Fullstack Development
6 articles
Building production-grade data products: APIs, pipelines, dashboards, and deployment architectures. From prototype to enterprise systems.
One training monorepo, or a repo per model?
Seven ML products, one retail team, and the question of whether to consolidate training into a single Vertex-native monorepo. The answer is conditional, and the condition is the whole point.
The Hidden Cost of Precision in Operational AI
Enterprise AI systems often work at the first level of granularity, then become fragile when the business asks for more precision. A field lesson from pharmaceutical supply optimization on why incremental architectures matter.
Real Latency vs Perceived Latency in GenAI Systems
Raw latency and perceived latency are different engineering problems. Production GenAI systems feel fast when they expose progress early, overlap backend work, and avoid silent waiting.
Why LLM-Only Parsing Breaks in Production — And What to Do Instead
LLMs can extract structured data from anything — until they cannot. This article documents the failure modes of LLM-only parsing in production pipelines, and presents a layered architecture where determinism comes first and the LLM is used only where it is structurally irreplaceable.
Stop Talking About Agentic Commerce. Start With Agentic RAG.
Most companies are not ready for autonomous commerce agents. The practical starting point is Agentic RAG: systems that retrieve business context, reason over it, and produce decision-ready outputs.
End-to-End Marketing Mix Model Architecture: From Data Pipeline to Optimization API
A comprehensive guide to deploying production-ready Marketing Mix Models—covering data ingestion, model training, cloud deployment, and real-time optimization APIs for budget allocation