A study space on AI agents.
Notes, experiments and open source code to understand how to build AI agents that actually reason. A personal laboratory open to anyone who wants to learn together.
Deep dives on AI agents, Knowledge Graphs, hybrid retrieval and emerging protocols. What I learn I write down, what I write down I publish.
Open source prototypes to test architectures, patterns and ideas. Runnable code, not just theory.
Technical books, articles and tutorials that make enterprise-grade techniques accessible to self-taught learners.
An open space: anyone who wants to read, discuss or contribute is welcome. No roles, no memberships.
Technical books for those who learn by doing
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Public project linked to the book "AI that Reasons". Other repositories are under review and will be published progressively.
Companion project of the book "AI that Reasons". Knowledge graph with ingestion pipelines, hybrid retrieval (vector + graph), web UI and multi-agent orchestration.
