2 AI for Problem Solving from Text

• Successful AI implementation starts with clearly defining the problem and understanding the audience it serves.

Key Talking Points Slide 45

• Clearly articulate the issue that current AI aims to address.
• Identify who benefits from solving the problem.
• Ensure AI strategies address well-defined needs.
• Resist the temptation to prioritize technology over problems using solution-led thinking.
• Continuously refine understanding of the problem and solution.

Caveats Slide 45

• Avoid starting with technology and retrofitting it to a problem.
• Emphasize the need for cross-functional alignment on problem definition.
• Address concerns about spending too much time on problem framing.
• Highlight that clearly defined problems lead to more impactful AI solutions.
• Problem and audience definition is key before applying AI solutions
• Understanding the problem and identifying the target audience is vital for successful AI implementation.

Key Talking Points Slide 46

• Focus on defining what problem you're trying to solve first.
• Identify who benefits from solving the problem from an audience-centric view.
• AI should align with validated needs, not trends when avoiding jumping to solutions.
• Iteratively improve problem framing to ensure alignment by continuously refining efforts.
• Tailor solutions to deliver measurable value using an outcome-driven approach.

Caveats Slide 46

• Avoid starting with the technology instead of the problem.
• Emphasize collaboration in defining the problem.
• Clarify the need for cross-functional alignment on audience needs.
• Highlight that problems drive better long-term outcomes.
• Prioritize understanding people over technology.
• Personas guide problem-solving by contextualizing user goals, challenges, and opportunities for impactful solutions.

Key Talking Points Slide 47

• Personas in focus act as composite profiles of target groups.
• Capture pains, gains, and behavioral insights of user needs.
• Foster understanding of users and buyers through empathy.
• Align team goals with personas' real-world problems through strategic alignment.
• Combine insights for comprehensive perspectives with qualitative and quantitative data.

Caveats Slide 47

• Clarify personas are generalized, not one-size-fits-all solutions.
• Address the risk of relying solely on assumptions without validation.
• Avoid overcomplicating personas with irrelevant details.
• Ensure personas are actionable and tied to project goals.
• Clearly identifying the problem and its audience ensures solutions are relevant, targeted, and impactful.

Key Talking Points Slide 48

• Focus on core challenges that need addressing when defining the problem.
• Identify who will benefit from solving the problem related to the target audience.
• Connect problems to measurable business and user outcomes through outcome alignment.
• Ensure stakeholders align on problem framing utilizing a collaborative definition.
• Continuously refine problem statements through iterative improvement.

Caveats Slide 48

• Avoid overly broad problem definitions.
• Emphasize collaboration in understanding user pain points.
• Clarify the connection between the problem and organizational goals.
• Highlight the importance of data-driven validation.
• AI enhances smart home systems by simplifying user experiences and reducing operational complexity for scalable automation.

Key Talking Points Slide 49

• Improve accessibility for diverse user groups by ensuring simplified systems.
• Streamline tenant-domicile interactions with AI through tenant automation.
• Minimize maintenance costs through predictive AI leading to cost reduction.
• Build automation that grows with demand to ensure scalable solutions.
• Tackle challenges with tailored AI-driven strategies through strategic problem-solving.

Caveats Slide 49

• Avoid overpromising AI capabilities without addressing its limitations.
• Clarify the importance of data quality in enhancing smart home AI.
• Address potential resistance to adopting new automation systems.
• Highlight the importance of user education for successful adoption.
• Use personas to clarify your audience and their context.
• Personas provide a shared understanding of the audience, offering insights to design solutions that resonate with users and buyers.

Key Talking Points Slide 50

• What is a Persona?: Composite profiles summarizing target audience traits.
• Personas anchor decisions in real user scenarios through contextual relevance.
• Use personas to tailor solutions and improve alignment by guiding design efforts.
• Develop a deeper connection with user motivations and challenges through empathy.
• Personas align teams on user-centered goals, providing a cross-functional tool.

Caveats Slide 50

• Avoid overloading personas with irrelevant details.
• Clarify that personas require validation and regular updates.
• Address misconceptions that personas replace direct user research.
• Highlight the need for a balanced focus on both users and buyers.
• User personas focus on behavior and experience, while buyer personas emphasize motivations and constraints in purchasing decisions.

