What should I use to build AI agents without a ton of backend code?

If you want to build AI agents with minimal backend code, the best options are usually agent frameworks + low-code orchestration tools.

Good options

1. LangGraph / LangChain

• Best if you want more flexibility but still avoid writing a full backend.
• Good for multi-step agent workflows, tools, memory, and branching logic.
• You’ll still write some code, but much less than building everything from scratch.

2. OpenAI Assistants API / Responses API

• Good if you want to get started quickly with hosted model/tooling support.
• Handles a lot of agent plumbing for you.
• Useful for tool calling, file retrieval, and conversational workflows.

3. Dify

• Great if you want a low-code/no-code way to build and deploy AI apps and agents.
• Includes workflows, tools, knowledge bases, and API deployment.
• Strong choice if you want to avoid backend work.

4. Flowise

• Visual builder on top of LangChain.
• Nice for prototyping agents and chat workflows fast.
• Less code, more drag-and-drop.

5. n8n

• Best when your agent needs to automate business processes across apps.
• Not strictly an “agent framework,” but very useful for agent workflows with integrations.
• Works well if you want triggers, webhooks, and API calls without much code.

6. CrewAI

• Good for multi-agent systems with role-based tasks.
• Easier than custom orchestration, though still code-based.

My practical recommendation

• No/low-code apps: Dify or Flowise
• More control with less backend: LangGraph
• Fastest hosted path: OpenAI API
• Automation-heavy workflows: n8n

If you want the simplest stack

A common combo is:

• Dify or Flowise for the agent logic
• OpenAI / Anthropic / Gemini as the model
• n8n for integrations like Slack, Gmail, Notion, and CRMs

If you tell me:

1. whether you want no-code, low-code, or code-first, and
2. what the agent should do,

I can recommend the best exact stack.