Microsoft CPO: If you aren’t prototyping with AI, you’re doing it wrong | Aparna Chennapragada

1. Invent the Future

Adopt the motto “The best way to predict the future is to invent it.” This encourages building what you believe should exist rather than waiting for others, recognizing that experiential building is key and no one truly knows the future.

2. Leverage Inflection Points

When building zero-to-one products, ensure at least two of three inflection points are present: a significant shift in technology, a clear change in consumer behavior, or a new business model. This framework helps determine if it’s the right time for an idea to succeed.

3. Solve Before Scale

For zero-to-one product development, prioritize “solve before scale.” Resist the temptation to prematurely focus on scaling, and instead, dedicate sufficient time to deeply understand and solve the core problem.

4. Embrace Chaos in Solve Mode

In the “solve mode” for new products, embrace and cultivate an appetite for “chaos” and wide lurches in direction. Be comfortable with significant shifts in focus, as premature fixation on a local hill can lead to long-term strategic errors.

5. Avoid Premature Metrics

For zero-to-one products, be wary of prematurely adopting “grownup metrics” (e.g., CTR, retention) as they can provide false precision. Instead, focus on qualitative feedback and identifying core, highly valued use cases.

6. Continuously Update AI Priors

Actively and frequently update your understanding of AI capabilities, as models evolve rapidly. Challenge outdated “priors” about what AI can or cannot do, setting high expectations and demanding more from current AI tools to unlock new possibilities.

7. Cultivate Reflexive AI Usage

Develop “reflexive AI usage” by constantly prompting yourself to consider how AI can assist with current tasks. A simple method is using a custom Chrome extension that asks “how can you use AI to do what you’re going to do right now?” on every new tab.

8. Prioritize Demos Over Memos

Prioritize prototyping and building to visualize ideas, using “prompt sets” as the new PRDs. Emphasize “demos before memos” to accelerate the product building loop and communicate ideas with higher bandwidth.

9. Adapt to New Dev Cadence

Adapt to the new product development cadence where the time to a first demo is shorter, but full deployment takes longer. Leverage AI to shorten the prototyping, iteration, and user research inner loops, but recognize the higher bar for achieving scale.

10. Cultivate Product Tastemakers

In an era of increased idea supply and rapid prototyping, it’s crucial to have a few “tastemakers” or “auteurs” at the core of product development. This prevents the creation of “Frankenstein products” and ensures a cohesive vision.

11. Elevate PM Editing Function

Product Managers should focus on developing strong “tastemaking” and “editing” functions. In a world with an exponentially higher supply of ideas and prototypes, the ability to discern, refine, and curate becomes paramount, raising the bar for PMs.

12. Earn PM Influence

Product leaders must earn their influence through valuable contributions rather than relying on title-based gatekeeping. Encourage engineers, researchers, and designers to leverage AI tools as “experts in their pocket” to develop and present their own ideas.

13. Learn Coding (Higher Abstraction)

Do not believe that coding is dead; instead, recognize that programming is evolving to higher levels of abstraction. Continue to understand computer science and mental models, as this will enable you to become a “software operator” and democratize interaction with computers.

14. Reimagine Human-Agent Collaboration

Explore and reimagine products and experiences that foster human-agent collaboration. Focus on creating “co-working spaces” where humans and AI agents work together to produce significantly greater output than either could alone.

15. Design Agents for Autonomy

Design effective AI agents by focusing on three core principles: increasing autonomy (delegating higher-order tasks), handling complexity (multi-step goals), and enabling natural interaction (beyond just chat).

16. Design Natural Language Interfaces

Recognize Natural Language Interface (NLX) as the new UX, understanding that conversational interfaces have invisible grammars, structures, and UI elements that require explicit design. Product builders should explore new principles and constructs for natural language.

17. Consciously Design NLX Elements

When designing NLX, consciously design elements like prompts, editable plans (for high-level goals), and the degree to which the AI “shows its work” or progress. Also, proactively suggest obvious follow-up actions to guide users effectively.

18. AI for Persuasive Communication

Leverage AI tools like ChatGPT to enhance communication and persuasion, such as refining pitches or adopting the “What Would X Do?” mindset to tailor messages for specific audiences.

19. Live One Year in Future

Institutionalize a “living one year in the future” mindset by imagining how work would change with advanced AI tools. This involves asking what questions would be asked, what work would be done, and how daily routines would adapt in such an environment.

20. Empower Early Adopters

To manage change in large organizations, don’t hold back early adopters. Instead, implement a “Frontier Program” to roll out cutting-edge experimental features to these users while simultaneously managing longer-term, trusted change for the broader company.

21. Balance Delight and Governance

When building enterprise products, balance user delight with governance and security. Avoid the trap of focusing solely on one aspect or crippling the user experience, as both are critical for success.

22. Embrace Rapid Iteration & Feedback

Use stand-up comedy’s iterative feedback loop (open mics) as a model for product development. This helps product builders develop resilience, get clear micro-feedback from users, and rapidly iterate on initial versions of products.