Innovation and the Digital Enterprise DragonSpears

Today we're sharing another insightful presentation from our most recent Innovative Executives League Summit, where Leon Chism, the Vice President of Engineering at Evolve, delivered a powerful lesson on collecting critical metrics for organization-wide success. As an experienced technologist and executive, Leon leads teams in unparalleled growth and innovation. In this presentation, Leon dives into how the collection of metrics examining speed and quality paired with human-driven evaluation and consistent reporting are the keys to success. 
In this episode, Leon first dives into DORA metrics and the significance of collecting and reporting those figures of speed and quality. He overviews the additional customization of the data he collects; in one example, he looks closely at aging reports to determine where processes are sticking and gains a live perspective on getting those tasks unstuck by allocating more resources. As the last place to observe metrics, Leon offers a compelling outlook on examining team balance and individual metrics. ("You want to measure the process and not the people.") In further support of optimizing processes and not people, Leon shares his perspective on leaderboards, comparison, and other human-oriented metric frameworks of note. 
In the final segment, Leon answers audience questions ranging from setting WIP limits (never too low), developer satisfaction, and key aspects of the communication around metrics to create a shared understanding and identify the value beyond the data. 
(02:16) – DORA metrics(07:39) – Aging Report(10:15) – Balance and individual metrics(12:22) – Metrics in the boardroom(13:35) – SPACE Framework(15:45) – Manual metric collection(17:19) – Developer satisfaction(18:48) – Gaming the metrics(20:26) – WIP limits(21:45) – Shared metrics and collaboration(26:00) – Hardware, software, firmware(27:05) – Communicating the metrics(28:26) – Value beyond the data
Leon Chism is the Vice President of Engineering at Evolve. As an experienced technologist and executive, he has led innovation and technology at Jellyvision, DialogTech, Rewards Network, Analyte Health, PowerReviews, and ORBITZ. He earned a bachelor’s degree from the Gies College of Business at the University of Illinois Urbana-Campaign.
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Today we’re sharing another insightful presentation from our most recent Innovative Executives League Summit, where Tanya Hannah discusses the roadmap to navigate the ever-evolving tech landscape. As a seasoned transformational business executive, Tanya offers the pillars needed to survive major shifts and thrive in the opportunities presented by them. 
In this episode, Tanya shares how critical a shared vision and strategy is in preparation. Teams cannot operate only with yesterday’s logic; they must look forward in anticipation of a pivot. Tanya offers how technologists can operate at the key intersection of short-term performance and long-term planning. She stresses the importance of a business perspective having a place in tech conversations and leaning into a skillset that embraces both.
As an award-winning technology leader, Tanya sees a path forward that focuses on data, talent, and vision. Tanya describes how data provides the competitive advantage businesses are looking for and how the ability to manipulate and understand the data is essential for the entire team. In focusing on the team itself, Tanya addresses how people are the key factor in remaining nimble (embracing in-house talent) and how the current shift in the labor environment points to the direction companies must anticipate. As remote and hybrid work continue, Tanya dives further into how focusing on talent is not only essential but teams and individuals must have a common understanding of the shared vision and strategy for success. While acknowledging the evolving technology and the often disruptive forces that shape the world today, Tanya Hannah offers a foundation to prepare for the future with tech and talent. 
(01:17) – A room of disruptors(02:36) – Adaptation(04:33) – Acting with yesterday’s logic(08:40) – Preparing to pivot(10:35) – Driving business with tech(13:02) – The win-win(14:26) – Understanding data is a must(16:10) – Focusing on people(21:55) – How are we planning?
Tanya Hannah has held executive and senior roles at Aon, Amazon, CSC, and King County, Washington. Tanya is a three-time CIO 100 Award winner and a 2021 National CIO of the Year. She’s a graduate of the University of Maryland.
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Podcast episode production by Dante32.

