Talking AI

How is the growing world of AI agents reshaping enterprise systems? In this episode of Talking AI, host Matt Paige is joined by Praveen Gunasekaran, Senior Director and Chief Architect at Visa, and Omar Shanti, CTO of HatchWorks, to explore the possibilities of agentic systems and their impact on software development.Together, they look at the power of agentic systems—technologies that can autonomously make decisions and execute changes in business processes without human intervention. This shift from deterministic to probabilistic systems opens up new opportunities for software developers to create more dynamic and responsive products.One of the key points in this episode is that agentic systems could help to democratize access to tech, enabling people with minimal coding experience to harness more advanced tools. But with that comes the question of governance. Omar talks about ensuring accountability and accuracy while preventing potential risks associated with AI agents. Curious about how AI agents are changing the landscape of automation and real-time systems? Tune in to discover the future of multi-agent systems, real-time processing, and AI-driven innovation with Praveen Gunasekaran and Omar Shanti!Key moments:How Praveen defines agentic systems and thinking How the agent model could lead to greater democratization of technologyWhy governance is essential for ensuring accuracy How measures like "AI judges" and breaking tasks into manageable parts could be the key How “an agent mesh” could become a new architecture for AI systemsAre APIs still the standard that the industry will follow?Praveen’s advice for making decisions on architecture and how agentic systems might change thatKey links: Connect with Praveen on LinkedIn

Could AI evolve from its position as a handy assistant to a fully-fledged teammate in the workplace? Patrick Lynch, PhD, AI Faculty Lead at Hult International Business School, and Omar Shanti, CTO of HatchWorks, join host Matt Paige to explore the AI industrial revolution we’re seeing and how human-AI collaboration could drastically affect the way teams collaborate. Patrick takes us through the "four faces of AI" - mechanical, analytical, intuitive, and empathetic - highlighting the progression of AI maturity and what it could mean for the future of work. This framework provides a valuable lens through which leaders can understand and leverage AI in the future.The episode also touches on cutting-edge AI applications, such as Hume AI's voice models, which can detect and respond to human emotions, opening up new possibilities for AI-human interaction in various fields, from customer service to therapy and education. Curious about how AI is becoming your new co-worker? Listen to Talking AI, where we explore how AI is turning into a real teammate at work. Subscribe on your favorite podcast platform and join us as we discuss how this technology is changing our future!Key moments:Why we’re seeing an AI industrial revolutionHow we can start thinking of AI as co-workers The four faces of AIA demonstration of Hume AIHow AI is starting to recognize emotionPotential use cases for AI co-workersThe challenge of coding charisma into AIHow adoption of AI could be affected by inaccurate resultsWhich cultures are best suited to using AIKey links: Visit Patrick’s websiteTEDx TalksConnect with Patrick on LinkedInConnect with Omar on LinkedIn

Change is often met with resistance, but Neil Goodrich, Chief Innovation Officer at Envista Forensics, challenges us to rethink our approach to innovation in this episode of Talking AI. Together with host Matt Paige, Neil explores where new AI tools can help to lead innovation and how small incremental changes can drive larger transformative projects. We look at how AI can boost efficiency at different stages of an innovation process, from creating faster prototypes to democratizing access to data insights across teams. Matt and Neil swap ideas on how AI could impact things like customer feedback, everyday work, job displacement, and education (for better or worse). A key takeaway point from this episode is the importance of adaptability – a skill that we will all need as tech like AI continues to evolve rapidly. Key moments:How AI can be involved in innovation projects big or small Neil provides the backstory to the DePaul innovation labsWill AI become an everyday tool like email is today?How AI could change different elements of an innovation processWhat excites and concerns Neil about the future of AIHow AI could impact jobs and educationKey links: Envista ForensicsConnect with Neil on LinkedIn

Generative AI may feel like the new kid on the block, but it's not as different from traditional machine learning as you might think.In this episode of Talking AI, we’re joined by Simba Khadder, Co-Founder & CEO of Featureform, and Omar Shanti, CTO of Hatchworks AI, to discuss how generative AI builds upon established ML principles and infrastructure. We explore the misconception that it exists as its own little island, when in reality, we see a clear continuity between classic ML and newer AI technologies.Simba and Omar break down the unique aspects of GenAI, such as prompting and large language models (LLMs), while also highlighting the shared foundations with traditional ML. They also touch on the evolution of retrieval augmented generation (RAG), the ML vs. GenAI lifecycle, and what MLOps teams should consider when it comes to driving value in a business.Want to stay ahead in the fast-moving world of AI? Tune in to Talking AI where we break down the latest trends and tools in Generative AI, MLOps, and more. Subscribe now, and don't miss out on practical insights from industry experts. Let’s transform your data into real business impact!Key moments:The similarities and differences between generative AI and traditional machine learningHow prompts differentiate LLMs from earlier transformer modelsThe challenges of implementing AI in production versus creating pilot projectsHow RAG has evolved and what it could mean for the future The importance of data as the core foundation for both traditional ML and generative AIHow feature engineering in ML relates to embeddings in LLMsHow an ML lifecycle differs from a GenAI oneKey links: Featureform Connect with Simba on LinkedIn

