Kris Mihalic

I just finished reading this post below by Aakash Gupta and Colin Lernell. I really appreciate the thoughtfulness regarding the market right now in looking for a job, as well as the actionable recommendations provided. In trying to discern the things that differentiate PMs in the marketplace, I found it a breath of fresh air. #JobSearch #ProductLeadership

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In a world that’s constantly evolving, the role of product management has never been more critical. It’s not just about building products; it’s about creating solutions that deliver outcomes and truly resonate with our users. 🚀 Looking forward to spending a day with fellow Chief Product Officers and product leaders sharing best practices, and exploring innovative strategies that can elevate our teams and organizations. Collaboration is key, and I believe that by learning from each other, we can push the boundaries of what’s possible in product management. https://lnkd.in/gfhvKajP #ProductManagement #CPO #Leadership #Innovation #Collaboration #ContinuousLearning

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I’ve spoken to 50+ CMIOs/CIOs over the past year. Here are 5 thoughts about AI Scribes I'm hearing that many people are NOT talking about👇 1️⃣ Distribution matters more than Product. Most are just buying Nuance because it’s easier to buy. It’s a known entity. It’s an add-on to the Microsoft contract which means less internal hoops. Key question for who wins long-term: will the startups get distribution faster than the incumbent gets innovation? Will the EHRs eventually just release their own native AI scribes? (my belief is yes… which Oracle/Cerner has already done). 2️⃣ There is a clear “phenotype” for the clinicians who actually use AI Scribes: it’s clinicians who don’t care to have control over how their notes look and sound. But for those who really care about controlling the output? Those folks will keep writing their own notes. 3️⃣ The impact of AI scribes on medical education and trainees is very unclear. Some believe trainees should get exposure to AI scribes early on. Others worry that trainees who don’t learn to write notes are going to miss a critical skill that helps clinicians think. And what happens if there’s a cybersecurity incident and the EHR goes down? Will future clinicians not know how to document manually? 4️⃣ ROI is still hard to truly measure. Few see any improvement in “productivity” (i.e. more patients seen). The real value is in improving clinician well-being. However it’s hard to prove AI scribes are lowering staff churn since that is a lagging indicator many steps away and affected by many other factors. 5️⃣ The per clinician pricing model used by most vendors breaks down at scale. If I have clinicians who would only use the AI scribe for 30% of their patient encounters, am I going to buy a license for them? Probably not. What other less talked about learnings or insights are you hearing behind the scenes?

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What do you think about AI in senior care? Personally, I think we have to be careful with it. When AI presents itself as human, it can be confusing for seniors who may not have strong digital literacy skills. In fact, if they think they're talking to a person and not an AI chatbot, it can be dangerous if they're having a medical emergency or issue. However, there are some helpful use cases. I think Kristen Fischer's exploration of AI here is really interesting. "Artificial intelligence may be a useful communication tool to help older adults with cancer communicate with their doctors and have more of a say in their treatment," she says. AI can provide more context or explanation about certain treatment plans and translate the patient’s needs to clinicians in situations where the patient doesn't feel understood or heard. AI will never replace professionals, but it could help patients and clinicians better understand each other. Feel free to share your thoughts on this—I'd love to know if you think AI would be an effective tool for these situations. #AI #SeniorCare #FutureOfHealthcare

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As a seasoned design leader at this stage in my career, I’d like to share a reflection of one of my greatest challenges—and privileges—navigating the delicate balance between leveraging well-established design patterns and crafting new, innovative product experiences. Why the balance matters: Tried-and-true design patterns are powerful because they provide familiarity and usability for users while reducing cognitive load. They’re a testament to the collective wisdom of our industry, refined over time through countless iterations and user feedback. However, relying solely on established patterns can sometimes limit creativity and lead to stagnation in product innovation. This is the dark side of established design systems. On the other hand, designing new flows and experiences allows us to break boundaries and chart new paths. This is where creativity shines, where we sharpen our skills and apply design principles in novel ways to solve evolving user needs. Yet, this comes with its own challenges—higher risk, potential user friction, and the need for extensive validation and iteration. As a design leader, the key is balance: 1. Master the fundamentals – Deep knowledge of design principles and established patterns is critical. These are the foundation upon which we innovate. 2. Push new horizons with intention – When we step into uncharted territory, it’s essential to root our explorations in a strong understanding of user goals, behaviors, and context. 3. Foster collaboration and experimentation – Building something truly innovative often requires stepping outside our comfort zone and collaborating across disciplines. 4. Measure and adapt – Whether we’re refining a pattern or creating a new one, data and user feedback are our guideposts to ensuring success. For me, the joy of designing the Akaio platforms lies in mastering this balance: ensuring products are intuitive and accessible while also delivering delightful, groundbreaking experiences. It’s a constant interplay of discipline and curiosity, structure and exploration. #designleader #innovation #exploration #flow #creativity #leaderrship #balance Check out a live use case of my latest product build here:

