Power of GPT-5: A Deep Dive into OpenAI’s Prompting Guide · AI for LinkedIn

Aug 15 • AI Tips

Power of GPT-5: A Deep Dive into OpenAI’s Prompting Guide

Evyai.com has GPT5 in it.

OpenAI’s latest flagship model, GPT-5, represents a significant leap forward in artificial intelligence, offering enhanced capabilities in agentic task performance, coding, raw intelligence, and steerability. To help users harness its full potential, OpenAI has released a comprehensive GPT-5 Prompting Guide as part of the OpenAI Cookbook, published on August 7, 2025. This guide provides actionable insights and best practices for crafting effective prompts to maximize the quality of GPT-5’s outputs. In this article, we’ll explore the key takeaways from the guide, highlight its practical applications, and explain how developers and users can leverage GPT-5’s advanced features for a wide range of tasks.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

Why GPT-5 Matters

GPT-5 is described as OpenAI’s “smartest, fastest, and most useful model yet,” with significant improvements over its predecessors, including reduced hallucinations and enhanced reasoning capabilities. Its versatility makes it suitable for everything from coding complex applications to handling multi-step agentic workflows. The prompting guide emphasizes that while GPT-5 performs exceptionally well out of the box, strategic prompt engineering can unlock even greater precision and efficiency, particularly for developers building agentic systems or coding solutions.[](https://aitoolsclub.com/a-practical-prompt-engineering-guide-for-gpt-5-with-examples/)

Key Features of the GPT-5 Prompting Guide

The guide, authored by OpenAI experts like Anoop Kotha and Julian Lee, focuses on tailoring prompts to suit GPT-5’s unique strengths, such as its steerability and ability to handle large contexts (up to ~400k tokens). Below are the core components of the guide and their practical implications:

1. Controlling Agentic Eagerness

GPT-5 is designed to operate across a spectrum of autonomy, from tightly controlled task execution to independent problem-solving. The guide provides strategies to calibrate its “agentic eagerness” to suit specific workflows:

• For Less Eagerness: To reduce latency and limit unnecessary tool calls, users can lower the reasoningeffort parameter (e.g., to “low” or “minimal”) and provide clear criteria to constrain exploration. For example, a prompt might instruct GPT-5 to “stop as soon as you can act” and limit tool calls to a maximum of two. This is ideal for latency-sensitive tasks like quick data extraction.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

• For More Eagerness: For tasks requiring autonomy, such as resolving complex queries without user intervention, the guide suggests increasing reasoningeffort and using prompts like: “Keep going until the user’s query is completely resolved, and do not ask for clarification unless absolutely necessary.” This ensures GPT-5 persists through uncertainty, making it suitable for multi-step problem-solving.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

Example Prompt for Less Eagerness:

Goal: Get enough context fast. Parallelize discovery and stop as soon as you can act.

• Start broad, then fan out to focused subqueries.

• Avoid over-searching; stop if top hits converge (~70%) on one path.

• Max 2 tool calls. If more needed, update user and proceed only with confirmation.

2. Tool Preambles for Transparency

GPT-5 is trained to provide “tool preambles”—clear explanations of its actions during tool calls. These preambles enhance user trust by making the model’s process transparent, especially in long-running tasks. The guide recommends prompting GPT-5 to restate the user’s goal, outline a structured plan, narrate each step, and summarize completed work. This is particularly useful for agentic workflows, such as coding or data analysis, where users need to track progress.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

Example Tool Preamble Prompt:

• Restate the user’s goal clearly and concisely.

• Outline a structured plan with logical steps.

• Narrate each step succinctly as you execute it.

• Summarize completed work, distinguishing it from the initial plan.

3. Tuning Reasoning Effort

The reasoningeffort parameter allows users to control how deeply GPT-5 thinks before responding. The guide advises:

• Minimal Reasoning: Use for fast, deterministic tasks like data extraction or simple reformatting. For example: “Extract all email addresses from this text as a comma-separated list.”[](https://aitoolsclub.com/a-practical-prompt-engineering-guide-for-gpt-5-with-examples/)

• High Reasoning: Use for complex, multi-step tasks like solving logic puzzles or generating code. Break tasks into distinct turns to improve quality and speed.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

Example Prompt for High Reasoning:

You are solving a logic puzzle.

• Use reasoningeffort: high

• Explain your reasoning step-by-step before giving the final answer.

• If the puzzle takes more than 5 steps, break it into stages and confirm with me after each stage.