Key Talking Points Slide 51

• User Personas: Focus on usage behavior, UX preferences, and qualitative insights.
• Buyer Personas: Emphasize budget, value propositions, and business pain points.
• Cover end-to-end needs from both users and buyers from dual perspectives.
• Holistic Design: Solutions should address both usage and purchasing challenges.
• Combine qualitative and quantitative data for accuracy through data integration.

Caveats Slide 51

• Clarify that personas should not overlap unless justified by shared attributes.
• Avoid creating too many personas, which can dilute focus.
• Ensure buyer personas align with organizational priorities.
• Address skepticism about the value of separating user and buyer personas.
• Choose personas to guide your solution exploration.
• Selecting relevant personas ensures solutions are rooted in real-world needs and provide clear guidance for exploration.

Key Talking Points Slide 52

• Activity Purpose: Identify a persona to shape the focus of your solution.
• Relevance to Outcomes: Personas connect solutions to specific goals.
• Collaborative Selection: Use group insights to finalize persona choice.
• Practical Application: Personas guide exercises and subsequent decisions.
• Time Constraint: Allocate 10 minutes to ensure focused discussion.

Caveats Slide 52

• Avoid spending excessive time debating persona details.
• Clarify that personas are starting points, not definitive representations.
• Ensure participants understand the connection between personas and outcomes.
• Highlight the value of diverse perspectives in persona selection.
• Overview of key session topics and focus areas.
• This agenda emphasizes foundational Al topics, personas, and activities to ensure practical learning and strategic thinking.

Key Talking Points Slide 53

• Key Topics: Covering personas, problem framing, and jobs-to-be-done approaches.
• Interactive Exercises: Engage participants with hands-on activities to learn the topics.
• Outcome-Oriented: Build towards actionable insights and solutions during the session.
• Logical Progression: Each topic prepares participants for the next step in learning and applying the concepts.
• Course Focus: Staying problem-driven and solution-oriented to keep the focus on Al.

Caveats Slide 53

• Avoid rushing through agenda topics; maintain a steady pace for a successful session.
• Clarify how activities reinforce session learning objectives.
• Address potential concerns about topic complexity or depth.
• Ensure participants are clear on the flow and structure of the session.
• Leveraging Generative Al for better problem and persona understanding.
• Generative Al supports exploring problems and refining personas through creative and iterative insights, enabling deeper user understanding.

Key Talking Points Slide 54

• Generative Al's Role: Facilitates exploration of problems and personas interactively.
• Problem Alignment: Helps identify and refine core challenges for users.
• Persona Insights: Generates nuanced profiles by analyzing behaviors and needs of the users.
• Iterative Exploration: Supports continuous persona improvement through hypothesis testing.
• Broad Application: Encourages diverse perspectives in persona and problem analysis.

Caveats Slide 54

• Avoid over-relying on AI-generated insights without validation.
• Clarify the importance of human judgment in refining AI outputs.
• Address risks of AI introducing bias into persona definitions.
• Highlight that AI serves as a supplement, not a replacement, for direct research.
• Using Generative Al for creativity and exploration, with some caveats."
• Generative Al enables creativity and innovation by producing new ideas and solutions, but must be used with critical oversight.

Key Talking Points Slide 55

• Creative Output: Generates new content like text, images, and music.
• Multiple Technologies: Combines deep learning, neural networks, and NLP.
• Challenges: Generative AI can produce hallucinations or confabulations requiring user oversight.
• Applications: Useful for brainstorming, content generation, and strategy alignment.
• Iterative Process: Helps refine outputs through successive iterations.

Caveats Slide 55

• Address risks of AI-generated inaccuracies without human verification.
• Emphasize critical evaluation of AI outputs to avoid overreliance.
• Highlight potential ethical concerns in creative applications.
• Clarify that AI enhances but does not replace creative processes.
• Understand the AI Chatbot Dialog: The roles of user, assistant, and system in AI interactions.
• Effective chatbot use depends on understanding the distinct roles of the user, assistant, and system in shaping conversations.

Key Talking Points Slide 56

• User Role: Makes requests and drives the chatbot interaction.
• Assistant Role: Provides responses based on user queries.
• System Role: Governs assistant behavior, ensuring responses meet session context.
• Collaboration: Successful interactions require alignment among roles.
• Session Context: Clearly defined context improves the quality of chatbot responses.

