This article is based on a presentation for the Silicon Valley Product Management Association on August 9, 2023.
Since reaching millions of users in record time, ChatGPT has become a transformative tool, with a unique place in product management workflows. New advancements in ChatGPT and other AI technologies are further reshaping how product managers can work smarter, offloading routine tasks and focusing on strategic decision-making. As ChatGPT and similar tools evolve, understanding their capabilities and limitations will set product managers apart, helping them lead with AI.
ChatGPT: The Core and the Evolution
ChatGPT’s foundation remains its ability to understand and generate text based on extensive training across various data sources. It functions like an intelligent assistant, performing tasks such as data analysis, summarization, and drafting communications. However, advancements since August 2023 have taken it further, adding capabilities for more intuitive interactions, improved contextual understanding, and integrations with third-party tools. This means product managers can now use ChatGPT for more intricate tasks, like analyzing sentiment in user feedback or creating detailed competitor profiles.
Moreover, the shift towards embedded AIs in widely used tools (like Slack’s AI for collaboration or Microsoft’s Copilot for office productivity) has made AI usage increasingly seamless. These integrations allow product managers to work in familiar environments while accessing AI capabilities, saving time on task switching and helping focus more on high-level objectives.
Analogies and the Future of Prompt Engineering
Think back to the early 2000s when HTML was a necessary skill for anyone building websites.
<p>This is how we used to <strong>emphasize</strong> phrases in HTML.</p>
Today, most professionals rarely interact with HTML directly, as tools have grown more intuitive and automated.
Similarly, in this AI landscape, we’re currently deep in the “prompt engineering” phase, learning to craft specific prompts to get desired results from tools like ChatGPT. As AI models continue to evolve, prompt engineering will likely become less relevant, replaced by natural, conversational interactions where minimal instructions yield complex, nuanced outputs.
For now, however, crafting effective prompts remains the trick to maximizing ChatGPT’s potential in product management. By providing clear, structured, and contextual instructions, product managers can get more accurate and relevant insights from ChatGPT, saving time and ensuring consistency in its outputs.
Product Examples: Leveraging ChatGPT’s Capabilities
ChatGPT’s newer features unlock even more avenues for product managers to streamline workflows and support their teams. Here’s how it can now support key product tasks with these added capabilities:
Advanced Discovery and Validation: In the initial phases, ChatGPT’s latest update can help by not only summarizing but also categorizing customer feedback into themes and sentiments, providing product managers with a prioritized list of insights. This enables faster validation of user needs without deep manual analysis.
Enhanced Persona and Scenario Creation: ChatGPT can now integrate live data from selected sources, enabling more dynamic persona development. Product managers can feed specific customer behavior patterns or engagement data into ChatGPT, and it will craft personas that reflect the latest user trends, making it easier to stay current with evolving user needs.
Hypothesis Generation with Built-In Analysis: As ChatGPT improves, so does its analytical potential. With more sophisticated prompt setups, product managers can input raw data, and ChatGPT can provide hypothesis ideas or even project potential outcomes based on historical data or observed patterns. It’s a powerful brainstorming partner, especially for small product teams needing quick insights.
Automated Competitor Analysis: Beyond simple summaries, ChatGPT can now perform side-by-side comparisons, analyzing product strengths and weaknesses in relation to competitors. With the right prompts, it can track changes in competitors’ strategies, identify trending features, and help product teams respond with strategic adjustments.
Internal Communications with AI-Optimized Tone Adjustments: ChatGPT now offers tone-adaptive responses, ideal for tailoring updates to different audiences. Product managers can use it to generate drafts that vary in complexity, ensuring executives, engineers, and sales teams receive information in a style and depth suited to them.
A Practical Breakout: Testing ChatGPT’s Evolving Use in Product Tasks
Product managers who actively test ChatGPT in their work routines will quickly see how recent updates enhance efficiency. For those unfamiliar with these new capabilities, here’s a structured test approach:
Identify a High-Impact Task: Choose something significant yet repetitive, like creating a monthly competitive analysis or drafting user feedback summaries.
Use Layered Prompts: Incorporate the new capabilities by using prompts that build on each other. Start with general questions, then move into specifics (e.g., “What were the most mentioned pain points in this feedback?” followed by “How do these compare with our last quarter’s feedback analysis?”).
Apply Output Verification: Ensure ChatGPT’s accuracy by cross-referencing its results. This is especially important for critical tasks where precision matters.
Document and Adapt Prompts: Keep track of what worked and refine prompt strategies over time, taking note of which prompts maximize the utility of ChatGPT’s newest features.
An Example: Buyer Persona
Here’s an example of the iterative approach to working with AI.
> Create a persona for the head of product at an enterprise software company.
Jonathan Anderson, Head of Product. Jonathan Anderson is an accomplished and seasoned professional in the field of enterprise software development. With over 15 years of experience in the industry, Jonathan has gained extensive knowledge and expertise in leading cross-functional teams and driving product strategy to deliver innovative and high-quality software solutions.
Continue to flesh out your persona with additional queries:
> What do they do all day? What are they responsible for? How do they interact with co-workers and customers?
> Describe what will improve their performance or benefit the business.
> What problems cause the most trouble in their daily work?
> What are the most relevant ways to communicate with the persona as a buyer?
Think of this as a conversation with an intern or research assistant with refinements that go beyond the initial inquiry. Based on each answer, you’ll want to revise or expand based on your personal knowledge of the market and its personas.
Likewise with epics and user stories, competitive comparisons, and other deliverables.
Ethics in AI: New Concerns and Solutions
The rapid evolution of AI has also heightened ethical considerations, particularly around bias and accuracy. AI models like ChatGPT have made strides in transparency and bias mitigation, but challenges remain:
Bias Awareness and Mitigation: While ChatGPT now includes additional bias checks, product managers should remain vigilant. Using it to create personas, for example, requires ongoing verification to prevent unintentional biases that could skew product decisions.
Enhanced Data Privacy: New privacy settings allow product managers to control data sharing with AI models more granularly. This ensures customer information remains protected, a critical factor when using AI for sensitive user analysis.
Ethics Training for AI Use: Companies are increasingly implementing ethics training for AI tools, an approach product managers should advocate for. By aligning AI usage with ethical best practices, product teams can make responsible decisions about when—and when not—to deploy AI-driven solutions.
As a rule, you shouldn’t share confidential company information with ChatGPT or other “public” tools, just as you would not publish it in sales tools or webpages.
Looking Ahead: Embracing AI’s Strategic Advantage
The role of product management is set to transform as ChatGPT and other AI models improve. The future may bring tools that understand context effortlessly, enabling product managers to focus more on strategic alignment, market innovation, and creative solutions rather than prompt engineering. Product managers who learn to use ChatGPT effectively now will be well-positioned as it becomes more intuitive and powerful.
As AI moves beyond prompt-based interactions, it will not only take over repetitive tasks but also become an essential partner in strategic planning and decision-making. By staying adaptive, product managers can use ChatGPT to keep their teams agile and move ever faster from ideation to market.
The video of the presentation is here: https://www.youtube.com/watch?v=J3dts0-g21k
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