Why We Built Loomkindle: The Story Behind the Agentic Semantic Layer
The founding story: why handcrafted SQL pipelines and duplicated semantic definitions sent the team to build Loomkindle from scratch.
Blog
Data engineering, straight talk.
Practitioner-written posts on semantic layer design, agentic data routing, dbt vs standalone metrics tools, schema drift remediation, DuckDB local workflows, and data contracts. Written for senior data engineers and analytics engineers who want specifics, not summaries.
What Is Agentic Data Routing? A Primer for Data Engineers
A ground-up explanation of agentic data routing — what it means, how it differs from traditional orchestration, and when you'd want it.
Semantic Layer vs dbt Metrics: Choosing the Right Tool for Your Stack
A practitioner's guide comparing standalone semantic layers vs dbt's metrics layer — covering use cases, overlap, and complementary roles.
Schema Drift Is Killing Your Pipeline Trust — Here's What to Do
Schema drift is the silent killer of data pipeline reliability. This post covers detection, automated remediation, and contract enforcement.
ETL vs ELT in 2025: What Actually Matters for Modern Data Teams
The ETL vs ELT debate has context that usually gets lost. This post cuts through the hype to what actually affects your team's decision.
DuckDB for Local Analytics: When It Makes Sense and When It Doesn't
DuckDB has earned its hype. But when does local DuckDB analytics make sense vs shipping to a cloud warehouse? Honest tradeoffs.
Data Contracts and the Semantic Layer: Enforcing Consistency Upstream
Data contracts at the semantic layer level give you upstream enforcement before bad data reaches downstream consumers.
Snowflake vs BigQuery: Semantic Layer Considerations for Each
How your choice of cloud data warehouse shapes semantic layer design — query pushdown, cost, and integration patterns compared.