Does generative AI have a place in the highly regulated world of life sciences, and can it produce value without compromising patient safety?In this episode of the Talking AI podcast, host Matt Paige sits down with Matt Lewis, Global Chief AI Officer at Inizio Medical, to explore the delicate balance between innovation and risk in healthcare AI.Matt brings a wealth of experience from his role at Inizio Medical, a powerhouse in the life sciences industry that balances scientific knowledge with cutting-edge technology like AI to transform medical communication and content. He shares invaluable insights on how AI is transforming pharmaceutical research, biotech advancements, and medical device development. Matt reveals Inizio’s strategy for prioritizing AI use cases, explaining why there's no one-size-fits-all approach in such a complex field. He also discusses how AI can save time in creating patient summaries and why personalization and custom AI tools are needed to produce complex content. Key moments:Generative AI's potential in life sciences and the associated risksHow augmented intelligence can enhance decision-making and improve patient outcomesMatt’s dual role in improving internal operations and supporting clients in AI adoptionHow to identify and prioritize AI use cases unique to each organizationPractical applications of AI and how they can save time and improve understanding The limitations of off-the-shelf AI tools like ChatGPT and the need for tailored solutionsWhy personalization in AI is important to provide tailored content Key links: Inizio’s WebsiteConnect with Matt on LinkedInThe NeuronOpenToolsSuperhumanOne Useful ThingThere’s An AI For ThatRegulated industries white paper Conor Grennan (Chief AI Architect, NYU) and Matt Lewis co-authored

In this bonus episode of Talking AI, Omar Shanti, CTO of HatchWorks AI, breaks down how LangChain’s abstractions have both helped and hindered AI innovation.He explains why these tools, while useful for quick starts, can sometimes make simple tasks harder as projects scale. The conversation highlights where LangChain shines and where it falls short.Viewers will hear insights on why prompt engineering and tuning are more challenging than building agent tools. Omar shares how over-abstraction can cause issues when taking projects into production, leading many to rethink their toolkits.If you’re working with LangChain or similar abstraction tools, this episode gives you practical advice on avoiding common pitfalls and understanding when these abstractions might not serve your needs.Key Moments:Introduction to LangChain’s abstractionsWhat is abstraction?LangChain’s pros and consChallenges with LangChain in productionObservability and orchestrationHow much orchestration do you need?Final thoughts on using LangChainKey links: HatchWorks AIConnect with Omar on LinkedIn

Is AI-generated content really good enough to compete in the highly competitive world of search engine optimization? This was a question that Tim Hanson had early on in his AI journey, as many of us were experimenting with ChatGPT and other tools with varying results. His solution? Penfriend.ai – a tool that generates articles based on proven content strategies without the need for traditional prompting. As Co-Founder and Chief Creative Officer, Tim joins the Talking AI podcast to delve into the world of AI-powered content and how Penfriend avoids the dreaded “AI wrapper” label. We hear Tim’s journey of developing Penfriend, inspired by his background in SEO and experience constantly adapting to Google’s algorithm tweaks. He tells host Matt Paige about the top mistakes he’s seen marketers make when using AI, and how his solution is built to mimic the multiple complex decisions a human makes before writing an SEO article. Tim's approach demonstrates that successful AI integration goes far beyond simple prompts, involving complex workflows, proprietary data, and a nuanced understanding of the target audience. Key moments:Creating value with an AI solutionThe importance of effective prompting and not overloading AI with too many tasksComparison of human decision-making in blog creation vs. using a single AI promptPenfriend’s approach to using different AI models for specific tasksThe non-linear process of keyword research and title selection in PenfriendHow Penfriend uses different prompts for various blog sectionsDiscussion on how AI is affecting SEO practicesThe biggest challenges and lessons learned when creating PenfriendWhat Tim’s most excited about in the future of AI content creationKey links: PenfriendConnect with Tim on LinkedIn