Today we’re sharing another insightful presentation from our most recent Innovative Executives League Summit, where Desiree Vargas Wrigley, Chief Innovation Officer of P33 Chicago and Executive Director of TechRise by P33, delivered a lesson in stakeholder-centric design. Desiree overviews the challenges Chicago’s underrepresented tech founders face and the process of developing TechRise’s initiatives. Highlighting the impact of TechRise and P33, Desiree presents a galvanizing picture of Chicago-based innovation that utilizes local money to generate a cycle of loyalty, growth, and investment that leans into Chicago’s advantages. 
In this episode, Desiree asks: “Who succeeds when you succeed?” As an enthusiastic believer in Chicago’s potential as an innovation hub, Desiree is also unafraid to point out its shortcomings, such as the lack of popularity in social ventures and lack of recycled capital. Demonstrating a stakeholder-centric design process with the case study of TechRise, Desiree shows how focusing on the key question of identifying all the stakeholders and all the solutions that benefit them drives success. She discusses sifting through bias for actual data and the extensive discovery process that went into developing the initiatives of TechRise. Desiree articulates how re-imagining pitch competitions (frequency, environment, etc.) has opened doors for founders by acknowledging the obstacles that women founders and founders of color often face. Desiree shares her interest in conscious capitalism and asks, “What else is possible?”
(1:15) – P33 Chicago(3:42) – Thinking about success(4:53) – A foundation for providing support and resources(6:57) – Stakeholder-centric design in four steps(9:36) – Funding women and founders of color(12:49) – TechRise(15:20) – Identifying solutions(16:35) – Weekly pitching(19:12) – Looking at impact(21:16) – What else is possible?
Desiree Vargas Wrigley is a serial entrepreneur with a track record of empowering women and people of color in the world of investing. Desiree is the Chief Innovation Officer of P33 Chicago and Executive Director of TechRise. She is a founding partner of The Josephine Collective and previously co-founded GiveForward. Desiree earned a bachelor’s degree in Latin American Studies from Yale University.
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Today we’re sharing another insightful presentation from our most recent Innovative Executives League Summit, where Maya Mikhailov, Chief Executive Officer and founder of SAVVI AI, discusses machine learning as a powerful toolkit of solutions. Comparing efficiency with and without AI, she highlights how the proper tool makes the difference and cuts through assumptions. Is Chat GPT the AI tool that makes Amazon such a success? No. It is Amazon's recommendation engine built on billions of data points. Looking beyond the hype of select functionalities of machine learning, AI applications abound.
In this episode, Maya introduces AI’s key practical uses, as she currently views the technology: decision automation, classification and prediction, large language models, and writing documentation and code. She emphasizes how natural language makes a query more accessible than programmatic language and shares example after example of increasing efficiency. Maya’s presentation sheds insight into where AI technologies are gaining traction (delinquencies) and continuing to grow in popularity (writing content). 
Maya dives into the importance of guardrails, building trust, and maintaining transparency when utilizing machine learning. She shares where AI is having massive success (summarizing data) and the problems that might emerge from AI reliance (“code bloat”). Maya discusses how when AI is wrong, it is still learning. Employing the right AI tool is essential for strategy and meeting goals.
(1:40) – Machine learning(4:45) – Examining data without AI(5:41) – AI-executed tactics(7:16) – Generative AI(9:14) – Hallucinating (10:57) – The practical realities(12:41) – Decision automation(15:28) – Classifications(17:10) – Predictions(18:15) – Large language models(22:03) – Writing documentation and code
Maya Mikhailov is the Chief Executive Officer and founder of SAVVI AI. She co-founded GPShopper, which Synchrony acquired in 2017. At Synchrony, Maya served as SVP and General Manager of the Direct-to-Consumer group (FinTech AI). She has been a speaker at CES Money 2020 and CTIA and featured in Bloomberg, CNBC, Forbes, Business Insider, and other outlets. Maya served as an adjunct professor at New York University, lecturing on digital and mobile technology. She earned a bachelor's degree in international management at American University.
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Podcast episode production by Dante32.

Coupling a charitable mindset and a drive to solve some of the toughest intellectual and scientific problems has led to success for P33 Chicago and founding Chief Executive Officer Brad Henderson. Serving Chicago and embracing the city’s challenges and strengths, Brad envisions the city as a hub for new technologies built on collaborative and dynamic innovation, all while embracing inclusive growth.