Caveats Slide 56

• Clarify that effective interactions rely on precise input.
• Address misconceptions about AI's ability to infer intent without guidance.
• Highlight the system's role in minimizing errors and maintaining relevance.
• Avoid overestimating the assistant's autonomous capabilities.
• Best practices for creating effective AI prompts.
• Clear, structured prompts ensure Generative AI produces high-quality, relevant outputs tailored to user needs.

Key Talking Points Slide 57

• Clarity Matters: Vague input leads to poor-quality output; specificity is key.
• Role Requesting: Ask for expert-level roles to improve response quality.
• Formatting Guidance: Show desired formats to guide the AI effectively.
• Iterative Refinement: Use examples and step-by-step instructions for better outcomes.
• Quality Input: Higher input quality leads to more actionable AI responses.

Caveats Slide 57

• Avoid expecting perfect results without refining inputs.
• Clarify that garbage input leads to garbage output (GIGO) when using AI.
• Address misconceptions about AI's ability to understand unstructured queries.
• Highlight the importance of including relevant examples for clarity with AI.
• Structuring AI prompts for diverse team needs and goals.
• Teams must align on context, goals, and task requirements to maximize the effectiveness of collaborative AI sessions.

Key Talking Points Slide 58

• Diverse Goals: Tailor prompts to specific team functions (UX, marketing, data science, etc.).
• Session Alignment: Define session context and objectives clearly for consistency.
• Collaborative Focus: Use shared prompts to unify team outputs.
• Role Customization: Ensure prompts address the unique needs of different stakeholders.
• Iterative Improvements: Refine prompts based on team feedback and outcomes.

Caveats Slide 58

• Avoid generalizing prompts across all team roles.
• Clarify that clear communication is essential for team-wide alignment.
• Address challenges in managing multi-disciplinary sessions effectively.
• Highlight the need for a feedback loop to improve prompts.
• Establish clear goals and parameters for effective Al interactions.
• Defining session context ensures Al outputs are accurate, relevant, and aligned with user goals and constraints.

Key Talking Points Slide 59

• Context Importance: Outlines user role, audience, and desired goals upfront.
• Task-Specific Clarity: Detail what task needs completion and related constraints in the session.
• Formatting Preferences: Specify preferred formats for outputs (bullets, slides, etc.).
• Reducing Errors: Clear context minimizes hallucinations and irrelevant responses from AI.
• Collaborative Tool: Ensures alignment between users, teams, and Al capabilities.

Caveats Slide 59

• Avoid incomplete or ambiguous context definitions.
• Clarify that more context reduces the risk of inaccurate AI outputs.
• Address skepticism about the time investment required for context setup.
• Highlight that context-setting is critical for scaling complex tasks with Al.
• Designing reusable, shareable prompts for consistent results.
• Structured starter prompts align team goals and outputs, fostering consistency, clarity, and problem-focused Al sessions.

Key Talking Points Slide 60

• Reusable Prompts: Create prompts that can be applied across sessions and teams.
• Problem-Centric: Focus prompts on problems, not solutions, to ensure relevance with AI.
• Clear Format: Define tone, context, and output expectations for clarity with Al.
• Team Alignment: Keep prompts shareable to unify collaborative efforts with AI.
• Session Efficiency: Well-crafted prompts save time and enhance productivity.

Caveats Slide 60

• Avoid overloading prompts with unnecessary details.
• Clarify that prompts are starting points, not exhaustive instructions when using AI.
• Address concerns about maintaining flexibility in structured prompts.
• Highlight that reusable prompts improve over time with refinement and learning.
• Launching structured, focused Al sessions for effective exploration.
• Structured Al sessions, using defined prompts and external resources, drive better exploration and learning outcomes.

Key Talking Points Slide 61

• Session Goals: Kickstart exploration with clear objectives and structured during Al usage.
• Tools Available: Use Mural and Generative Al chatbots like ChatGPT or Claude to generate text analysis.
• Prompts with Context: Combine Persona YAML and external data for targeted sessions when using AI.
• Collaboration: Encourage team-based exploration to leverage diverse perspectives using AI.
• Outcome Focus: Prepare for subsequent class exercises by setting a strong foundation.

Caveats Slide 61

• Avoid starting sessions without sufficient data or structure with Al.
• Clarify that prompts need refinement as insights emerge during AI usage.
• Address potential challenges with unfamiliar Al tools.
• Highlight that context setting ensures relevance and accuracy when using AI.
• How context evolves and impacts Al response accuracy.
• Managing context effectively within Al tools ensures consistent, relevant responses over the course of interactions.

