15 Mandatory Readings for AI Solution Architects
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2.800+Articles
Dimension of Practical Implementation — From concept to code that works in production. Tools verified, Tutorials with technical grounding and Real cases with declared metrics.
Learning
Reference library, training roadmaps and implementation Tutorials — the canon of AI and the shortest path between understanding and building.
Samples
Real cases with verifiable metrics, technical model analyses and vertical applications by sector — what actually works in production.
Tools
Curated catalog, independent comparisons and complete AI Stacks — honest technical criteria without marketing affiliation.
Reference tools — open source and commercial ecosystem
Implementing Local RAG: Total Privacy without Cloud Dependency
Complete stack with Ollama + Qdrant + FastAPI — from zero to production system without sending data to external APIs.
Inside Llama 3: Anatomy of an Open-Source Language Model
Architecture, structural limitations, and what's actually happening when the model generates text — without the marketing hype.
Claude vs. GPT vs. Gemini vs. Llama: Who Wins in Each Category
Independent benchmarks, cost per token, and the criterion no vendor accounts for: which model works with your real data
Samples
