Inside OpenAI | Logan Kilpatrick (head of developer relations)

1. Hire for Agency & Urgency

When hiring, prioritize candidates who demonstrate high agency and urgency. High agency individuals proactively identify and solve problems without needing extensive consensus, enabling faster progress and greater impact.

2. Build Vertical AI Products

When building AI products, focus on specific, vertical use cases rather than general-purpose assistants. This strategy helps avoid direct competition with foundational AI providers and allows for deeper domain-specific value creation.

3. Provide AI Prompt Context

Provide ample context to AI models in your prompts, including relevant background information, links to external resources, or specific details, to ensure more accurate and valuable responses.

4. Leverage AI for Engineering

Utilize AI tools like ChatGPT for software engineering tasks, especially lower-hanging fruit, to achieve significant efficiency gains (potentially 50% or more) in development.

5. Utilize Custom Internal GPTs

Develop and use custom GPTs to address tactical, company-specific problems by incorporating internal nuance and domain knowledge, making AI solutions highly relevant and effective for your organization.

6. Prioritize Product Reliability

Prioritize providing a robust and reliable user experience for your products and APIs. Even the most innovative features are useless if customers cannot dependably use them.

7. Adopt “Measure in Hundreds”

Adopt a “measure in hundreds” mindset for new endeavors, viewing initial failures as early attempts in a long series, to encourage persistence and acknowledge that success often requires numerous tries and compounding effort.

8. Prioritize Quality Sleep

Prioritize and improve your sleep habits, as sleep science suggests it’s one of the most significant ways to enhance personal well-being and performance.

9. Innovate Beyond Chat Interfaces

Develop AI products that go beyond traditional chat interfaces, offering novel user experiences to gain a significant competitive advantage in the market.

10. Plan for AI Normalization

Plan for rapid user adoption and normalization of new AI tools; assuming immediate, radical, and disruptive change can be a disadvantage, while anticipating quick integration into daily routines provides an edge.

11. Augment Human Capabilities with AI

Actively learn and use AI tools to augment your capabilities, as humans augmented by AI will be more competitive in the job market than those who don’t adopt these technologies.

12. Use New Embeddings Models

Leverage the new V3 embeddings models for question-answering systems based on your own documentation, especially for non-English languages, due to state-of-the-art performance, improved multilingual capabilities, and significantly lower cost.

13. Adopt ChatGPT Business Accounts

For businesses, consider using ChatGPT Teams or Enterprise to manage multiple subscriptions, enable SSO, and securely share internal prompt templates and custom GPTs, enhancing collaboration and control.

14. Report AI Bugs with Examples

When reporting bugs or issues with AI models, provide shared chats or tangible, reproducible examples to enable developers to effectively diagnose and fix the problems.

15. Expense AI Tool Subscriptions

Request your company to expense your ChatGPT Plus subscription (or similar AI tools) to ensure you’re using the latest versions and maximizing your productivity with AI.

16. Consult Prompt Engineering Guides

Consult official prompt engineering guides (e.g., OpenAI’s) to learn best practices and nuanced techniques for improving AI model performance.

17. Integrate Zapier with GPTs

For non-developers, explore integrating Zapier with your GPTs to connect with thousands of applications and enable your custom AI to perform a wide range of automated actions without coding.

18. Build Socratic Learning AI

Consider building AI tools that employ a Socratic method or interactive learning approach to help users learn new concepts more effectively.

19. Foster Slack-Heavy Culture

Foster a Slack-heavy culture for instantaneous, real-time communication and cross-functional coordination, as it can be more efficient than in-person interactions for quick alignment.

20. Maintain Small Research Teams

In resource-constrained research environments (e.g., GPU capacity), maintain an intentionally small research team, as adding new researchers can decrease overall productivity unless they significantly up-level existing team members.

21. Prioritize Mission Alignment

When making product decisions, consistently evaluate whether a proposed initiative aligns with and contributes to the core mission (e.g., achieving AGI), using it as a primary filter for prioritization.

22. Adapt Planning to Change

Implement mechanisms for continuously updating your understanding of the market and adapting goals, especially in rapidly evolving fields like AI, to remain agile and responsive to change.

23. Build AI Solutions Now

If you have innovative ideas for AI solutions, now is the opportune moment to build them, as the world needs more practical applications of these tools.

24. Try Weighted Sleep Mask

Consider using a weighted sleep mask (e.g., from “Manta Sleep”) to improve sleep quality, as the added pressure can be beneficial.

25. Try OAWAAWAAW Sleep Mask

Try the OAWAAWAAW sleep mask, which is designed with ample eye space to prevent pressure on eyelids and eyelashes, potentially improving comfort and sleep quality.

26. Build Radically Different General AI

If you aim to build a general-purpose AI assistant, ensure it offers a radically different and superior solution to multiple existing problems to effectively compete with established platforms.

27. Create Private Planning GPT

Build a private GPT for personal or team planning (e.g., OKR planning) to ensure consistency in framing, focus on individual metrics, and avoid common planning pitfalls.

28. Prepare for GPT Monetization

Prepare for future monetization opportunities within the GPT store by building valuable custom GPTs, as creators will soon be able to earn revenue based on usage.

29. Use Narrow Vertical GPTs

When introducing AI to new users, focus on packaging GPTs as narrow, vertical tools that solve one very specific problem well, making the value immediately clear and encouraging broader adoption.

30. Design Data-Grounded AI Answers

Design AI products that allow users to ask natural language questions and receive data-grounded summaries or insights, moving beyond dashboard filters to provide direct answers to complex queries.

31. Experiment with Prompt Cues

Experiment with subtle cues like adding a smiley face or instructing the model to “take a break” before answering, as these human-like interactions can sometimes yield small performance improvements due to training data patterns.