How to Decide What Work AI Should Do for You: The AI Deputization Audit

Key takeaways

AI tools are evolving from capability-focused to context-aware systems, enabling more effective deputization of routine tasks.
GROKBOT and OpenAI's Computer History are examples of new features that allow AI to understand and automate work based on user recordings and ongoing context, respectively.
The model race in AI is diversified, with speed, cost, and efficiency being critical factors; newer models like Gemini 3.7 Flash and GPT-5.6 Soul Ultra-Fast exemplify this trend.
Choosing the right model depends on the specific use case and budget considerations; more expensive models do not necessarily mean better performance for all tasks.
OpenAI's recent leadership changes are noteworthy but should be viewed in the context of strategic adjustments, not necessarily problems.
The AI Deputization Audit provides a structured way for individuals and organizations to evaluate and decide which recurring tasks can be delegated to AI, emphasizing importance, teachability, verifiability, stakes, and dependency.
Overall, the episode encourages proactive experimentation with AI deputization tools to enhance productivity, while being mindful of privacy and security issues.

Summary

The New Wave of AI Tools for Work Automation

This section discusses recent innovations like GROKBOT and OpenAI's Computer History feature, which move AI from capability to understanding context. GROKBOT allows users to teach tasks by recording them, aiding repetitive workflows, while Computer History lets ChatGPT learn from everything on a computer to understand user habits and automate tasks more effectively. The discussion highlights how these tools facilitate AI deputization—assigning AI tasks that are frequent, teachable, verifiable, low-stakes, and non-unique to the user—and the importance of choosing which work to delegate.

The AI Model Race: Speed, Cost, and Efficiency

This part evaluates the recent release of Google's Gemini 3.7 Flash, emphasizing its speed advantages—over twice as fast as GPT-5.6 Luna—and modest price reduction. However, it faces a middle ground challenge due to limited benchmark performance relative to cost. The discussion extends to how different models perform in real-world tasks, showing that higher-priced models may not always deliver the best cost/benefit ratio. OpenAI's introduction of GPT-5.6 Soul's ultra-fast mode and the debate over model efficiency illustrate the diversity of strategies in the ongoing AI model race.

The Impact of AI on Business and Personnel Moves at OpenAI

This segment covers OpenAI's recent personnel changes, notably the departure of CRO Denise Dresser and its implications amid the company's strategic positioning. The broader context of executive turnover and potential internal shifts are discussed with skepticism and consideration of market perceptions. The conversation also touches on the significance of such moves in shaping investor confidence and company narrative ahead of a delayed IPO.

Practical Framework: The AI Deputization Audit

Central to the episode is the introduction of the AI Deputization Audit—a practical, step-by-step framework to assess which recurring work processes can be handed over to AI. It involves taking inventory of routine tasks, scoring them across five criteria (frequency, teachability, verificability, stakes, and centrality), and categorizing them into 'defer,' 'duet,' or 'consider' for automation. The goal is to help workers systematically decide where AI can most effectively augment their work, balancing potential efficiency gains with privacy and reliability concerns.

Show notes

OpenAI’s Computer History and GrokBot’s “teach a task” feature point to a new phase of AI: tools that learn how you work so they can take more work off your plate. NLW introduces the AI Deputization Audit, a simple framework for deciding what to hand over, what to do alongside AI, and what to keep for yourself. In the headlines: Gemini 3.7 Flash, the true cost of cheaper models, GPT-5.6 Sol’s ultra-fast mode, and more OpenAI executive turnover.

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