Key Talking Points Slide 62

• Initial Context: Clear starting parameters improve initial response quality with Al analysis.
• Token Limits: Al models forget earlier context as token limits are exceeded.
• Summarization Strategies: Summarize key points to maintain alignment when using AI.
• Prompt-Response Impact: Both contribute to token count and context retention when using AI.
• Adaptive Management: Continuously refine and reframe to maximize session value.

Caveats Slide 62

• Avoid overloading the context window with unnecessary details using AI.
• Clarify that token limits vary between Al tools, so check your product's functionality when using AI.
• Address misconceptions about Al retaining unlimited memory during use.
• Highlight the importance of summarization for maintaining relevance in Al analysis.
• Using external resources to enhance Al performance.
• Combining Al with external tools, like PDFs or real-time search, enhances relevance and decision-making accuracy.

Key Talking Points Slide 63

Al-Assisted Search: Tools like Perplexity provide near-real-time, accurate data to combine with AI.

• Document Integration: Upload domain-specific files (PDFs, images) for deeper context in AI analysis.
• Improved Focus: External resources sharpen insights and reduce errors when using with AI.
• Outcome Alignment: Ensures Al recommendations align with up-to-date knowledge when external data is present.
• Practical Examples: Demonstrate use cases of combining Al with external tools.

Caveats Slide 63

• Avoid assuming all Al tools can integrate external resources effectively.
• Clarify the importance of verifying data accuracy from external sources when using AI.
• Address concerns about privacy and data sharing when uploading files to AI platforms.
• Highlight that not all use cases benefit equally from external inputs and AI combinations.
• Structured data formats improve Al interaction quality.
• Structured data formats like YAML or JSON reduce ambiguity and improve clarity, making Al responses more actionable.

Key Talking Points Slide 64

• Beyond Markdown: Use structured formats like CSV or YAML for clarity in your Al analysis.
• Reduced Ambiguity: Using Al performs better with clean, well-organized data inputs since Al cannot account for data variances.
• Shareable Outputs: Enables consistent, reusable formats for collaborative work when using AI.
• Team Alignment: Keeps everyone on the same page with standard data practices when using AI.
• Scalable Approach: Structured data supports larger, more complex projects.

Caveats Slide 64

• Avoid using formats the team isn't familiar with when using AI.
• Clarify that structured data requires consistent maintenance and updates for AI accuracy.
• Address challenges in converting unstructured data into usable formats when using AI.
• Highlight the importance of data validation to avoid Al errors.
• Applying proven frameworks to product management challenges.
• Product management templates like Opportunity Solution Trees and Customer Profiles enhance problem-solving and strategy development.

Key Talking Points Slide 65

• Framework Variety: Includes tools like JTBD canvases and User Journey Maps.
• Opportunity Trees: Visualize pathways from problems to solutions.
• Customer Profiles: Map pains, gains, and jobs-to-be-done effectively.
• Collaboration Boost: Standard frameworks align teams on shared goals.
• Strategic Value: Enhances decision-making by providing structured insights.

Caveats Slide 65

• Avoid rigidly sticking to templates; adapt as needed.
• Clarify the importance of tailoring frameworks to specific use cases.
• Address skepticism about the time investment for building canvases.
• Highlight that templates are starting points, not solutions themselves.
• Enhancing Al prompts with established frameworks.
• Referencing product management frameworks within prompts guides Al towards delivering relevant, structured outputs.

Key Talking Points Slide 66

• Opportunity Trees: Use Teresa Torres' framework to explore ideas during AI analysis.
• Customer Mapping: Leverage Osterwalder's profiles for JTBD analysis by testing AI insights.
• User Journeys: Jeff Patton's maps visualize key touchpoints when Al provides customer insights.
• Positioning: Apply Geoffrey Moore's template for product differentiation using generated prompts.
• Hypothesis Framing: Use Tim Herbig's UX templates for testable ideas using Al integration.

Caveats Slide 66

• Avoid overloading prompts with multiple frameworks at once.
• Clarify that Al output depends on how frameworks are referenced.
• Address potential misalignment if frameworks are misunderstood by Al tools.
• Highlight the iterative nature of refining outputs using prompts with Al solutions.
• Creating consistency and collaboration with templated prompts.
• Templated prompts provide clarity, structure, and scalability across projects, enabling consistent results for teams.

