[HN Gopher] LLM Agents Are Simply Graph - Tutorial for Dummies
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       LLM Agents Are Simply Graph - Tutorial for Dummies
        
       Author : zh2408
       Score  : 10 points
       Date   : 2025-03-19 21:29 UTC (1 hours ago)
        
 (HTM) web link (zacharyhuang.substack.com)
 (TXT) w3m dump (zacharyhuang.substack.com)
        
       | zh2408 wrote:
       | 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/48ff99bb...
       | 
       | Pydantic Agents: organizes steps in a graph:
       | https://github.com/pydantic/pydantic-ai/blob/4c0f384a0626299...
       | 
       | Langchain: demonstrates the loop structure:
       | 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-...
        
         | czbond wrote:
         | Thank you - really interesting looking read, thanks for
         | crafting the deep explanation, with links to actual internal
         | code examples. Also, thanks for not putting it behind the
         | Medium paywall
        
           | zh2408 wrote:
           | Thank you!!
        
       | mentalgear wrote:
       | Everything that was previously just called automation or pipeline
       | processing on-top of LLM is now the buzzword "agents". The hype
       | bubble needs constant feeding to keep from imploding.
        
       | campbel wrote:
       | I follow Mr. Huang, read/watch his content and also plan to use
       | PocketFlow in some cases. A preamble, because I don't agree with
       | this assessment. I think agents as nodes in a DAG workflow is
       | _an_ implementation of an agentic system, but is not the systems
       | I most often interact with (e.g. Cursor, Claude + MCP).
       | 
       | Agentic systems can be simply the LLM + prompting + tools[1].
       | LLMs are more than capable (especially chain-of thought models)
       | to breakdown problems into steps, analyze necessary tools to use
       | and then executing the steps in sequence. All of this is done
       | with the model in the driver seat.
       | 
       | I think the system described in the post need a different name.
       | It's a traditional workflow system with an agent operating on
       | individual tasks. Its more rigid in that the workflow is setup
       | ahead of time. Typical agentic systems are largely undefined or
       | defined via prompting. For some use cases this rigidity is a
       | feature.
       | 
       | [1 https://docs.anthropic.com/en/docs/build-with-claude/tool-
       | us...
        
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       (page generated 2025-03-19 23:00 UTC)