GPT o1: Real-World Applications and Ultimate Prompt Guide

Imagine a world where a year-long coding challenge can be resolved in just one hour. Sounds unbelievable? This is the reality brought to life by GPT AI o1, a breakthrough AI model that transforms coding processes from painstaking to seamless.

In this article, we explore how a PhD student’s year-long coding challenge was revolutionized by GPT AI o1. You’ll discover practical tips on how to effectively assign coding tasks to GPT o1, and gain insights into how developers, researchers, and businesses use this powerful model to transform concepts into functional code.

GPT AI o1: The Ultimate Code Generation Machine

The o1 model is the first public demonstration of OpenAI's 'groundbreaking technology' known under the codename Strawberry. Unexpectedly, the model was named o1 rather than GPT-5. According to the company, this reset to "one" signifies a transition to a new paradigm, where it's no longer just about the number of parameters — the model's "thinking capacity" can now be dynamically scaled according to the complexity of the task.

What Makes GPT AI o1 Special

• Advanced code generation: GPT AI o1 doesn’t just generate text; it writes, debugs, and optimizes code on the fly. Whether you're developing a new algorithm, building complex simulations, or writing automated scripts, GPT AI o1 does the heavy lifting.
• Synthetic data creation: Testing and debugging often require large datasets. GPT AI o1 generates realistic synthetic data, allowing developers to simulate real-world conditions.
• Versatile applications: From research and product development to creative content generation, this model is built to be a multipurpose tool.

Showcase: Success Story of the PhD Student GPT AI o1

The Struggle: 10 Months of Coding Frustration

Meet Alex, a dedicated PhD student who spent nearly a year battling the complexities of coding for his astrophysics research. He manually coded methods described in their research paper and faced constant issues. Every attempt seemed to uncover more challenges, as the code had to be precise to handle data from cutting-edge telescopes. The frustration mounted, and the student wondered if they’d ever finish.

The Breakthrough: How GPT o1 Did It in Just 1 Hour

Curious, Alex decided to test GPT o1-preview. Without even providing the exact code, the PhD student simply fed GPT o1 the methods section of their research paper. What happened next was nothing short of remarkable.

Within minutes, GPT o1 generated working code, making real-time corrections and even creating its own synthetic data inputs. The model identified the core tasks, applied the right algorithms, and transformed the abstract instructions into executable code. A task that had taken 10 months to figure out manually was solved in just one hour.

In real-time, the student’s reaction was full of disbelief:

“Oh my God—it ran! It ran the code in a way that I could not believe. I did not even have to give it any example code... it just understood!”​

GPT o1 not only replicated the function described but also optimized it using synthetic inputs, creating visualizations that would have taken days to manually produce. Even in areas that required additional fine-tuning, the core of the work was done—effortlessly and accurately.

Understanding the O1 Series: o1-preview and o1-mini

This student’s experience is just one of many real-world applications showing how GPT o1 series can change the way developers approach complex projects. The o1-preview is ideal for intricate reasoning tasks, while o1-mini focuses on rapid code generation and efficiency, catering to users who prioritize speed and cost.

• o1-preview: This flagship model is engineered for deep reasoning and advanced problem-solving. It excels in complex tasks requiring comprehensive understanding, demonstrating remarkable performance in benchmarks such as competitive programming and scientific problem-solving.
• o1-mini: A smaller, faster model optimized for efficiency and cost-effectiveness. It is particularly well-suited for coding tasks and applications that require less processing power, making it an attractive choice for developers looking for budget-friendly solutions.

Exceptional Performance: MMLU and MATH

• Reasoning & Knowledge (MMLU): GPT o1-preview leads with a 91% accuracy, the highest in this category. This indicates that the model excels at tasks related to general knowledge and reasoning abilities compared to other models like GPT-4o (Aug 6) and Claude 3.5.

• Quantitative Reasoning (MATH): GPT o1-mini achieves the highest accuracy of 90%, outperforming all other models in this category. This indicates that o1-mini is exceptionally strong in tasks that involve mathematical problem-solving and quantitative analysis.