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How do you know if you’re ready to go from product feedback/research to outcomes validation?    From a product perspective, we ask if our clients have received end-user feedback or answers to the following 10 questions. If there isn’t clarity (or quality) in their answers, then additional research should be directed there before entering into more rigorous clinical outcomes validation. Here they are! 1. What is your understanding of the problem or issue we are trying to address? 2. How does this issue impact you and those around you emotionally, physically, financially? 3. Can you give us an example of how you encounter this issue? Walk us through the situation. 4. How might you quantify the impact this issue has on your life?  What does it cost you? 5. Imagine if you could eliminate this problem; what does that world look like to you? 6. What must be true in a solution that would have a meaningful impact on your world? 7. Would you be willing to pay for this solution? Why or why not? 8. What, do you believe, are the negative consequences to pursuing a solution like the one you described? 9. Who else do you feel we should talk with to get a better understanding of this issue or opportunity? 10. What else do you think we should know about the problem or solution as you imagine it? We then ask (or analyze) how well the current product aligns to these answers. Perfect alignment is a pretty good clue that you might be ready from a product perspective. Business and regulatory factors will need to be addressed next! Longer article coming soon!  Manos Health Rishab Shah

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Ever wondered how Apple consistently creates such buzz around their product launches? As a PM, I'm fascinated by their approach, and I've just published a blog post breaking down their strategies. It's not just about the shiny new gadgets – it's about storytelling, building anticipation, and creating an experience. Check out my blog post for the full scoop #productlaunch #marketing #apple #storytelling #tech

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Reimagining Healthcare Workforce Platfforms: Turning Capital Into Labor The future isn’t just about filling shifts. It’s about scaling labor intelligently, driving better outcomes for systems, staff, and patients alike. Andreessen Horowitz and Alastair (Alex) Rampell reinforced this Vision in a recent post and it applies to the next phase of healthcare workforce evolution. Healthcare workforce marketplaces plus AI are at the tipping point of transformation, evolving into systems of record that don’t just manage labor—they optimize it. Much like EHRs centralized patient care data, these marketplaces can centralize workforce operations, aligning talent supply with clinical demand. But there’s a bigger opportunity here: turning capital into labor. Here’s what I mean. Historically, industries (including healthcare) have focused on enterprise computing tasks—streamlining data entry, compliance, and back-office functions. While valuable, this approach often stops short of transforming the real-world, repetitive processes that make up the bulk of work in healthcare. Think beyond enterprise software. The next frontier lies in leveraging embodied AI and workforce marketplaces to automate and enhance labor-driven processes, transforming capital investments into productive labor outputs. For healthcare, this means turning staffing costs into scalable, dynamic systems that deliver value far beyond filling shifts: 1. Dynamic Labor Matching: Capital invested in marketplace platforms enables real-time matching of labor supply with patient demand, replacing outdated scheduling models with predictive, automated systems. 2. Workflow Automation: From credentialing to compliance and shift bidding, embodied AI can streamline traditionally manual tasks, freeing human resources for higher-value work. 3. Labor as a Strategic Asset: Workforce marketplaces shift the focus from static staffing budgets to proactive labor deployment, ensuring that every dollar invested in labor drives outcomes and efficiency. It is about the billions of repetitive, planned tasks that AI can improve. In healthcare, that means automating everything from staffing logistics to clinical task assignments, creating a horizontal system of engagement for labor (think Zendesk) that integrates seamlessly with vertical, workflow-specific platforms (think Toast for staffing operations). The result? Hundreds of billions in untapped market potential—and a healthcare workforce model that transforms how care is delivered. By turning capital into labor through smarter marketplaces and automation, we don’t just solve staffing challenges; we redefine what’s possible in healthcare operations and ShiftMed is leading the way with health systems moving beyond tired models. #capitalintolabor #systemsofrecord #healthworkforce #aiworkforce #healthsystems #hospitals #cno #hospitalceo #healthcareinnovation

