Data & AI Insights

Thoughts on AI delivery, data architecture, and technical leadership. Practical insights from building real systems.

articles published·topics

Data Governance for Engineers: Building Compliance That Ships with the Code

GDPR right-to-erasure in denormalised warehouses, PII detection at ingestion, governance as code in CI, and the audit questions your data platform cannot answer yet.

17 April 2026·12 min read

Topic Clusters

AI Delivery

Production AI agents, RAG, multi-agent systems, MCP

Data Architecture

Data platforms, database selection, observability

Data EngineeringData Architecture

Data Pipeline Engineering: Production Patterns That Survive the First Year

ETL vs ELT tradeoffs, data contracts in CI, schema evolution without pipeline fires, and the failure taxonomy from operating pipelines across fintech and telecom at scale.

17 April 202613 min

Data StreamingData Engineering

Real-Time Data Streaming: When You Actually Need It and How to Build It

Kafka 4.0 with KRaft, Flink vs Kafka Streams tradeoffs, exactly-once semantics in practice, and the cost equation that determines whether streaming is worth the operational overhead.

17 April 202614 min

RAGAI Delivery

Building the Work Brain: A Glean Alternative in a Weekend

Self-hosted RAG over 45,349 Jira and Confluence documents for €60/month on AWS. Hybrid search, Reciprocal Rank Fusion, pgvector, and the three mistakes I made first.

16 April 202620 min

RAGAI Delivery

RAG Architecture That Actually Works in Production

Beyond the tutorials: practical RAG patterns for enterprise systems. Chunking strategies, retrieval architecture, and evaluation frameworks from real deployments.

8 April 202610 min

AI AgentsMulti-Agent Systems

Multi-Agent Systems: Patterns That Ship to Production

Architecture patterns, coordination strategies, and hard-won lessons from building multi-agent AI systems that actually work. Not theory; production patterns.

6 April 20269 min

Data EngineeringData Architecture

Data Observability: The Engineering You're Probably Missing

Why your data pipelines break silently and how to fix it. A practitioner's guide to monitoring, alerting, and incident response for production data platforms.

4 April 202610 min

MCPAI Delivery

Model Context Protocol (MCP): A Practical Guide for Enterprise AI

What MCP is, why it matters for enterprise AI integration, and practical patterns for implementation. A no-hype guide to connecting AI models with your systems.

26 February 202623 min

Data ArchitectureData Engineering

Modern Data Architecture Patterns That Actually Scale

The data architecture decisions that matter in 2026. From warehouse selection to pipeline design, patterns from building platforms that handle real enterprise workloads.

24 February 202624 min

AI AgentsAI Delivery

Building Production AI Agents: Lessons from Real Deployments

Moving beyond demos to production-ready AI agents. Architecture decisions, observability patterns, and hard-won lessons from deploying agents that actually work.

20 February 202626 min

Database DesignData Architecture

Choosing the Right Database: A Practitioner's Framework

How to select databases for enterprise workloads. Beyond the benchmarks and vendor marketing, a practical framework for decisions that stick.

18 February 202629 min

AI DeliveryProject Management

From POC to Production: Why Most AI Projects Fail (And How to Fix It)

The patterns that sink AI initiatives, and the engineering and organizational practices that lead to success. Lessons from projects that shipped and those that didn't.

15 February 202624 min

Data & AI InsightsData & AI Insights