Notes from building real systems.
Practical writing on software, data and AI engineering: what worked, what did not and why. We share candid technical lessons from production systems.
What we write about
- Production AI
AI Integrations & Evaluation
The unglamorous engineering between a quick prototype and a dependable tool: evaluation frameworks, review loops, guardrails, and daily operational reliability.
- Data Engineering
Modern Data Infrastructure
Pipelines, real-time analytics, and data modeling that turn fragmented operational systems into clean, dependable sources of truth.
- Architecture
Resilient Software Engineering
Building dependable applications, automated release pipelines, and domain-focused tools that operations teams rely on every day.
First essays are currently in review.
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Have a specific architecture or engineering challenge you'd like us to dissect? Send a topic suggestion to info@doxantro.com.