users expect to ask questions with words, photos or voice and
Multimodal search UX patterns: designing interfaces for text, image and audio queries Read Post »
Good developer documentation is more than a reference; it is a product whose user experience determines whether engineers adopt an
Docs UX: Patterns to Increase Adoption and Reduce Support Load Read Post »
Embedding AI in customer-facing products raises legal and regulatory issues that go beyond technical engineering. AI compliance must be part
Feature stores are now central to production ML platforms, and continuous integration workflows must treat them as first-class artifacts. A
CI workflows for feature stores: testing, versioning and reproducibility Read Post »
Federated learning offers a way to train machine learning models for product analytics without centralizing raw user data. In 2026,
Federated Learning for Product Analytics: Privacy-First Model Training Read Post »
Event-driven personalization changes how recommendation systems deliver relevant content by reacting to user actions in real time. Instead of periodic
Event-driven Personalization: Building Low-Latency Recommendation Pipelines Read Post »
Managing ML cost is now a core operational concern for engineering and data science teams. As models grow in size
ML cost control: budgeting, autoscaling and spot instances Read Post »
SPA observability means understanding what happens inside client-side single-page applications so you can measure performance, trace failures and debug real
SPA observability: metrics, traces and real-user debugging for client-side apps Read Post »
Composable AI services are the practical approach SaaS teams use to assemble intelligence like building blocks: modular models, well-designed APIs,
Composable AI services: designing modular models and APIs for SaaS Read Post »