To illustrate the model's logical reasoning and spatial awareness, let's have a look at its effectiveness in thought experiments. In the scenario where a person walks from the North Pole, the model successfully analyzes the implications of walking 1 km south, then east, and considers how these movements affect the individual's position relative to the starting point. It also accounts for the curvature of the Earth and the concept of latitude.

Assigning Coding Tasks to GPT o1

Working with GPT o1-preview is like having a super-smart developer who picks up on what you need quickly but occasionally overcomplicates things. The great part about o1 is that it doesn’t need complicated prompt engineering to understand you—just give it instructions as you would to a seasoned pro.

For example, if you need to rewrite a course template in Golang to match the look and feel of your website, a short prompt will do the trick:

Rewrite this course template in golang to follow style of my own website. You can reuse all of my styles and drop the external css (as used by the course).

<golang template to rewrite>

<full html source of my website, as copied from browser>

For bigger tasks, like restructuring code or adding a new feature, it is suggested to break it into two steps: Explore and Implement.

First, ask GPT o1 to come up with some ideas that prioritize clean, simple code. Then, directly include the full source files, with sections of code using technologies like Vue.js, Pinia, Tailwind CSS, Axios, Vite, Lucide, a custom icon resolver, and Python FastAPI.

Take a look at this code from my multi-mode (a la vim or old terminal apps) block-based content editor.

I want to build on the keyboard interface and introduce a simple way to have simple commands with small popup. E.g. after doing "A" in "view" mode, show user a popup that expects H,T,I, or V.

Or, after pressing "P" in view mode - show a small popup that has an text input waiting for the permission role for the page.

Don't implement the changes, just think through how to extend existing code to make logic like that simple.

Remember, I like simple code, I don't like spaghetti code and many small classes/files.

After that, pick your favorite solutions and ask o1 to integrate them into the project.

Write me files that incorporate your suggestions: 1-5, 8, 10

In most cases, it gets the code right on the first try—about 95% of the time! This saves a lot of time compared to manually prompting models like Sonnet 3.5 or even GPT-4, making o1 a real time-saver.‍

P.S. Credits to @llm_under_hood for the instructions.

Explore More Use Cases

Supply Chain Crisis Management

In situations like the one faced by Global Tech Innovations (GTI), where geopolitical tensions and environmental issues disrupt supply chains, the GPT o1 model can analyze the crisis and propose immediate, actionable strategies. For example, it can recommend direct engagement with suppliers, prioritizing orders, and identifying alternative sources quickly to mitigate risks.

Procurement Contract Framework Design

In complex procurement scenarios, such as Global Energy Services' transition to renewable energy, the GPT o1 model can help design flexible procurement contracts that address multiple challenges. It can provide specific clauses that ensure compliance with regulatory changes, accommodate technological advancements, and incorporate sustainability goals, thus aligning with the company's long-term strategic objectives.

Financial Strategy Development

For companies like Evergreen Argo Corporation (EAC) grappling with financial crises in their supply chain due to climate change and political instability, the GPT o1 model can generate comprehensive financial strategies. It can suggest innovative financing solutions such as partnerships with fintech companies or blockchain platforms to improve access to capital for small-scale farmers, thereby stabilizing the supply chain.

Medical Diagnosis

The o1 model can be used in healthcare settings to analyze patient data and provide accurate diagnoses based on complex medical information.

Advanced Physics

In mere minutes, GPT o1-preview solved three complex problems from the Classical Electrodynamics textbook by John David Jackson, a task that typically requires PhD-level knowledge and can take graduate students up to two weeks to complete. The model showcased its ability to accurately derive mathematical solutions, even adjusting its approach when necessary.

Customer Service and Support

The o1 model could be integrated into customer support platform to enhance AI-driven chatbots and virtual assistants, providing more accurate and context-aware responses to customer inquiries and troubleshoot issues.

Education and Personalized Learning

Develop intelligent tutoring systems that analyze student performance data to tailor educational content, quizzes, and learning paths.

Revolutionize Your Workflow with GPT AI o1

Say goodbye to repetitive coding and time-consuming debugging with GPT AI o1. Focus on what truly matters — innovation.

Unlock the power of GPT AI o1 by signing up with AI/ML API today. Book a free consultation to see how GPT AI o1 and other 200+ AI models can accelerate your next project.