A Comprehensive Guide to Using OpenAI o1 Effectively: Moving Beyond the Chat Paradigm

OpenAI's latest model o1 is a truly impressive model. It surpasses it's predecessor GPT-4o in many ways, however, to effectively use o1, we first need to understand that it represents a significant departure from previous models like ChatGPT or Claude 3.5 Sonnet. While many of us have grown comfortable with conversational AI where we have a back and forth conversation, o1 represents something fundamentally different - and understanding this difference is crucial for leveraging its power effectively.

From Conversation to Reports: The Paradigm Shift

Imagine you're hiring a new senior analyst. You wouldn't have a back-and-forth chat to extract their expertise - instead, you'd provide them with a comprehensive brief and expect a well-researched report. This is exactly how o1 operates, marking a significant departure from traditional chat-based AI models. The key difference lies in how o1 processes information. Unlike conventional models that engage in interactive dialogue, o1 employs what's called a "think before answering" approach. It's like having a thoughtful expert who takes time to thoroughly analyze your request before providing a comprehensive response.

The Power of Comprehensive Briefs

The secret to getting the most out of o1 lies in how we present our requests. Think of it as preparing a project brief rather than having a conversation. When working with o1, more context isn't just helpful - it's essential.

For example, instead of asking "How can we improve our customer service?" and dripping in some numbers, you might provide:

Current customer satisfaction metrics
Existing service protocols
Specific pain points from customer feedback
Resource constraints and business objectives
Previous improvement attempts and their results

Here's an example prompt:

Our customer AuroraTech seeks to optimize its customer service approach by balancing technological enhancements, strategic investment, and a more personalized support experience. I want a list of five concrete measures on how to implement the improvement for their customer services.

Describe each of the five measures in short detail and estimate the effort and time that is needed to implement the measure. For each measure give a pro and con and an overall score of 1-10 in applicability (10 being the best). Write a recommendation for the three highest-impact customer service improvements measures.

Format your result so that it can be used in a presentation.

Make sure that you only propose measures that are within a budget of 30.000€ per year.

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1. Current Customer Satisfaction Metrics

AuroraTech conducts quarterly satisfaction surveys and tracks real-time Net Promoter Score (NPS) data. The latest figures show a moderate satisfaction level of 78% and an NPS of +22. Though these numbers are slightly above the industry average, management aims to raise overall satisfaction to above 85% within the next 12 months.

2. Existing Service Protocols

AuroraTech employs a multi-tiered support model:

•Tier 1: Frontline chat and phone agents use a scripted knowledge base to handle common issues.

•Tier 2: Specialized technicians address escalated technical problems.

•Tier 3: In-house expert panel tackles advanced software and hardware faults.

A standard operating procedure (SOP) ensures all tickets follow an initial 24-hour response time target, with priority cases flagged for expedited handling.

3. Specific Pain Points from Customer Feedback

•Delayed Response Times: Users often experience wait times longer than the promised 24-hour window when issues spike.

•Script Overuse: Customers complain about feeling “handled” by rigid scripts rather than receiving personalized solutions.

•Lack of Self-Service Tools: Many request a more robust online knowledge base and self-help options to reduce the need for direct support contact.

4. Resource Constraints & Business Objectives

•Staffing Limitations: A lean customer service team struggles to manage tickets during peak demand.

•Budget Priorities: Funding is focused on R&D for new product releases, leaving limited resources for large-scale service overhauls.

•Strategic Goal: Increase overall brand loyalty and expand into new markets, where outstanding support is seen as a key differentiator.

5. Previous Improvement Attempts & Results

•Automated Ticketing System Rollout: Successfully reduced administrative load by 15% but did not significantly improve customer wait times.

•Agent Training Program: Increased first-call resolution rate by 10%, yet feedback still indicates dissatisfaction with scripted solutions.

•Pilot Self-Service Portal: Launched for a limited product line; despite a promising 20% reduction in call volume for that segment, it has not been expanded due to budget constraints.

This comprehensive context allows o1 to generate more precise, actionable insights rather than generic recommendations.

Simplicity in Instructions

Counterintuitively, while o1 needs extensive context about your situation, it needs minimal instruction about how to think. Unlike earlier AI models where we might say "think step by step", "act as business analyst" or "analyze this carefully," o1 works best with straightforward directives.

For instance, rather than writing:

Please carefully analyze the customer feedback data, considering all angles and thinking step by step about potential improvements...

Simply write:

Based on the customer feedback data, recommend three highest-impact service improvements.

The Beauty of Patience

One notable characteristic of o1 is its response time - often taking several minutes to generate a response. While this might seem slow in our instant-gratification world, it's actually a feature, not a bug. This time is spent on deep analysis and reasoning, much like how a human expert might need time to properly analyze a complex business situation. This longer processing time enables o1 to handle complex tasks like:

Developing comprehensive market entry strategies
Creating detailed technical implementation plans
Evaluating complex policy implications

Making the Most of o1's Capabilities

To effectively use o1 in your business, consider these key principles:

Embrace the brief-writing mindset. Instead of thinking about how to ask questions, focus on how to present complete information. Use clear sections or delimiters to organize your input - think of it like preparing a well-structured document rather than writing an email.
be specific about what you want in the output. Rather than asking o1 to "analyze our market position," request "Provide a detailed analysis of our market position, including competitive advantages, vulnerabilities, and specific growth opportunities in the Asia-Pacific region."
Utilize o1's strength in handling complexity. This model excels at tasks requiring deep analysis and multi-factor consideration - the kind of problems that would typically require hours of expert consultation.

Looking Ahead

o1 represents a significant evolution in AI capability - moving from conversational assistants to sophisticated analysis tools. The key to success lies in adapting our approach: providing richer context, being more precise in our requests, and having the patience to allow for thorough analysis. When used correctly, o1 can provide insights and analyses that rival those of expert consultants, making it a powerful tool for modern business decision-making. By understanding and properly leveraging o1's capabilities, businesses can make more informed decisions and develop more sophisticated strategies in our increasingly complex business environment. In the end, mastering o1 isn't about learning new prompting tricks - it's about learning to properly frame our business challenges and provide the context necessary for meaningful analysis.