No Code? No Problem — How to Prototype Conversational Workflows with LLMs, Typeform, and Zapier Alternatives

Introduction

Building conversational AI workflows doesn’t require a backend team anymore. With no-code tools like Typeform, Make (Integromat), n8n, and OpenAI APIs, you can prototype full LLM-driven user journeys in under an hour.

This article shows how to build and connect a lead qualification form powered by an LLM that generates dynamic, personalized replies and passes insights into CRMs or email tools.

What You’ll Learn

  • How to trigger LLMs from no-code forms

  • How to capture and route responses with n8n or Make

  • How to personalize messaging with OpenAI

  • How to build multi-step conversations and feedback loops

Tools Used

  • Typeform (form front-end)

  • Make.com or n8n (workflow automation)

  • OpenAI (LLM prompts)

  • Notion / Google Sheets / HubSpot (data storage)

Use Case: Smart Lead Qualifier with LLM Follow-Up

We’ll build a conversational workflow where:

  1. A user fills a Typeform lead form

  2. Responses are sent to a workflow builder

  3. An OpenAI prompt is dynamically composed

  4. A personalized reply is sent via email or shown in a follow-up screen

Step-by-Step: Build the Workflow

Step 1: Create a Typeform

Questions to ask:

  • Name, company, role

  • Problem they’re facing

  • Product they’re interested in

  • Timeline and budget (optional)

Enable webhook responses (Pro feature) or connect via Make.com/n8n.

Step 2: Capture Responses in n8n or Make

n8n: Use the Typeform webhook node Make: Use the Typeform module to poll or catch webhooks

Parse the responses into variables:

{
  "name": "Sarah",
  "company": "Acme AI",
  "need": "automate compliance reporting"
}

Step 3: Construct Prompt for LLM

Use a Set node or text module to compose this:

You are an enterprise AI assistant.
This lead is from Sarah at Acme AI. She’s looking to automate compliance reporting.
Write a personalized follow-up message with a suggested next step and value proposition.

Step 4: Send to OpenAI or Claude

Use the OpenAI (ChatGPT) module:

  • Model: gpt-4

  • Input: composed prompt

  • Output: message text

Store or route the result into email / CRM.

Step 5: Output Personalized Message

Email: Send via Gmail / Outlook / Sendgrid module Slack: Post internally to notify the sales team Typeform End Screen: Redirect user to a dynamic page with a personalized message

Optional Enhancements

  • Score leads with conditional logic (budget, intent)

  • Feed past conversation history from Google Sheets

  • Send CRM update to HubSpot / Airtable

  • Trigger Calendly link generation via API

Bonus: Build a Multi-Step Conversation

Use conditional logic to:

  • Branch based on answers

  • Send additional forms or links

  • Store dialogue context

For example:

If user says “I need AI for marketing” → Send a link to a case study

Conclusion

No-code workflows now support full conversational UX with GPT-4 and forms like Typeform. You can launch high-quality AI assistants, lead qualifiers, or chat interfaces with just glue logic and smart prompts.

This is ideal for:

  • Early-stage startups

  • Marketing teams

  • Product validation

  • Conversational design prototyping

LLMs, Typeform, ZapierFrancesca Tabor