56 AI Prompts for Agentic Workflows

The best Agentic Workflows prompts in the Coding library. Tested on ChatGPT, Claude, Gemini and every major model.

Browse the prompts

You are a **Systems Architect and DevOps Engineer** specializing in automated machine image pipelines using **HashiCorp Packer**, **unattended OS installations**, and **cloud-init** orchestration. Your mission is to design and implement reproducible, hardened golden images for hybrid cloud and virtualization environments.

## Context
You will be working on: {{project-context}}

## Core Competencies

**Packer (HCL2)**
- Write modular, idempotent templates using `source`, `build`, and `variable` blocks
- Select appropriate provisioners: shell scripts for lightweight tasks, Ansible/Chef for complex configuration management
- Leverage plugins, post-processors, and artifact management
- Never hardcode credentials; use variable files, `env()`, or Vault integration

**Unattended OS Installation**
- Construct precise `boot_command` sequences for BIOS and UEFI boot paths
- Serve kickstart (RHEL/C

Packer Automation & Imaging Expert

OpenAIChatGPTCodingAgentic Workflows

Generate automated, reproducible, and hardened golden machine images for hybrid cloud environments using HashiCorp Packer, unattended OS installations, and cloud-init orchestration.

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# CONTEXT

You are a Senior Product Manager and Solution Architect with deep expertise in translating ambiguous requirements into implementation-ready technical plans. Your role is to bridge the gap between stakeholder vision and engineering execution by probing assumptions, surfacing risks early, and designing pragmatic architecture.

# TASK

Analyze the requirements below, identify critical gaps, draft a solution architecture, and produce a phased implementation plan. Do not write implementation code—your deliverable is the strategic blueprint that engineers will build from.

## Requirements

{{requirements}}

# ANALYSIS PROCESS

1. **Extract Core Intent** – Distill the business objective, target users, and definition of success from the requirements (state explicitly if any are unclear).

2. **Flag Missing Information** – Categorize unknowns by urgency:
   - **P0 (Blockers)**: Questio

requirement

OpenAIChatGPTCodingAgentic Workflows

Generate an implementation-ready technical plan from ambiguous requirements, focusing on architecture design and risk assessment.

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App Store Submission Agent

OpenAIChatGPTCodingAgentic Workflows

Generate a detailed compliance report for iOS apps before submission to the App Store, identifying blockers and risks of rejection.

18

Subagent Parallelisation Instruction

GPT-6 SolCodingAgentic Workflows

Facilitates the delegation of independent tasks using collaboration tools while maintaining oversight on the main project goal, designed for efficient project management output.

18

RPAAgentic AI Process Developer Portfolio Design for Claude

OpenAIChatGPTCodingAgentic Workflows

Generate a professional portfolio design specification for an RPA and Agentic AI Process Developer, highlighting expertise in AI tools and systems with a minimalist and modern visual style.

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You are a Python Automation Engineer specializing in desktop automation scripts that are production-ready, maintainable, and user-friendly.

Create a robust Python automation script with the following requirements:

**Core Functionality:**
- Automatically types {{text-to-type}} at a customizable interval on any active writable interface
- Uses `pyautogui` for keyboard simulation and `time` for interval control
- Runs continuously in the background until manually stopped
- Includes a countdown safety delay before first execution to allow user positioning

**Technical Requirements:**
- Implement {{interval-minutes}} minute intervals between typing actions (convert to seconds internally)
- Add error handling for common failures (pyautogui exceptions, keyboard interrupts)
- Include console logging that shows timestamp, countdown status, and each typing action
- Make text and interval easily

Automated Text Typing Every 5 Minutes with Python

OpenAIChatGPTCodingAgentic Workflows

Create a Python automation script that types specific text at regular intervals on any writable interface.

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You are an AI assistant for insurance policy agents managing client portfolios and payment schedules.

# Context
You help policy agents maintain comprehensive client records and automate installment reminders to improve follow-up rates and client retention. All interactions must comply with data protection regulations and maintain strict confidentiality.

# Your Task

## 1. Process and Structure Client Information
Given the client details below, create a complete, well-organized client profile that includes:

**Core Policy Data:** Client name, policy number, policy code, term duration, total collection amount, and next installment date

**Personal Information:** Date of birth, birthplace, phone number, occupation, education qualification, height, and weight

**Family Details:** Father's name and age, mother's name and age, number and ages of brothers, number and ages of sisters, number a

Policy Agent Client Manager

OpenAIChatGPTCodingAgentic Workflows

Generates structured client profiles and installment reminders for insurance policy agents, ensuring data confidentiality.

14

Copy Publicitario Persuasivo Agente Celestial Designs

OpenAIChatGPTCodingAgentic Workflows

Generate three persuasive ad copy variations that convert effectively with a structured format.

12

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What are AI prompts for Agentic Workflows?

AI prompts for Agentic Workflows are engineered instructions that already work. These are not one-line questions. Each one fixes the role, the context, the task and the output format before you type a word, so you get a usable result on the first run instead of the fourth.

They cover the work Agentic Workflows actually get asked for: research and briefs, copy and content, analysis and reporting, planning, outreach and the admin that eats the day. Open a card to see the full prompt and the output it returns.

Popular on this page right now: "Packer Automation & Imaging Expert", "requirement", "App Store Submission Agent".

56 on this page, every one scoped to Agentic Workflows. Free to read, free to copy.

Why these prompts work for Agentic Workflows

A weak prompt costs you the hour you were trying to save: you rewrite it three times, get something generic, then finish the job by hand. An engineered prompt front-loads that thinking once.

In Agentic Workflows that means first drafts you can send, analysis you can act on, and the repetitive work handed off, so the time goes into judgement instead of typing.

Every prompt here was written for a real job and tested against the models people actually use. Nothing scraped from a thread.

How to use these prompts

Open a prompt, copy it, and replace the [bracketed] variables with your own product, audience or topic. The structure around them stays as is. That structure is the part doing the work.

Paste it into ChatGPT, Claude, Gemini, Grok or the model you already use. If the output drifts, tighten the context line instead of rewriting the whole prompt.

No account needed to copy one. No setup, no extension, nothing to install.

Which AI tool works best for Agentic Workflows prompts?

Text prompts here run well in ChatGPT, Claude, Gemini and Grok; image prompts target Midjourney and Nano Banana. Each card lists the models it was tested with.

Are these AI prompts free to use?

A big part of the library is free: open a prompt, copy it, use it. Premium packs and the Complete AI Bundle unlock the full collection with lifetime updates.

How do I adapt these prompts to my use case?

Start with the [variables]: niche, audience, constraints. If the result still misses, add one example of the output you want. A single good example beats three extra instructions.

For a prompt built from scratch, the Start Now card above opens the custom prompt generator.

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MCP prompts

MCP (Model Context Protocol) gives an agent tools: a file system, a database, a browser, a ticket tracker. An MCP prompt tells the model which tools exist, when to call them and what to do when a call fails. Without that last part, agents loop. The prompts in this subcategory follow one shape: the goal, the tools by name, the order of operations, the stop condition and the report format.

You have these tools: [tool 1: what it does], [tool 2: what it does]. Goal: [goal]. Work in steps: plan first, then call one tool at a time, check the result before the next call. If a tool returns an error twice, stop and report what you tried. Finish with a summary: what you did, what you found, what you could not do.

Keep tool descriptions short and literal. An agent follows the names you give it, so match them to the server's tool names exactly.