Agentic AI: Building AI agents and retrieval systems, a masterclass in LLM agents, RAG, and production deployment.
This handbook exists because of a gap we kept running into ourselves. Most material on agentic AI andretrieval-augmented generation sits at one of two extremes: either a breathless case for how agentschange everything, with no working code attached to the claim, or a narrow tool tutorial that teaches aframework's own syntax and says nothing about the engineering judgement underneath it. Neitherextreme is much use to someone who actually has to ship a system, with real users depending on itsanswers, that a human eventually has to trust with an action rather than only a sentence
Authors
- Harry Patria (ORCID: https://orcid.org/0000-0002-7844-538X)
Institutions
- SPX Transformer Solutions (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-08-21
- DOI
- https://doi.org/10.5281/zenodo.22049522
- Primary Topic
- Multi-Agent Systems and Negotiation
- Type
- article
- Field-Weighted Citation Impact
- 0.00