Designing reliable AI Systems for Production Environments
What I'm Learning About Enterprise AI Architecture.
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Latest Posts
Educational AI Systems. What I'm Learning About Governance Gaps
As I explore AI governance through formal coursework and implementation context, I'm identifying specific gaps where educational chatbots introduce operational and compliance challenges that standard enterprise AI discussions often overlook.
Educational AI at Scale. Why Governance Precedes Capability
What I'm learning about governance in AI education: why decision architecture has to precede technical architecture.
Prompt Injection in Educational AI. The Security Risk Hidden in Your Compliance Gap
A prompt injection attack on an educational AI system is not just a security incident. Under EU AI Act Article 9, it is a risk your management system should have anticipated, documented, and mitigated before deployment.
Why Document Ranking Matters in RAG. What I'm Learning About Retrieval Failures
Naive RAG retrieval relies on vector similarity alone. This fails silently when documents are semantically similar but contextually irrelevant. Re-ranking adds a second filtering gate that evaluates actual relevance.
RAG Is Not One Thing. A Practical Architecture Map for Reliable Enterprise AI Systems
RAG isn’t a single pattern, but a family of architectures. And choosing the wrong architecture isn’t a performance problem, but a design flaw.
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Raúl Ferrer
Software Architect & Tech Lead. Applying software and systems engineering principles in production to build reliable, observable, and maintainable AI. Author of iOS Architecture Patterns (Apress).
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