New Guide Explains How to Build Smart AI Agents from Scratch

A new comprehensive reference called 'The Hitchhiker's Guide to Agentic AI' has been published on arXiv. It serves as a practitioner's guide for building autonomous AI systems, covering the entire pipeline from first principles to production deployment. The book's central thesis is that building great agentic systems requires understanding every layer of the pipeline, not just one.

The guide opens with the LLM substrate—transformer architecture, GPU systems, training and fine-tuning (including SFT, LoRA, and mixture-of-experts), model compression, and inference optimization—treating these as essential foundations rather than the primary focus.

This matters because it provides a structured, end-to-end view of how to build AI agents that can operate autonomously. Rather than focusing on just one aspect, it connects the dots between model internals and real-world system design.

If you're curious, you can read the full abstract on arXiv by searching for 'The Hitchhiker's Guide to Agentic AI.'