AI Breakthroughs – Boosting Efficiency and Customization

03 December 2025 - 5 mins read time
Tags: AI Blogs Cookbooks

Across these blog posts, several key trends and announcements stand out:

Advancements in GPT Models: The introduction of GPT-5 and GPT-5.1 showcases significant improvements in intelligence, speed, and steerability. Notably, GPT-5.1 offers enhanced customization for agent behavior, improved instruction-following, efficient token use, and the new none reasoning mode for low-latency applications.
Optimized Prompting and Troubleshooting: Comprehensive guides for both GPT-5-Codex (coding) and Sora 2 (video generation) highlight the importance of concise and adaptable prompts. Recommendations stress minimal, specific input for optimal results and provide clear best practices for troubleshooting common model behaviors like overthinking, underthinking, verbosity, and latency.
Integration and Workflow Automation: The seamless connection of custom GPTs with Zapier enables users to integrate ChatGPT with thousands of applications, streamlining workflows across popular productivity tools and CRMs without complex setup.
Business-Driven Model Evaluation: A shift toward evaluating language models based on real-world outcomes, such as user payment conversion rates, is emphasized. A/B testing and statistical analysis replace traditional offline methods, guiding model selection to balance user engagement and operational costs.

Overall, these posts reveal an ecosystem focused on model versatility, tailored user experience, robust integration capabilities, and business-aligned evaluation strategies—empowering both developers and end users to achieve greater efficiency and impact with advanced AI tools.

New Cookbook Recipes

gpt_action_zapier.ipynb

Source: openai/openai-cookbook

The blog post announces the integration of GPT Actions with Zapier, allowing users to connect custom GPTs within ChatGPT to over 6,000 applications and 20,000 actions. This integration simplifies workflows by enabling direct access to various tech tools without extensive additional setup. It includes practical use cases, such as creating a Calendar Assistant GPT that provides context about meeting attendees through LinkedIn or a CRM GPT for seamless HubSpot interactions. Developers are encouraged to familiarize themselves with essential resources on GPT Actions and utilize provided links for setup and configuration. Users can import GPTs into ChatGPT using a specified Zapier URL. Feedback on integrations is welcomed via GitHub for continuous improvement.

gpt-5-codex_prompting_guide.ipynb

Source: openai/openai-cookbook

The “GPT-5-Codex Prompting Guide” outlines key features and recommendations for using the GPT-5-Codex model, which is specifically optimized for coding tasks. Key highlights include:

Steerability & Adaptation: The model excels in generating high-quality code with less guidance and can adapt its reasoning based on task complexity.
Code Review Proficiency: It effectively conducts code reviews and validates software correctness through navigation and testing.
Prompting Principles: Emphasizes minimal prompt usage—focus on “less is more” to enhance output quality. Avoid lengthy instructions or contextual preambles, as they may hinder performance.
Use Case Recommendations: Best suited for agentic and interactive coding situations, providing a streamlined approach for tasks in coding environments like Codex CLI, IDEs, and GitHub.

The guide encourages developers to familiarize themselves with concise prompting to leverage the model’s capabilities effectively.

gpt-5-1_prompting_guide.ipynb

Source: openai/openai-cookbook

The blog post outlines the key features and enhancements of GPT-5.1, the latest model offering improved intelligence and speed for various tasks. Notably, it introduces a new none reasoning mode, optimizing interactions for low-latency needs without compromising on functionality. It significantly reduces token consumption for simpler queries while efficiently processing more complex prompts.

Developers transitioning from GPT-4.1 to GPT-5.1 will benefit from enhanced steerability, allowing customization of agent behavior, personality, and communication style. The model also excels in instruction-following, ensuring complete task execution without unnecessary interruptions. Additionally, the introduction of user updates enhances user experience by providing consistent progress updates during operations. Overall, GPT-5.1 promises increased efficiency and versatility for coding and agentic tasks, cementing its position as a highly adaptable AI tool.

gpt-5_troubleshooting_guide.ipynb

Source: openai/openai-cookbook

The “GPT-5 Troubleshooting Guide” outlines common issues and best practices for optimizing performance with GPT-5. Key findings include:

Overthinking can be mitigated by reducing the reasoning.effort parameter for straightforward tasks and establishing clear stop conditions.
Underthinking issues may be corrected by increasing the reasoning_effort and implementing a self-reflection mechanism to evaluate answers before presentation.
Over-deferential behavior can be addressed by issuing persistence instructions in the prompt, encouraging the model to act decisively.
Verbosity can be controlled by adjusting the verbosity parameter to produce more concise responses.
Latency optimization strategies involve tracking time metrics and structuring requests to minimize response time.

The guide emphasizes the significance of tailored prompts and systematic monitoring to enhance user interactions with GPT-5.

sora2_prompting_guide.ipynb

Source: openai/openai-cookbook

The blog post, “Sora 2: Prompting Guide,” provides comprehensive guidance on crafting effective video prompts for the Sora model. Key points include the importance of balancing detail and creativity in prompts—specificity allows for control, whereas open-ended cues can yield unexpected results. Users are encouraged to treat prompts as a flexible wish list rather than rigid directives, allowing for iteration and adjustments.

Essential API parameters for video generation are outlined, including model selection, resolution, and clip length, emphasizing the need for concise prompts. The guide also covers the anatomy of effective prompts, suggesting clear descriptions of camera angles, actions, and lighting. Additionally, it highlights the role of style and visual cues in shaping the model’s output, alongside techniques for dialogue and sound integration. This guidance aims to enable users to achieve desired video outcomes through thoughtful prompting and collaboration with the model.

selecting_a_model_based_on_stripe_conversion.ipynb

Source: openai/openai-cookbook

The blog post discusses how startups can select AI models based on user payment conversion rates rather than relying solely on offline evaluations and benchmarks. It outlines HyperWrite’s evaluation approach using Stripe payments to determine how effectively different language models convert users into paying customers. Key steps include executing A/B tests where users are randomly assigned to different models, tracking conversion rates, and using statistical analysis to identify significant differences.

HyperWrite’s focus was to transition to a less expensive model (GPT-4.1) without diminishing conversion rates compared to the existing model (Claude 3.5). The results showed that GPT-4.1 matched conversion rates while providing cost savings. The post emphasizes that A/B testing is crucial for startups to optimize their AI models effectively, ensuring alignment with real business outcomes.