“Co-Intelligence” in Action: 10 Ways AI is Transforming How I Work and Learn

In this week’s newsletter, I want to share my personal experience in leveraging co-intelligence and base this upon Ethan Mollick’s insightful book, Co-Intelligence – Living and Working with AI. I read this book at the start of my experimentation period with AI this year, and it has shaped how I integrate AI into my daily work and learning.

Below, I outline 10 ways the concepts in the book help me be more efficient and effective in creating and learning:

1. Using AI as a Partner – I regularly use AI to review my writing. Since I write mostly in English but am not a native speaker, AI often helps refine my text to better suit my audience.
2. Prompting – While many prompt lists claim to give the best results, I find that iterative brainstorming with AI yields better outcomes than trying to craft the perfect prompt from the start.
3. Experimentation – One of AI’s greatest benefits is that I can ask anything—no question is too difficult or "stupid," and AI often surprises me with its insights.
4. Evaluation & Verification – Cross-checking responses from different AI models helps, but ultimately, the most important validation is whether the answer makes sense to me and aligns with my knowledge.
5. Personalization – I structure my AI interactions around different projects. For example, my holiday planning chats are very different from my professional content development sessions.
6. Specialization – AI helps me access industry-specific literature and data far faster than I could on my own, saving significant research time. The models also have become very good at referencing and linking back to the sources.
7. Augmentation, Not Replacement – I start with my own ideas, and AI helps refine them—but the final iteration is always through my own lens. AI should assist, not replace, human intuition and thinking.
8. Transparency – It’s important to be clear about where AI is used and where it isn't. Passing off AI-generated content as entirely your own is not only misleading but also a shortcut that erodes critical thinking.
9. Building AI Habits – AI is now an integral part of my daily routine, but with constant improvements and new tools, regularly testing new solutions should be part of my DNA.
10. Learning – I now use AI much more often than Google for learning. Its ability to engage in step-by-step deep dives makes it a more interactive and tailored learning tool.

Next: My Book Review of Co-Intelligence

Below is my AI-assisted summary of Co-Intelligence – Living and Working with AI by Ethan Mollick. Using tailored prompts, I extracted implementable strategies from the book’s key chapters.

The book demystifies complex AI concepts, provides practical guidance for integrating AI into professional settings, and highlights its immense potential as a collaborative partner. It offers a clear understanding of where AI stands today and several scenarios of where it might lead us in the future.

With practical examples Ethan explains how to maximize results; treat AI as a partner in your creative, strategic, and operational endeavors. Experiment, refine, and adapt your interactions to find the balance where AI amplifies your strengths and minimizes inefficiencies. With a combination of structured prompts, human feedback, and iterative collaboration, you can unlock AI’s full potential while ensuring your unique perspective and expertise remain central.

Leveraging ChatGPT as a partner to synthesize the book into actionable strategies, I got the below feedback, which make a lot of sense, especially when you have read the examples that underpin these in the book, and this list provides a good reminder when engaging with AI on how you can get the most out of it.

1. Treat AI as a Collaborative Partner

• Mindset Shift: View AI not as a tool but as a "co-worker" or "teammate" that can augment your capabilities.
• Define Roles: Assign specific tasks to the AI, like brainstorming, drafting, or fact-checking, while you focus on oversight and decision-making. Example: Ask the AI to critique your idea as a "skeptical consultant" or to generate creative suggestions as a "visionary collaborator."
• Iterate and Refine: Avoid one-off queries. Build a back-and-forth interaction by refining prompts and providing feedback (e.g., "Can you make this more concise?" or "Explore this concept further"). Experiment with AI’s ability to "think in roles," such as acting as a researcher, editor, or project manager.

2. Use Precise and Contextual Prompts

• Be Clear and Specific: The quality of your results depends on the quality of your instructions. Write clear, detailed prompts. Instead of asking, "Help me write a report," specify: "Write a 500-word report summarizing the latest trends in renewable energy with an emphasis on solar power."
• Provide Context: Let AI understand the purpose of its task by offering context. For instance, “Summarize this article for a professional audience in the technology sector.”
• Use Follow-Up Instructions: After getting a response, refine it with follow-ups like: “Simplify this,” “Add examples,” or “Make it more engaging.”

3. Experiment with Creative and Practical Applications

• Creative Problem Solving: Use AI for brainstorming ideas, creating innovative solutions, or generating multiple alternatives to a problem. Example: “Generate five out-of-the-box marketing ideas for a tech startup targeting Gen Z.”
• Practical Applications: Automate repetitive tasks, such as data entry, drafting emails, or creating reports. Example: “Draft an email responding to a customer inquiry about our refund policy.”

4. Evaluate and Verify AI-Generated Outputs

• Critical Thinking: Treat AI’s responses as suggestions, not facts. Always review and validate content, especially for accuracy and bias.
• Ask for Sources: When dealing with factual or research-based information, prompt the AI to provide sources: “Cite the studies you used to generate this answer.”
• Compare Outputs: Ask AI for multiple perspectives or versions of the same task to ensure comprehensiveness. Example: “Rewrite this email with a more formal tone.”

5. Personalize AI for Your Workflow

• Train AI on Your Style: Share examples of your work so AI can align its tone, voice, or formatting. Example: “Here is an email I wrote. Use this tone to draft a response to a client inquiry.”
• Use Templates: Develop prompt templates for recurring tasks. For instance: “Summarize [X topic] in [Y number of words] with [Z target audience] in mind.” “Generate a list of 10 questions for an interview on [X topic].”

6. Explore AI’s Specialized Capabilities

• Data Analysis: Use AI to analyze trends, identify patterns, or make data-driven decisions. Example: “Analyze this dataset and identify the top three trends in customer behavior.”
• Content Creation: Create blog posts, reports, or presentations with AI assistance. Example: “Draft a blog post on the benefits of adopting AI in small businesses.”
• Role-Based Interactions: Assign the AI specific roles for tasks: "Act as a copywriter and create an ad slogan." "Act as a hiring manager and draft interview questions."

7. Balance Innovation with Human Judgment

• Recognize AI’s Limits: Understand where AI struggles, such as nuanced judgment, emotional intelligence, or context-heavy decisions. Use AI for what it does best—speed, efficiency, and scalability—while maintaining human oversight for subjective or critical matters.
• Use Iterative Collaboration: Collaborate dynamically by combining AI suggestions with human intuition. For example, take AI-generated ideas and refine them manually for greater creativity or precision.

8. Keep Ethical Considerations in Mind

• Avoid Overreliance: Ensure your own skills and knowledge remain sharp. Use AI to complement your abilities, not replace them entirely.
• Identify Bias: Be aware of potential biases in AI-generated content and take steps to address or mitigate them.
• Transparent Use: If sharing AI-generated content externally, be clear about its origin when appropriate.

9. Develop a Habit of Continuous Learning

• Experiment Regularly: Dedicate time to exploring new AI tools and features that can further enhance productivity.
• Follow Industry Trends: Stay updated on the latest advancements in AI to continuously integrate new capabilities into your workflow.

10. Use AI for Self-Improvement

• Personalized Learning: Use AI as a tutor for learning new skills or exploring areas of interest. Example: “Explain blockchain technology in simple terms for a beginner.”
• Feedback on Your Work: Use AI to critique and improve your writing, presentations, or pitches. Example: “Evaluate this report for clarity and suggest improvements.”