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This week's Product Management takeaway🤗: Stakeholders aren't just anyone - they're individuals/groups impacted by or interested in your product. 3 Key Stakeholder Management Lessons: Lead, don't follow Prioritize, don't please Collaborate, don't dictate Effective stakeholder management = Successful product launch! Share your stakeholder management experiences! #StakeholderManagement #ProductManagement #Leadership #ProductLaunch"

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How do you get a group of 60 clinicians, health-tech engineers, and healthcare practitioners to come up with ground-breaking healthcare AI use cases and functional demos in 36 hours? I hosted Out-Of-Pocket's first healthcare AI hackathon at IDEO for an evening of rapid-fire brainstorming and concept sketching. Teams brainstormed use cases and problem areas before going wild into divergent concepting. Along the way, I shared my thoughts on the Creative Recipe of how to design AI successfully in healthcare, including: 1️⃣ Finding new feelings for the AI collaboration: As AI takes on forms beyond the chatbot, what emotions do we want to design at the moment of collaboration and what will that teach the user? 2️⃣ Fostering empathy in the simulation: Multiple studies has shown that AI is effective at crafting compassionate messaging for patients, especially in comparison to providers that are working under heavy patient loads and facing burnout. How can AI light a path on how we can be more empathetic with each other through simulation? 3️⃣ Planning for systems-level impact: In a world where for every AI startup looking to help providers speed up Prior Auth, there is a competing AI on the payer-side being trained to deny claims at the same speed. How can we ensure AI actually pushes for systems-level impact instead of just making one side of a broken fee-for-service system temporarily faster? From these foundations, teams spent the next two days furiously coding, designing, and interrogating. I had a great time helping shape the pitches and bringing a human-centered design to the projects. My favorite pitches? 🚑 hospital bed capacity management through immediate AI transcription of EMS calls 🤖 using AI to navigate pharmacy IVR phone trees to get the most up to date medication stock 📽 helping nurses make ADL reports using multimodal voice and video observation 🧪 using clinically informed AI interpretation to decrease patient anxiety around lab results releases as consequence of the 21st Century Cures Act 📝 automatic medicaid eligibility and form filler using your personal bills and forms you have on hand Shout-out to Nikhil Krishnan and Danielle Poreh for instigating and collaborating on a fun weekend. And to other hackathon mentors Luke Van Seters, Payal Patnaik, MPH, and Matthew Sakumoto! And IDEO AI design facilitators Angela Kochoska and Ziyuan(Zoey) Zhu #hackathon #ideo #design #healthcare #innovation

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As the CEO of an AI-driven health-tech company, Labops, I’m constantly evaluating how technology can create the most impact. While Large Language Models (LLMs) are making headlines, I believe Small to Medium-sized Language Models (SMLs) deserve more attention—especially for businesses operating in niche domains like healthcare. Why do I say this? 1️⃣ Tailored Solutions: In healthcare, where precision and specificity are critical, SMLs (40–50B parameters) are more adaptable to domain-specific needs. 2️⃣ Cost-Effectiveness: For startups, running and fine-tuning a SML is more economical than relying on large, resource-intensive LLMs. 3️⃣ Ownership & Flexibility: Open-source SMLs allow businesses to build and deploy models on their terms, giving greater control over data and performance. At Labops, where we’re building solutions to transform diagnostic services, the ability to leverage AI that aligns with our unique requirements is crucial. SMLs strike the right balance between scalability and practicality, making them a natural fit for startups like ours. LLMs have their place, but they’re not always the answer for every use case—especially in sectors where focus and efficiency matter more than sheer size. If you’re in healthcare or another specialized industry, I encourage you to explore the potential of SMLs. They might just be the competitive edge you’re looking for. What’s your perspective on SML vs. LLM? Let’s discuss! 💬 #AI #HealthTech #LLM #SML #Startups #Innovation #Labops

