dagctl blog

Technical guides for production data teams

Deep dives on running SQLMesh and dbt-core at scale — infrastructure, CI/CD, scheduling, and the sharp edges nobody warns you about.

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Latest Engineering

The Model Is Commodity. The System Around It Is Not.

Notes on building autonomous systems around language models. The model is the least interesting part.

Scotty Pate Apr 7, 2026 15 min read

Engineering

dbt vs SQLMesh: Which Tool Is Right for You?

A technical comparison of dbt and SQLMesh for data engineers evaluating both tools. Covers state management, environments, SQL understanding, change workflows, ecosystem, and when each one fits.

Mar 25, 2026 13 min read

Vision

Data Engineering, Industrialized

No car company starts by smelting its own steel. The competition wouldn't allow it. But every data engineering team starts from zero. That's the gap, and it's closing.

Mar 18, 2026 6 min read

Engineering

SQLMesh for dbt Users: The Mental Model Shifts That Matter

A practical guide for experienced dbt users evaluating or migrating to SQLMesh — covering the real differences in how environments, deployments, state, and incremental models work.

Feb 27, 2026 11 min read

Engineering

Operating SQLMesh in Production: State, Scheduling, and Observability

How SQLMesh state works under the hood, how to set up scheduling with the built-in scheduler or external orchestration, and what to monitor in a running production system.

Feb 20, 2026 12 min read

Engineering

Running SQLMesh in Production: Infrastructure, CI/CD, and Deployment

How to containerize SQLMesh, set up CI/CD pipelines with the plan workflow, configure multi-environment deployments, and avoid the infrastructure mistakes that bite teams in production.

Feb 13, 2026 14 min read