Learning Log

Architecture notes, build logs, and lessons from production.

Practical writing on AI systems, platform engineering, and the tradeoffs that only show up outside demos. No fluff, no theory without grounding.

Build LogMar 15, 202612 min

How We Built Our First Enterprise AI Application

A field report on deploying an internal AI platform inside a real enterprise: security reviews, stakeholder alignment, and operating trust at scale.

Enterprise AIArchitectureCase Study
Read→
ArchitectureMar 10, 202615 min

Designing Reliable AI Pipelines: What Production Taught Us

Reliability in AI systems is mostly about interfaces, observability, fallback behavior, and operational discipline — not the model.

ReliabilityArchitecture
Read→
LessonsMar 5, 202618 min

Why Most AI Systems Fail in Production

Five recurring failure modes that show up when promising AI demos meet compliance, cost, latency, and messy real-world data.

ProductionFailure Modes
Read→
ExperimentFeb 20, 202610 min

Azure Document Intelligence vs. Vision LLMs: A Practical Comparison

When to use dedicated OCR services versus multimodal models. Tradeoffs across accuracy, cost, latency, and operational complexity.

Document AIAzure
Read→
GuideFeb 10, 202611 min

Observability for AI Applications: What to Track and Why

Most AI apps skip the operational layer. Here is the minimum instrumentation that makes production workable: latency, confidence, failure paths, and cost.

ObservabilityProduction
Read→