Key Talking Points Slide 67

• Consistency in Output: Repeatable structures lead to reliable results when working with various prompt types.
• Collaboration Ready: Templates align team efforts around shared frameworks and concepts.
• Scalable Solutions: Adapt prompts for various projects without starting over.
• Time Efficiency: Save time by leveraging pre-defined formats for analysis.
• Team Unity: Keeps stakeholders aligned through a shared process when using AI tools in a business function.

Caveats Slide 67

• Avoid overly rigid templates that limit flexibility with integrated AI solutions.
• Clarify the need to adapt templates to specific project contexts during scaling.
• Address concerns about over-dependence on templated formats as solutions.
• Highlight the role of iteration in improving prompt templates to ensure continuous use.
• Brainstorming personas' challenges, benefits, and objectives. Identifying pains, gains, and jobs-to-be-done clarifies personas' needs and aligns solutions with actionable insights.

Key Talking Points Slide 68

• Activity Goals: Understand personas' challenges and benefits for problem-solving.
• Group Brainstorming: Use collaborative tools like Mural to capture insights with AI features.
• JTBD Framework: Define key jobs and connect them to user goals with Al.
• Prompts for Clarity: Use optional prompts to guide discussions effectively with Al in a professional setting.
• Outcome-Oriented: Focus on actionable outputs for subsequent exercises.

Caveats Slide 68

• Avoid fixating on minor details during brainstorming related to artificial intelligence.
• Clarify that pains, gains, and JTBD must be evidence-based during analysis and research.
• Address time constraints by setting clear activity limits for scalable AI models.
• Highlight the importance of connecting insights to real-world outcomes in practical AI use cases.
• Exploring Al's role in product management with deeper insights.
• Day 2 focuses on applying Al concepts to product management challenges through frameworks, strategies, and actionable exercises.

Key Talking Points Slide 69

• Deep Dives: Build on Day 1 foundations with advanced Al strategies and models.
• Hands-On Learning: Participate in exercises to connect theory with practice when building Al based analysis and products.
• Framework Application: Leverage tools like JTBD and personas in real-world contexts for applicable learnings.
• Collaborative Focus: Encourage team discussions for shared learning and insights across multi-disciplinary teams.
• Outcome-Oriented: Drive actionable insights and product management solutions when using AI.

Caveats Slide 69

• Avoid rushing through advanced topics without addressing questions about AI design and concepts.
• Clarify connections between Day 1 and Day 2 objectives for clear understanding of the curriculum.
• Address potential apprehension about tackling complex concepts using appropriate support materials.
• Highlight the importance of iterative learning throughout the session using appropriate learning patterns.
• Define and articulate underserved needs for clarity.
• Clear problem framing helps teams focus on underserved needs, aligning efforts across stakeholders and teams.

Key Talking Points Slide 70

• Define Needs: Articulate specific user problems to focus efforts in your AI analysis.
• Alignment Tool: Align stakeholders on problem priorities when using artificial intelligence.
• Customer Storytelling: Use narratives to connect with stakeholder perspectives and improve alignment.
• Prioritization Aid: Focus engineering and resource allocation effectively to highlight Al strengths.
• Foundation for Solutions: Establish a clear path for strategic outcomes by aligning team efforts.

Caveats Slide 70

• Avoid generalizing problems without evidence or data.
• Clarify the distinction between symptoms and root causes.
• Address potential misalignment in stakeholder priorities.
• Highlight the iterative nature of refining problem statements to improve accuracy and outcomes.
• Identify, refine, and articulate the central challenge regarding Al and design.
• Identifying the core problem ensures teams address the right challenges and align solutions with real-world needs.

Key Talking Points Slide 71

• Focus on Specificity: Define a clear, actionable problem statement when designing Al projects.
• Collaborative Input: Involve stakeholders to refine understanding and use cases.
• Data-Driven Approach: Use evidence to validate problem assumptions.
• Customer-Centricity: Ensure the problem aligns with user needs at launch.
• Iterative Refinement: Continuously improve problem clarity as new insights emerge.

Caveats Slide 71

• Avoid framing vague or overly broad problems when designing AI use cases.
• Clarify that problems must be validated through research with artificial intelligence in mind.
• Address concerns about diverging perspectives among stakeholders with open communication.
• Highlight the importance of framing problems that are solvable and measurable when designing AI.
• Communicate the problem to align teams and stakeholders during AI focused projects.
• Framing problems effectively aligns teams, prioritizes efforts, and focuses stakeholders on solving the right challenges.

