Guided Series
Curated multi-part deep dives across three domains: AI engineering — retrieval, evaluation, and agent patterns that make LLM systems production-worthy — infrastructure — distributed systems, cloud architecture, and the defaults worth reconsidering — and platform & DevOps — from custom images and CI runners to full dev environment assembly. Each series builds progressively from fundamentals to production patterns; domains are cross-referenced where they intersect.
GitOps in Practice 1
Multi-cluster ArgoCD architecture, repo structure, ApplicationSets, and the operational patterns that make GitOps work at scale.
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RAG and AI Engineering 7
From retrieval fundamentals to agentic loops — building AI search systems that work in production.
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Distributed Systems 6
CAP trade-offs, partial failure, dual writes, and data reconciliation at scale.
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Cloud Architecture 5
Migration patterns, region-level resilience, modernisation, cost engineering, and security architecture for production cloud systems.
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Cloud Defaults Reconsidered 2
Examining widely-recommended cloud defaults that frequently get applied as blanket mandates without evaluating whether the cost is proportional to the actual benefit.
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DevOps & Platform Engineering 6
From custom images and CI runners to full dev environment assembly — the infrastructure that accelerates delivery.
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Fresh VM to Dev Infra: The Complete Setup GuideNew Mar 04, 2026
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