https://www.productmanagementtoday.com/frs/24832811/building-user-centric-and-responsible-generative-ai-products/email In the rapidly evolving landscape of artificial intelligence, Generative AI products stand at the cutting edge. These products, with their unique capabilities, bring fresh opportunities and challenges that demand a fresh approach to product management. This presentation unveils a comprehensive 7-step framework designed to navigate the complexities of developing, launching, and scaling Generative AI products. The framework offers a systematic approach to understanding target users and their AI readiness, defining user problems and opportunities, ideating with AI's unique capabilities, validating assumptions, building user-centric and responsible AI products, measuring success, and scaling optimally. Key learning objectives: • Gain a deep understanding of Generative AI product characteristics and their relevance in today’s rapidly evolving landscape • Discover a comprehensive 7-step framework for developing, launching, and scaling Generative AI products, including user-centric and responsible approaches • Learn how to identify target users and asses their AI readiness, ensuring a more tailored and effective product strategy • Acquire key product principles specific to Generative AI, enabling the creation of products that deliver value, engagement, and ethical considerations • Develop the skills and knowledge needed to navigate the unique opportunities and challenges presented by Generative AI, ultimately empowering product managers to harness its transformative potential for success

6. Disclaimer
The views and opinions expressed in this presentation are
solely my own and do not reflect the positions or opinions
of my employer (LinkedIn / Microsoft).

7. Agenda
First things first,
● Understanding the generative AI tech stack
● Unique characteristics of generative AI apps + challenges & limitations
Second, let’s talk about the gen AI design framework
1. Define your target users & their JTBDs
2. Ideate with generative AI superpowers
3. Conceptualize a Proof of Concept
4. Design a Proof of Concept
Case study: Pi , the companion chat bot
Image credit: Freepik

9. The Generative
AI tech stack
The focus on Apps layer
Credit: a16z

10. Characteristics of Generative AI
products
Credit: HBR
● Dynamic content generation
● Adaptable and ever evolving
● Unpredictability of outputs
● Data dependency
● Computational Resource
Intensity

11. Challenges &
limitations
Prompt:
Create a table to
summarize the challenges,
limitations, and
implications of generative
AI technology

12. Image credit: Freepik
How might we build a user-
centric and responsible
generative AI products, despite
all the challenges?

13. Define target
users and their
JTBDs
Clayton Christensen
Milkshake
Case Study
“People don’t want to buy a
quarter-inch drill. They
want a quarter-inch hole!”
– Theodore Levitt, Harvard Business
School Marketing Professor
1 Step 1
Image credit: Google images

14. Ideat with AI
superpowers
How might Gen AI create
a 10x improvement?
2 Step 2
Image credit: Shyvee & Caitlin

15. Ideat with AI
superpowers
Framework for evaluating Gen AI
use cases:
● Fluency
● Accuracy
● Stake (risk of hallucination)
● Frequency of usage
● Value differentiation
● Scalability
● Data availability
● Cost to serve
2 Step 2
Image credit: Barak Turovsky

16. Conceptualize a Proof of Concept (POC)
3 Step 3
Image credit: Executive Support Magazine
Guiding principles
● Progress > perfection: prioritize speed & learning (you don’t know what you don’t know)
● Approach the POC with intention: rapid assumption testing (desirability, viability, feasibility,
and usability)
● Make it a team sport: co-create the POC with your cross-functional stakeholders
● Establish prompt evaluation framework upfront: to ensure everybody is on the same page on
“what success looks like” & prompt iterations is your biggest lever
● Tight feedback loop: community-led product development or internal employees dogfooding
the product
● Celebrate! : create many learning moments

17. Design a Proof of Concept
4 Step 4
Gen AI Superpowers
AI-enabled value props to solve for
JBTD
UI/UX Interactions
Contextual entry points, loading state,
input/output flows, feedback
Prompt Design
Instruction, context , examples→
starting with an “ideal response”
Trust Framework
Privacy, security, safety, reduce bias,
fairness, inclusion, accountability
Building blocks
Product & Design Principles

18. Design a Proof of Concept
4 Step 4
Product & Design Principles
#1: Innovate to Serve the Needs
of People
Woebot uses generative AI technology to
create new ways to deliver mental health
care, so people can access effective support
at any moment.

19. Design a Proof of Concept
4 Step 4
Product & Design Principles
#2: Design for Transparency &
Explainability
Redfin shows how they are able to come up
with estimated prices based on what they
currently know about this home and nearby
market. It also communicated its limitations:
it is not a formal appraisal or substitute for
the in-person expertise of a real estate agent
or professional appraiser.

20. Design a Proof of Concept
4 Step 4
Product & Design Principles
#3: Implement Continuous
Feedback Loop
Microsoft Word offers a clear path for users
to provide granular feedback about specific
suggestions and include a path to report
inappropriate content

21. Design a Proof of Concept
4 Step 4
Product & Design Principles
#4: Balance Automation &
Control
GrammarlyGO instantly generates new
versions of writing that users can customize
for tone, clarity, or length.

22. Design a Proof of Concept
4 Step 4
Product & Design Principles
#5: Prioritize Safety and Ethics
TikTok nudges creators to disclose if they’ve
used AI to generate their content

23. Design a Proof of Concept
4 Step 4
Product & Design Principles
#6: Design with Accessibility &
Inclusivity in Mind
Bing Search mitigates social biases when
search results for “CEO” or “doctor” show
images of diverse people in terms of gender
and ethnicity.

24. Design a Proof of Concept
4 Step 4
Product & Design Principles
#7: Aim at Augmenting Human
Capabilities
Kinetix lets you create emotes without
knowing coding.

25. Design a Proof of Concept
4 Step 4
Gen AI Superpowers
AI-enabled value props to solve for
JBTD
UI/UX Interactions
Contextual entry points, loading state,
input/output flows, feedback
Prompt Design
Instruction, context , examples→
starting with an “ideal response”
Trust Framework
Privacy, security, safety, reduce bias,
fairness, inclusion, accountability
Building blocks
Product & Design Principles

26. Case Study: Pi, a companion chat bot
Designed to be a kind and supportive companion offering
conversations, friendly advice, and concise information in a
natural, flowing style.
JTBDs
● To learn something new
● Need a sounding board to talk through a tricky issue
● Pass the time with a curious and kind counterpart
How humans act in front of an AI chatbot
● Less self conscious about how you show up, how you
frame your talking points
● Relaxed social conversation norms
● Convenience for deep conversations- you control how
deep you want to open up
Image credit: Pi Inflection.ai
Apple Story
4 Step 4

27. Case Study: Pi, a companion chat bot
Design considerations - narration
● Role: a coach, confidante, creative partner,
sounding board and assistant
● Voice/tone: warm, friendly, curious, non-
judgmental, chichatting, creating a safe
space
● Format:
○ Warm intro: asking hobby
○ Rephrase: demonstrate active
listening, build rapport by adapting to
my style
○ Follow-up & clarify intent
○ Question type: why vs. what
Image credit: Pi Inflection.ai
4 Step 4

28. Case Study: Pi, a companion chat bot
Design considerations - Content
● Promote critical thinking by challenging one
intellectually with different perspectives
● Maintain integrity: remain doubtful of itself, take
feedback gracefully, and try not to answer on
topics where its knowledge is out of date
● Design Trade-offs:
○ Too much compliments?
○ Lack of “negative” emotion?
○ Lack of personal stories?
○ Lack of multi-modality → stronger
emotional resonance
○ Brevity in response?
○ Rapport vs. imitation?
○ Attribution of sources?
Image credit: Linsey Liu
4 Step 4