Gen AI promises to completely transform our world, from how we work to how we live. But do the core first principles in product management and strategy change with this new technology? Join Matt as he digs into this question with Uday Kumar, Principal - Data and AI Product Management at Metashore. Uday shares his insights on maintaining core principles in product management while leveraging the new tools and technologies offered by generative AI. He emphasizes that while the fundamentals of understanding customer needs and solving problems remain unchanged, generative AI presents a new and compelling toolset. They also discuss the potential of generative AI to revolutionize sectors like healthcare, fintech, and education by making complex technological solutions more user-centric and effective and highlight the importance of 'falling in love with the problem'—spending significant time understanding the issue before looking at the tools available to solve it. The conversation also explores how organizations can start integrating generative AI into their operations. Key moments:Gen AI and product strategyFundamentals of project management in the age of AIChallenges and opportunities with gen AIImplementing gen AI in organizationsData considerations and security in AI Strategic implications of gen AIThe future of AI Agents and project managementHow to get in touch with Uday Key links: MetashoreConnect with Uday on LinkedInMentioned in this episode:Gen AI Innovation WorkshopGenerative AI is revolutionizing industries, staying ahead means not just understanding its capabilities but actively leveraging them. This episode dives into Hatchworks' cutting-edge Generative AI Innovation Workshop, designed to equip businesses with the knowledge and tools needed for success in this transformative landscape. Join us as we explore: 1. Introduction to Generative AI: An overview of how generative AI is reshaping industries and why it's critical for businesses to adapt. 2. Hatchworks' Innovation Workshop: A detailed look into our full-day immersive workshop focused on generative AI. Discover how we combine learning, hands-on ideation, and practical building activities to enhance your understanding and application of AI in your business. 3. Foundational Concepts: Insight into the key concepts of generative AI and how they apply to your specific domain, paving the way for innovative thinking and application. 4. Use Case Development: Learn how we guide participants through the process of identifying and developing real-world use cases tailored to their business and industry needs. 5. Custom GPT Creation: An exciting peek into how we build a custom GPT model based on defined use cases, offering a glimpse into the tailored solutions that can drive your business forward. Whether you're looking to deepen your understanding of generative AI or seeking actionable ways to implement AI strategies in your business, this episode is a must-listen. Dive in with us at the Hatchworks Innovation Workshop and start unlocking the full potential of generative AI for your business.

What if the future of work is not just about humans collaborating with machines, but about creating entire organizations that operate through AI agents? In this episode of the Talking AI podcast, host Matt Paige unpacks this concept with Alan Wunsche, Managing Partner at Agentware AI and an expert in organizational change and emerging technologies. Together, they discuss the rise of "agentic organizations," where AI agents are not merely tools but integral members of the workforce, executing tasks autonomously and enhancing productivity.Alan draws parallels between the current AI revolution and historical technological advancements, such as the printing press. He explains how organizations are beginning to give AI agents more agency, allowing them to take on responsibilities and make decisions that were once the domain of human workers. They also discuss the challenges organizations face in implementing AI agents, the critical role of HR leaders in managing the transition, and lots more. Key moments:A look at ‘agentic organizations’ Comparison of AI’s impact to historical technological revolutionsA look at the transition of AI from assistant roles to autonomous agentsThe critical role of HR leaders in managing organizational change related to AI Insights into the challenges organizations face adapting to the advancementsWhat the potential displacement of knowledge workers due to AI advancements could look likeHow to equip employees with new skills to thriveThe evolving relationship between humans and AI agentsWhere people can connect with Alan Key links: Alan's BookConnect with Alan on LinkedInMentioned in this episode:Gen AI Innovation WorkshopGenerative AI is revolutionizing industries, staying ahead means not just understanding its capabilities but actively leveraging them. This episode dives into Hatchworks' cutting-edge Generative AI Innovation Workshop, designed to equip businesses with the knowledge and tools needed for success in this transformative landscape. Join us as we explore: 1. Introduction to Generative AI: An overview of how generative AI is reshaping industries and why it's critical for businesses to adapt. 2. Hatchworks' Innovation Workshop: A detailed look into our full-day immersive workshop focused on generative AI. Discover how we combine learning, hands-on ideation, and practical building activities to enhance your understanding and application of AI in your business. 3. Foundational Concepts: Insight into the key concepts of generative AI and how they apply to your specific domain, paving the way for innovative thinking and application. 4. Use Case Development: Learn how we guide participants through the process of identifying and developing real-world use cases tailored to their business and industry needs. 5. Custom GPT Creation: An exciting peek into how we build a custom GPT model based on defined use cases, offering a glimpse into the tailored solutions that can drive your business forward. Whether you're looking to deepen your understanding of generative AI or seeking actionable ways to implement AI strategies in your business, this episode is a must-listen. Dive in with us at the Hatchworks Innovation Workshop and start unlocking the full potential of generative AI for your business.

Amir Behbehani, Founder and Chief AI Engineer at Memra and former AI research scientist at Google and Meta, dives into the transformative potential of agentic AI. He unpacks the challenges of current AI systems, highlighting memory management and data orchestration. Amir introduces an emergent five-layer AI stack for enhanced functionality and discusses the significance of vector and graph databases. He envisions a future where AI reshapes the labor market, encouraging entrepreneurial endeavors through improved productivity and automation.