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Just wrapped up a fantastic course in Product Operations! As someone deeply invested in optimizing product teams, this course offered a comprehensive dive into the fundamentals and advanced strategies essential for making product teams thrive. The demand for skilled Product Ops pros is growing fast, and this Product-Led Alliance course by Chris Butler captured exactly why this role is indispensable. Key highlights: 🔹 Mastering Core Terminology & Roles – Clarifying expectations and responsibilities so that every Product Ops professional can deliver maximum value. 🔹 Community-Centric Product Management – Practical insights on applying product management expertise to foster strong, engaged product communities. 🔹 Experimentation & Data – Tactics for designing experiments and using data to inform programs and elevate team performance. 🔹 Building World-Class Communities – A blueprint for driving collaboration across product, process, and people. Excited to bring these insights into my work and help drive the impact of Product Ops forward! #ProductOperations #ContinuousLearning #ProductManagement #ProductOps #Leadership

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There is so much hype around AI today, it is refreshing to see examples where the technology is making a tangible real-world impact. Healthcare is one such area, where early signs are very promising. AI is helping in areas ranging from reducing errors in breast cancer screening to greatly expanding access to radiology services within emerging economies. Check out this must-listen conversation below with the CEOs of Celesta Capital companies Whiterabbit.ai and 5C Network to hear more about this exciting area of practical AI advancement.

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Product Management Tip of the Week: As AI continues to transform product management, it's crucial to address the ethical considerations that come with it. Here are some key tips to guide you: 1. Bias and Fairness: Ensure that your AI systems are designed and trained to minimize bias. Regularly audit and test for fairness to avoid perpetuating discrimination. 2. Transparency: Be clear about how AI is being used in your products. Transparency with users and stakeholders builds trust and ensures accountability. 3. Privacy and Security: Safeguard user data by implementing robust privacy and security measures. Make sure that AI applications comply with data protection regulations. 4. Informed Consent: Obtain explicit consent from users when collecting and using their data for AI applications. Users should be aware of how their data will be used and have the option to opt-out. 5. Human Oversight: Maintain human oversight in critical decision-making processes. While AI can enhance efficiency, human judgment is essential for ethical considerations. Let's discuss! How do you incorporate ethical AI practices in your product management strategies? Share your insights and experiences in the comments below. 👇 #AI #Ethics #ProductManagement #Innovation #TechResponsibility

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Looking forward to sharing how we at basys.ai are leveraging Generative AI to tackle healthcare’s biggest challenges. PS: Also looking forward to sporting my basys vest in the #BayArea PPS: What I’m not looking forward to is the second cross-country flight in less than a week. #GenAI #BasysAI #GenerativeAI

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🤯 Imagination in Action gets beyond the AI hype . Own your own digital persona and decide how your data is used. We’re looking at new business models here and new design paradigms. Awesome demo Anna Kazlauskas ! ProductRX.org Healthero.io #GenAI #ImaginationInAction #MITFORGE2024

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💡This is not just any ordinary feedback...this is Adam’s feedback💡 Building a product can be overwhelming. You’ve got a vision, but sometimes you need an outside perspective to guide you through the noise, to make things clearer and easier. I’m here to help ... 🧠 crafting intuitive and delightful interactions 🔎 aligning your product with customers needs 🎯 developing positioning that resonates. I provide actionable feedback that’s grounded on a deep understanding from years of experience, built on collaboration, and always with the outcomes you need in mind. Let’s work together to make your product the best it can be. Because you're not alone in this. First person to take me up on this gets a 50% discount! #Founders #ProductGrowth #Guidance #Teamwork #ProductDevelopment #FeedbackMatters

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LLMs are great, but we need to broaden our perspectives on what AI can do for humanity. Such as predictive healthcare and disease prevention, smart agriculture, or education personalization – the list goes on. If we only look at AI from the narrow scope of LLMs, we’re hamstringing our creative understanding of what’s coming and how to prepare. This is exactly what HumanX is all about: broadening our viewpoints and understanding of AI. I hope to see you there!

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