AI Workflow Builder: OpenAI vs. Google vs. n8n

Key Takeaways:

• After n8n, Zapier & others now OpenAI launched its own workflow builder to build AI workflows for OpenAI Models: OpenAI Agent Builder

• Agent Builder enables users to create multi-Agent environments with

  • tools,

  • guardrails,

  • vector storages,

  • IF-ELSE-flow logics and more

  in a no-code UI

• Contrary, Google offers a Python library to create multi-Agent environments: Google SDK

• LangChain comments: "Not another workflow builder"

  1. Visual workflow builders are not “low” barrier to entry.

  2. Complex tasks quickly get too complicated to manage in a visual builder.

• That aligns with my view:

  • If tasks are too complex OR could become to complex, a coded solution is way more flexible then a visual no-code solution

  • A simpler task could easily be done by an Agent without a complex workflow

  • Non-technical people can build logic rather quickly but complex, production-ready, maintainable workflows should rather be coded than non-coded

• We learned that LLMs are provide good results when the Context is clear - which is only possible with RAG pipelines, guardrails and multi-agent setups. If we now add further complex IF-ELSE-rules/workflows we are back to complex, maintain-intensive environments LLMs once promised to save us from

• n8n added further feature: Now you can build AI agents and automation with natural language within n8n.

  
  
  
  

  

  
  

  

  
  

Sources:

• https://openai.com/index/introducing-agentkit/

• https://platform.openai.com/docs/guides/agents/agent-builder

• https://blog.langchain.com/not-another-workflow-builder/

• https://x.com/mdancho84/status/1975221616968675726

• https://google.github.io/adk-docs/