775 tutorials · free to read

A working handbook for data and software engineering.

Hands-on tutorials by Alex Merced on Apache Iceberg, the data lakehouse, pipelines, agentic AI, and the languages and tools that hold it all together.

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  1. 01Decoupled Catalogs vs. Managed Tables: Architectural Freedom in the Age of Table Format Convergence![Papercut comparison of a bundled managed table stack and a decoupled open catalog stack](/images/2026/week-2026-07-06/decoupled-catalogs-vs-managed-tables-architectural-freedom-in-the-age-of-table-format-convergence-diagram-1.png)
  2. 02Decoupled Catalogs vs. Managed Tables: Architectural Freedom in the Age of Table Format ConvergenceCross-posted. This article’s canonical home is iceberglakehouse.com. Decoupled Catalogs vs. Managed Tables: Architectural Freedom in the Age…
  3. 03Designing Idempotent Pipelines in the Agentic Lakehouse: Eliminating Double-Write Anomalies![Papercut duplicate write failure path versus idempotent retry path in a lakehouse pipeline](/images/2026/week-2026-07-06/designing-idempotent-pipelines-in-the-agentic-lakehouse-eliminating-double-write-anomalies-diagram-1.png)
  4. 04Designing Private, Air-Gapped Data Lakehouses: Scaling Iceberg in Highly Secure, On-Premises Clouds![Papercut architecture showing private air-gapped lakehouse with storage, Iceberg, catalog, query, semantic layer, and audit inside secure boundary](/images/2026/week-2026-07-06/designing-private-air-gapped-data-lakehouses-scaling-iceberg-in-highly-secure-on-premises-clouds-diagram-1.png)
  5. 05Designing Your Own AI Harness: A Deep Dive Into the Architecture of Agent Loops, Tools, Context, and ControlA deep dive into custom AI harness architecture: model layers, tool design, context management, permissions, control budgets, persistence, orchestration, and evaluation systems.
  6. 06Deterministic Data Engineering With AI Harnesses: Using Claude Code, Codex, Antigravity, and OpenCode for Data Work You Can Actually TrustHow to use AI agent harnesses for data engineering without losing determinism, reproducibility, and trust in your data pipelines and analytics.