Sources & Further Reading
iSources checked: September 2026
The content of this module was researched in May 2026; all source links were checked for availability in September 2026 and updated where needed. As the AI landscape evolves quickly, some details may have changed since then.
Sources
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Yao, S. et al. (2022). ReAct: Synergizing Reasoning and Acting in Language Models. arXiv:2210.03629. https://arxiv.org/abs/2210.03629
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Anthropic (2024). Tool Use (Function Calling) Documentation. https://platform.claude.com/docs/en/agents-and-tools/tool-use/overview
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OpenAI (2024). Function Calling Documentation. https://developers.openai.com/api/docs/guides/function-calling
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NVIDIA (2024). NeMo Guardrails – Open-Source Toolkit for LLM Safety. https://github.com/NVIDIA/NeMo-Guardrails
Further Reading
Frameworks & Libraries
- LangChain Documentation: Framework for building LLM-powered applications and agents. https://docs.langchain.com/oss/python/langchain/quickstart
- LangGraph: Framework for stateful multi-agent workflows. https://langchain-ai.github.io/langgraph/
Agentic Patterns
- Anthropic – Building Effective Agents: Overview of proven agent architectures and patterns. https://www.anthropic.com/engineering/building-effective-agents
- Lilian Weng – LLM Powered Autonomous Agents: Comprehensive overview of agent architectures. https://lilianweng.github.io/posts/2023-06-23-agent/
Deep Dives
- Andrew Ng – Agentic Design Patterns: Four key agentic AI patterns explained. https://www.deeplearning.ai/the-batch/how-agents-can-improve-llm-performance/