The Hitchhiker's Guide to Agentic AI: From Foundations to Systems
- Published
- Source
- arXiv
- Paper number
- 504
- Field
- AI / General
- arXiv ID
- 2606.24937
Key points
- It covers the foundations from LLM architecture, including tokenization, transformers, attention, and GPU systems, all the way to Flash Attention.
- It covers alignment techniques such as RLHF, PPO, DPO, and GRPO, and reasoning techniques such as Chain-of-Thought and test-time scaling.
- For agents, it covers trajectory RL, RAG and Agentic RAG, in-context, external, episodic, and semantic memory systems, and agent harness design.
- It systematically organizes MCP, or Model Context Protocol, A2A, or Agent-to-Agent, protocols, along with tool use and agent skills.
- It covers centralized, distributed, and hierarchical multi-agent architectures and communication patterns among agents.
- It covers the full practical stack, from evaluation methods and agent UI design to production deployment, across more than 600 pages and 400 references.
Paper links
External research summaries. These are not HDATF publications or measured product results.