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Data Bricklaying Diary

Records practices, thoughts, and pitfalls on the data grunt-work journey, sharing content on data platforms, data analysis, data processing, data governance, knowledge graphs, and more. Less theory, more hands‑on, making complex data technologies simple.

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Latest from Data Bricklaying Diary

86 recent articles

Data Bricklaying Diary

Aug 18, 2026 · R&D Management

Vibe Coding's Paradox: AI Speeds Code but Amplifies Missing Judgment

This article argues that Vibe Coding — rapid AI-driven code generation — increases anxiety because generation speed outpaces human judgment and verification. It distinguishes exploration from delivery, showing how missing problem definition, design baselines, and independent verification turn fast output into systemic chaos, and prescribes guardrails like explicit boundaries, acceptance criteria, and deliberate pauses to retain engineering control.

AI-assisted developmentVibe Codingdesign baselines

0 likes · 19 min read

Vibe Coding's Paradox: AI Speeds Code but Amplifies Missing Judgment

Data Bricklaying Diary

Aug 18, 2026 · Artificial Intelligence

Semantic Models ≠ Live State: Why Agents Need Object Runtime

This article distinguishes semantic models (which define business object meanings) from object runtime (which provides traceable, versioned projections of specific object states for AI agents), detailing five core responsibilities, differences from data platforms and agent runtimes, a credit-adjustment case study, and guidance on when and how to implement minimal object projections.

Agent ArchitectureCDCMCP

0 likes · 21 min read

Semantic Models ≠ Live State: Why Agents Need Object Runtime

Data Bricklaying Diary

Aug 17, 2026 · Artificial Intelligence

Don't Overhype Ontology: A Three-Gate Framework for AI Semantic Decisions

This article warns against treating ontology as a universal solution for AI scenarios, distinguishing semantic governance, deterministic computation, and dynamic reasoning, and provides a three-gate decision framework to evaluate when ontology adds value versus when simpler mechanisms suffice.

AI architectureKnowledge RepresentationLarge Language Models

0 likes · 19 min read

Don't Overhype Ontology: A Three-Gate Framework for AI Semantic Decisions

Data Bricklaying Diary

Aug 16, 2026 · Big Data

Ontology-Driven Data Governance: 8 Steps to Connect 4A from Business Scenarios to Feedback

This article presents an eight-step methodology for ontology-driven data governance that connects business, data, application, and technology architectures (4A) by starting from high-value business scenarios, establishing semantic kernels, mapping data evidence, linking application actions, referencing technical constraints, enforcing semantic quality, publishing usable semantic products, and closing the loop with operational feedback.

4A architectureAgentData Governance

0 likes · 12 min read

Ontology-Driven Data Governance: 8 Steps to Connect 4A from Business Scenarios to Feedback

Data Bricklaying Diary

Aug 15, 2026 · Industry Insights

Beyond 4A: Ontology-Driven Data Governance for AI-Ready Enterprise Architecture

This article explains why traditional 4A enterprise architecture fails to support AI agents, proposes an ontology semantic platform as a computable cross-domain layer, and outlines an 8-step approach to transform static architecture assets into dynamic, AI-ready business context with semantic services and action contracts.

4A architectureAI agentsData Governance

0 likes · 13 min read

Beyond 4A: Ontology-Driven Data Governance for AI-Ready Enterprise Architecture

Data Bricklaying Diary

Aug 14, 2026 · Artificial Intelligence

Action ≠ API: Designing Business Execution Contracts for Enterprise Agents

This article explains why ontology Actions are not mere API wrappers but business execution contracts that bind semantics, decisions, evidence, permissions, idempotency, compensation, and audit receipts, detailing four Action forms, five boundary categories, common misconceptions, and a six-step implementation approach for enterprise agents.

IdempotencyMCPaction contract

0 likes · 20 min read

Action ≠ API: Designing Business Execution Contracts for Enterprise Agents

Data Bricklaying Diary

Aug 13, 2026 · Backend Development

Where Do Business Rules Belong? A Framework for Atomic Rule Placement

This article proposes decomposing business policies into atomic rules—semantic definitions, fact constraints, disposition strategies, process rules, and transaction invariants—and assigning each to its appropriate engineering carrier (ontology, validation, decision service, workflow, or code) based on what it constrains and who owns the outcome, unified by a policy catalog linking versions and implementations.

atomic rulesbusiness rulesdecision service

0 likes · 16 min read

Where Do Business Rules Belong? A Framework for Atomic Rule Placement

Data Bricklaying Diary

Aug 12, 2026 · R&D Management

Scaling AI Pilots: Reuse Validated Capability Packages, Not Agent Instances

The article argues that scaling AI pilots requires reusing validated capability packages—including business semantics, Skills, tool contracts, governance, evaluation assets, and operational mechanisms—rather than copying Agent instances, emphasizing stable core vs. configurable scenario adaptation, phased expansion with admission assessments, unified maintenance responsibilities, and metrics tracking reuse rates and cost reduction.

AI implementationAI scalingAgent reuse

0 likes · 15 min read

Scaling AI Pilots: Reuse Validated Capability Packages, Not Agent Instances

Data Bricklaying Diary

Aug 11, 2026 · Artificial Intelligence

Three-Layer Ontology Intelligence: Separating Semantics, Decisions, and Actions

This article explains why ontology intelligence systems require a three-layer architecture—semantic layer for defining business meaning, decision layer for forming explainable action plans, and action layer for controlled state changes—with explicit handoff contracts to avoid mixing rules and side effects into prompts.

AI architectureDecision LayerOntology Intelligence

0 likes · 20 min read

Three-Layer Ontology Intelligence: Separating Semantics, Decisions, and Actions

Data Bricklaying Diary

Aug 9, 2026 · R&D Management

Beyond Multiple Chats: Real Role Division in AI-Assisted Development

The article presents a case study of separating architecture and development roles in AI-assisted programming, emphasizing decision boundaries, design baselines, deliverables, and evidence-based handoffs. It shows how architecture handles requirements and design while development implements, with gaps returned to architecture, and how mid-project changes require unified baseline updates to avoid conflicting local facts.

AI-assisted developmentGraph EngineeringSDD

0 likes · 21 min read

Beyond Multiple Chats: Real Role Division in AI-Assisted Development