Key Talking Points Slide 72

• Storytelling Approach: Use narratives to convey the problem's impact.
• Outside-In Focus: Start with the customer's perspective for better alignment during development of your AI strategies.
• Strategic Prioritization: Guide engineering and design efforts effectively for optimal outcomes.
• Cross-Team Alignment: Ensure all stakeholders share the same understanding across all projects.
• Outcome-Driven: Connect problem framing to measurable business outcomes.

Caveats Slide 72

• Avoid skipping stakeholder input during the framing process.
• Clarify that framing should remain flexible for refinement and continuous improvement.
• Address potential resistance to prioritizing problems in a professional setting.
• Highlight the risks of misaligned problem definitions when designing AI projects.
• An example of framing a clear, actionable problem.
• A well-framed problem example shows how to define user challenges, motivations, and obstacles to align team efforts.

Key Talking Points Slide 73

• Persona-Based Framing: Use personas to ground the problem in real-world scenarios and focus the outcome.
• Clarity in Challenges: Define the “why” behind user difficulties for a comprehensive approach.
• Root Cause Identification: Highlight underlying issues like lack of awareness or adherence during the design process.
• Emotion Connection: Capture user frustrations to humanize the problem.
• Alignment Focus: Link the problem to broader team goals and outcomes for design excellence.

Caveats Slide 73

• Avoid assuming the example fits all scenarios and adapt as needed.
• Clarify that personas require validation for accurate framing of project goals.
• Address potential overemphasis on emotional aspects without data support for artificial intelligence.
• Highlight the importance of solving root causes, not symptoms in your efforts.
• Using prompts to explore personas' challenges and goals with artificial intelligence.
• Strategic prompts help teams uncover key pain points, outcomes, and barriers faced by personas to drive effective solutions.

Key Talking Points Slide 74

• Identify Pain Points: Use prompts to explore persona challenges deeply and resolve issues.
• Define Outcomes: Focus on goals the persona is striving to achieve through strategic actions.
• Uncover Barriers: Highlight obstacles preventing success and formulate insights.
• Empathy Focus: Understand how personas feel about their problems to create a human connection.
• Iterative Exploration: Use prompts to refine understanding continuously.

Caveats Slide 74

• Avoid generic prompts that lack persona-specific context for unique and specific solutions.
• Clarify the role of prompts in guiding discussions, not dictating outcomes for a transparent project.
• Address potential biases in persona-driven assumptions.
• Highlight the need for team alignment when using prompts for a unified product and design process.
• Define a problem worth solving for impactful outcomes in a professional format.
• This activity encourages teams to document a clear, validated problem statement based on persona pains, gains, and jobs-to-be-done.

Key Talking Points Slide 75

• Activity Goal: Document the top problems for user and buyer personas for the product
• Problem Worth Solving: Focus on challenges tied to meaningful outcomes in an artificial intelligence project and rollout.
• Collaborative Framework: Use whiteboarding tools to capture ideas and facilitate understanding.
• Persona Connection: Link problems to the target personas' needs for focus and clarity on project design.
• Outcome Alignment: Articulate a problem that supports measurable results with realistic design.

Caveats Slide 75

• Avoid framing problems without supporting evidence for a data driven process.
• Clarify that problem statements should be concise and actionable for easy problem solving.
• Address potential misalignment in team perspectives and promote communication.
• Highlight the importance of revisiting and refining problem statements as needed.
• Moving from problem identification to solution exploration through thoughtful design.
• Transitioning from understanding the problem to exploring solutions requires structured approaches to ensure alignment with user needs.

Key Talking Points Slide 76

• Problem Clarity: Start with a well-defined, validated problem.
• Exploration Frameworks: Use frameworks to ideate structured solutions for artificial intelligence systems.
• Iterative Testing: Test hypotheses to refine potential solutions early and often in the design process.
• Stakeholder Alignment: Ensure team buy-in before advancing the design to the next level.
• Outcome Orientation: Keep solutions focused on delivering user value during product rollout.

Caveats Slide 76

• Avoid jumping to solutions without full problem validation during AI based designs.
• Clarify that initial solutions may require multiple iterations for optimal results.
• Address potential misalignment in team solution priorities through consistent communication.
• Highlight that solutions must be feasible and measurable during designs.