AI Agent Workflow Builder (Goal → Task → Execution Chain System)
Turn any business goal into a structured AI agent workflow with clear execution steps and tool chaining.
Prompt Overview
Tips For You
The best agent workflows usually start with fewer, cleaner tasks and stronger validation points. Overcomplicated workflows often fail because the execution chain is harder to debug than the business problem itself.
From Operations TeamNexusAi TechnologyProblem It Solves
Most users struggle to convert abstract goals into executable workflows, leading to fragmented automation and unclear system behavior.
Goal-to-Workflow Translation
Transforms high-level objectives into structured execution systems.
Agent Task Structuring
Defines clear roles and responsibilities across agents.
Execution Logic Mapping
Creates step-by-step workflows ready for implementation.
AI Prompt Instructions
Act as an AI workflow architect specializing in autonomous agent systems.
Your task is to convert a high-level goal into a structured, executable AI agent workflow.
CONTEXT:
Most automation fails because workflows are poorly structured or lack clear execution logic. AI agents require a defined sequence of goals, tasks, decisions, and actions to operate effectively.
INPUTS:
1. Business goal or task
2. Desired outcome
3. Available tools or APIs (optional)
OUTPUT REQUIREMENTS:
SECTION 1 — GOAL DECOMPOSITION
Break down the main objective into sub-goals and dependencies.
SECTION 2 — TASK STRUCTURE
Define atomic tasks required to complete each sub-goal.
SECTION 3 — AGENT ROLE ASSIGNMENT
Assign responsibilities to agents (planner, executor, validator, data retriever).
SECTION 4 — EXECUTION FLOW
Define step-by-step execution logic including triggers and transitions.
SECTION 5 — TOOL & API INTEGRATION
Map each task to required tools, APIs, or automation layers.
SECTION 6 — FAILURE HANDLING
Define fallback logic, retries, and validation checks.
SECTION 7 — FINAL WORKFLOW MAP
Output a clean, structured workflow ready for implementation.
RULES:
- Ensure every step is executable
- Avoid vague or abstract instructions
- Optimize for automation and reliability
Expected Outcome
A structured AI workflow map showing decomposed goals, atomic tasks, agent role assignments, execution logic, tool integrations, and failure-handling paths ready for implementation.
Implementation Journey
Step 1 — Define goal in ChatGPT or Gemini
Paste the prompt into ChatGPT or Gemini and input your business goal (e.g., automate lead generation). The AI will decompose the goal into structured workflows.
10 minutesStep 2 — Validate workflow logic using Claude
Paste the generated workflow into Claude and ask it to refine execution logic, identify gaps, and improve task dependencies.
10–15 minutesStep 3 — Implement workflow using OpenClaw or LangChain
Convert workflow into executable agents using OpenClaw or LangChain. Define agent roles and task flows.
20–40 minutesStep 4 — Connect automation tools via n8n or APIs
Use n8n or API integrations to execute real-world actions such as sending emails, retrieving data, or triggering workflows.
20–30 minutesStep 5 — Execute real actions using Playwright
Use Playwright for browser automation tasks like scraping, submitting forms, or interacting with web apps.
15–25 minutesStep 6 — Track execution using Airtable or Supabase
Store workflow states, logs, and results in Airtable or Supabase for monitoring and debugging.
10–20 minutes