4. Leveraging the Responses API

The guide strongly recommends using the Responses API over the Chat Completions API for agentic workflows. By passing the previousresponseid, GPT-5 can reuse prior reasoning, reducing token usage and improving latency. OpenAI reports a Tau-Bench Retail score increase from 73.9% to 78.2% when switching to the Responses API, demonstrating measurable performance gains.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

Example Responses API Prompt:

resp = client.responses.create(

model="gpt-5",

previousresponseid="resp12345",

input="Summarize the insights from the analysis above in bullet points."

)

5. Maximizing Coding Performance

GPT-5 excels in coding tasks, from bug fixes to multi-file refactors. The guide suggests codifying project standards (e.g., frameworks like Next.js or styling with Tailwind CSS) to ensure consistency. It also highlights lessons from Cursor, an AI code editor, which found that setting low verbosity for general text and high verbosity for code diffs improves readability and reduces unnecessary tool calls.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

Example Coding Prompt:

You are editing a React app.

• Follow BEM CSS naming.

• Use Tailwind for styling.

• Place new components in /src/components/ui.

• Use hooks for state management.

Add a responsive navbar with a dropdown menu matching the existing color palette.

6. Prompt Optimization

The guide introduces a Prompt Optimizer tool in OpenAI’s Playground to refine prompts by removing contradictions, clarifying instructions, and aligning with GPT-5’s capabilities. For instance, a vague prompt like “Write a friendly product description” can be improved by specifying tone, length, and brand voice.[](https://cookbook.openai.com/examples/gpt-5/prompt-optimization-cookbook)

Example Optimized Prompt:

Write a product description for our coffee shop.

• Tone: Warm, inviting, and conversational.

• Length: 150–200 words.

• Brand voice: Cozy, community-focused, emphasizing sustainability.

Practical Applications

The prompting guide is particularly valuable for:

• Developers: Building agentic applications or automating coding tasks with precise tool integration.

• Businesses: Streamlining workflows like market research or data analysis with clear, repeatable prompts.

• Creative Professionals: Generating consistent, high-quality content by fine-tuning verbosity and reasoning effort.

For example, a developer might use GPT-5 to create a frontend application by specifying frameworks and styling preferences, while a researcher could summarize market trends with a prompt that limits exploration to 2023–2025 data and requires three credible sources.[](https://aitoolsclub.com/a-practical-prompt-engineering-guide-for-gpt-5-with-examples/)

Best Practices for Success

1. Be Specific: GPT-5 follows instructions with “surgical” accuracy, so avoid conflicting rules. For example, replace “Never schedule without consent, but auto-assign early” with “Only schedule with explicit consent; if given, choose the earliest time.”[](https://aitoolsclub.com/a-practical-prompt-engineering-guide-for-gpt-5-with-examples/)

2. Use Structured Prompts: Break tasks into steps, provide templates, and specify output formats (e.g., Markdown with H2 headings).[](https://aitoolsclub.com/a-practical-prompt-engineering-guide-for-gpt-5-with-examples/)

3. Iterate and Experiment: Prompting is not one-size-fits-all. Use the Prompt Optimizer and run A/B tests to refine prompts for your use case.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)

4. Leverage New Parameters: Use verbosity to control output length and reasoningeffort to balance speed and depth.[](https://www.cometapi.com/how-to-use-gpt-5s-new-parameters-and-tools/)

5. Ensure Tool Safety: Validate raw text outputs from custom tools and use Context-Free Grammars (CFGs) to enforce valid syntax.[](https://www.cometapi.com/how-to-use-gpt-5s-new-parameters-and-tools/)

Why This Guide Matters

The GPT-5 Prompting Guide is a game-changer because it empowers users to maintain control without micromanaging. By setting parameters like reasoning effort and verbosity, and using structured prompts, users can achieve predictable, high-quality outputs. The guide’s emphasis on transparency (via tool preambles) and efficiency (via the Responses API) makes GPT-5 accessible for both novice and advanced users. Whether you’re building a retro gaming store landing page or analyzing a large dataset, the guide provides a foundation for success.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)[](https://aitoolsclub.com/a-practical-prompt-engineering-guide-for-gpt-5-with-examples/)

Getting Started

To dive into GPT-5, visit the OpenAI Cookbook at cookbook.openai.com and explore the guide’s examples. Set up your OpenAI API key, experiment with the provided prompts, and use the Prompt Optimizer to refine your workflows. As OpenAI notes, “Good prompts aren’t fancy—they’re specific.” With this guide, you can unlock GPT-5’s full potential and build smarter, more efficient solutions today.[](https://cookbook.openai.com/examples/gpt-5/gpt-5promptingguide)[](https://cookbook.openai.com/examples/gpt-5/prompt-optimization-cookbook)

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