Hey folks! I just posted a quick tutorial explaining how LLM agents (like OpenAI Agents, Pydantic AI, Manus AI, AutoGPT or PerplexityAI) are basically small gra

Hey folks! I just posted a quick tutorial explaining how LLM agents (like OpenAI Agents, Pydantic AI, Manus AI, AutoGPT or PerplexityAI) are basically small graphs with loops and branches. For example: OpenAI Agents: for the workflow logic: https://github.com/openai/openai-agents-python/blob/48ff99bb736249e99251eb2c7ecf00237488c17a/src/agents/run.py#L119 https://github.com/openai/openai-agents-python/blob/48ff99bb... Pydantic Agents: organizes steps in a graph: https://github.com/pydantic/pydantic-ai/blob/4c0f384a0626299382c22a8e3372638885e18286/pydantic_ai_slim/pydantic_ai/_agent_graph.py#L779 https://github.com/pydantic/pydantic-ai/blob/4c0f384a0626299... Langchain: demonstrates the loop structure: https://github.com/langchain-ai/langchain/blob/4d1d726e61ed58b39278903262d19bbe9f010772/libs/langchain/langchain/agents/agent_iterator.py#L174 https://github.com/langchain-ai/langchain/blob/4d1d726e61ed5... If all the hype has been confusing, this guide shows how they actually work under the hood, with simple examples. Check it out! https://zacharyhuang.substack.com/p/llm-agent-internal-as-a-graph-tutorial https://zacharyhuang.substack.com/p/llm-agent-internal-as-a-...