In this episode, Brad shares the successes of P33 Chicago and TechRise’s efforts, including outlining how two million dollars invested into Black, Hispanic, and women founders led to ninety-three million in additional private financing. He discusses the lasting effects of starting a business under-capitalized and the realities of how most founders raise capital. Brad offers insight into connecting investors with opportunities where they might lack first-hand expertise or experience and the benefits of encountering and working with new people and ideas.
Brad dives into ongoing success stories in Chicago (EventNoire and more), the ripe environment for a Chicago-based battery boom, the new CZ Biohub, and the aims and recent triumphs of Innovate Illinois. He shares a key component to the city's success: the collaborative spirit of the top-caliber universities. Brad paints a picture of an innovative Chicago that utilizes the abundance of college graduates and embraces scientists and thinkers across institutions working together to create new technologies funded by bold Chicago investors and building on the city’s history of innovation.
(04:26) – Introducing Brad Henderson and P33 Chicago(05:52) – TechRise(07:27) – The impact of an under-capitalized start(09:45) – Proof points and coaching founders(12:05) – Success story: EventNoire(14:21) – A battery boom(18:41) – Chicago-based investors(20:34) – The impact of exceptional, collaborative universities (25:25) – Where is Chicago headed?(26:17) – Leveraging a small staff(29:38) – Chicago-based innovation and collaboration
Brad Henderson is the Founding Chief Executive Officer at P33 Chicago, the forward-thinking nonprofit organization dedicated to elevating Chicago's status as a world premier hub of technological discovery and development. Brad's leadership extends to various roles on boards and advisory committees of Interfaith Youth Core (Board Chair), the College Visiting Committee at the University of Chicago, the President’s Advisory Council at the University of Illinois, the College of Computing Advisory Board at Illinois Tech, Rush University Medical Center, Rush University (Board of Governors), Chicago Council on Global Affairs, and the Chicago History Museum. Brad earned a bachelor’s degree in economics with honors and a master's in social science from the University of Chicago. A Rhodes Scholar, Brad also earned a master’s of science in economics and social history from the University of Oxford and an MBA from Saiid Business School at the University of Oxford.
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Today we’re sharing another insightful presentation from our most recent Innovative Executives League Summit, where Michelangelo D’Agostino, VP of Machine Learning at Tegus, delivered a foundational lesson about large language models. Imagine you are Rip Van Winkle, as Michelangelo puts it, and you have woken up after a long sleep and encountered the current AI landscape. What have you missed? What do you need to know to move forward? Calling upon his data analysis and machine learning expertise, Michelangelo offers clear, concise insights to introduce audiences to the capabilities and shortcomings of large language models today. 
 In this presentation, Michelangelo integrates large language models to demonstrate their abilities. Defining the term and other critical ones (What does GPT mean?), he dives into the factors that have led to the exponential growth in these models since 2020 and details the training methodologies that led to major advances. Michelangelo covers how instruction tuning brought an exercise in probability to usefulness that will change industries.
Offering insight into the challenges large language models are encountering, Michelangelo walks audiences through a “hallucination,” where the LLM offers a confident answer that is incorrect—a concerning flaw--and displays how prompt engineering generates the correct result with a minor tweak. With the input and output being natural language, Michelangelo encourages people to embrace the low barrier of entry to try out the models directly (OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Bard) by writing prompts and learning its capabilities firsthand. Michelangelo shares the areas where he’s excited about the potential of large language models and their transformative power for text-heavy industries. 
(00:58) – Demystifying AI(03:37) – Large language models(05:13) – Unpacking training(08:43) – Why now?(12:05) – Increased potential(14:50) – Hallucinations(16:26) – Prompt engineering(18:25) – Applications of language models(22:48) – Play around with it!
Michelangelo D’Agostino is the Vice President of Machine Learning at Tegus. Previously, he held leadership roles in data and machine learning at Cameo and ShopRunner. Michelangelo’s career as a technologist career is marked by his exploration of large language models and their applications in financial text data. He studied physics, earning a bachelor’s degree from Harvard University and a Ph.D. from the University of California, Berkeley.
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