My guest today is Yeshwant Satam, an ICT professional and consultant with over four decades of experience.In this conversation, he freely shares:<ul><li>His four-decade journey from soldering boards and PROM patching to firmware, software, IT services leadership, and manufacturing automation.</li><li>Continual learning multiple programming languages including Pascal, Fortran, C, and Occam, then rapidly building capability through curiosity and commitment.</li><li>Memorable moments including reverse engineering an IBM PC BIOS before realizing the boot floppy was still in a drawer in the US.</li><li>The early days of Indian software exports: faxed requirements, shared processors, STPI floppy submissions, and the birth of professional delivery processes.</li><li>That managers in technology must stay connected to the craft, even if they no longer code every day.</li><li>Tips for great crisis leadership which includes staying calm, finding the real problem solvers, shielding the team from noise, and tracking technical progress closely.</li><li>On AI in manufacturing, he distinguishes stable predictive AI in core operations from generative AI, which is currently safer at the fringes and in human-assisted decision making.</li><li>Career advice for new entrants: study where hiring is moving, reskill seriously, and do not wait for a company to teach you everything.</li><li>Career advice for mid-career professionals: get back in touch with technology, learn continuously, and show that you can move with new directions.</li><li>Actionable takeaway: stay curious, stay close to the work, respect people who solve problems, and never let a title separate you from learning.</li></ul> Yeshwant Satam is an ICT professional and consultant with over four decades of experience.Over his career he has experience in multiple domains and technologies. A few highlights: <h4>Solutioning, managing and guiding full life cycle projects, including network managed services.</h4><h4>Managing global delivery units with multi-million USD P&L responsibility.</h4><h4>Building long-term sustainable customer and partner relationships.</h4><h4>Work experience spans from conceptualizing IT solutions and products on heterogeneous platforms, to successful implementation and support in diversified cultural environments.</h4><h4>International exposure and is conversant in dealing with international customers.</h4><h4>Consistent track record of driving teams in achieving higher customer satisfaction. Guide teams in establishing processes to optimize effectiveness of IT deliveries.</h4><h4>Defining and designing IT architectures and approaches for solutions in OT to IT integration in manufacturing enterprises</h4><ul><li>Identifying technologies, frameworks and standards for practical and fit-for-purpose solutions</li></ul> <a href="http://www.linkedin.com/in/yeshwant-satam-a3b1809" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">www.linkedin.com/in/yeshwant-satam-a3b1809</a>

My guest today is Yeshwant Satam, an ICT professional and consultant with over four decades of experience.In this conversation, he freely shares:His four-decade journey from soldering boards and PROM patching to firmware, software, IT services leadership, and manufacturing automation.Continual learning multiple programming languages including Pascal, Fortran, C, and Occam, then rapidly building capability through curiosity and commitment.Memorable moments including reverse engineering an IBM PC BIOS before realizing the boot floppy was still in a drawer in the US.The early days of Indian software exports: faxed requirements, shared processors, STPI floppy submissions, and the birth of professional delivery processes.That managers in technology must stay connected to the craft, even if they no longer code every day.Tips for great crisis leadership which includes staying calm, finding the real problem solvers, shielding the team from noise, and tracking technical progress closely.On AI in manufacturing, he distinguishes stable predictive AI in core operations from generative AI, which is currently safer at the fringes and in human-assisted decision making.Career advice for new entrants: study where hiring is moving, reskill seriously, and do not wait for a company to teach you everything.Career advice for mid-career professionals: get back in touch with technology, learn continuously, and show that you can move with new directions.Actionable takeaway: stay curious, stay close to the work, respect people who solve problems, and never let a title separate you from learning.Yeshwant Satam is an ICT professional and consultant with over four decades of experience.Over his career he has experience in multiple domains and technologies. A few highlights:Solutioning, managing and guiding full life cycle projects, including network managed services.Managing global delivery units with multi-million USD P&L responsibility.Building long-term sustainable customer and partner relationships.Work experience spans from conceptualizing IT solutions and products on heterogeneous platforms, to successful implementation and support in diversified cultural environments.International exposure and is conversant in dealing with international customers.Consistent track record of driving teams in achieving higher customer satisfaction. Guide teams in establishing processes to optimize effectiveness of IT deliveries.Defining and designing IT architectures and approaches for solutions in OT to IT integration in manufacturing enterprisesIdentifying technologies, frameworks and standards for practical and fit-for-purpose solutionswww.linkedin.com/in/yeshwant-satam-a3b1809

Software People Stories

From Soldering to Software with Yeshwant Satam

My guest today is Arun Subash Manickam. An Engineering leader at Google.In this conversation, Arun shares:<ul><li>his journey from Chennai schooling to computer science and a long career in networking, startups, acquisitions, and Google.</li><li>transitions from individual contributor to manager, startup life, acquisitions, autonomy, AI, and career growth.</li><li>learning continuously, adapting to change, and working hard with purpose as core career principles.</li></ul> <h2>Highlights</h2> <ul><li>A teacher’s suggestion changed Arun’s path from commerce to computer science.</li><li>Early Cisco work built strong engineering foundations, while startups deepened product and business understanding.</li><li>Startup experience offers intense learning, faster execution, and visible impact.</li><li>Moving from IC to manager requires mindset change, feedback, and self-awareness.</li><li>Hybrid work balances flexibility with in-person collaboration and team bonding.</li><li> Acquisitions vary: autonomy depends on overlap, integration model, and business uniqueness.</li><li>AI is a major productivity enabler, but domain knowledge remains essential.</li><li>AI-generated code and documents still need clear human direction and review.</li><li>Career advice: learn, adapt, and work hard—smartly and consistently.</li><li>Late-career focus shifts toward impact, enjoyment, experimentation, and grounded personal practices.</li></ul> <a href="https://www.linkedin.com/in/arun-subash-manickam-768b1416/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/arun-subash-manickam-768b1416/</a><a href="mailto:arunsubashm@gmail.com" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">arunsubashm@gmail.com</a>

My guest today is Arun Subash Manickam. An Engineering leader at Google.In this conversation, Arun shares:his journey from Chennai schooling to computer science and a long career in networking, startups, acquisitions, and Google.transitions from individual contributor to manager, startup life, acquisitions, autonomy, AI, and career growth.learning continuously, adapting to change, and working hard with purpose as core career principles.HighlightsA teacher’s suggestion changed Arun’s path from commerce to computer science.Early Cisco work built strong engineering foundations, while startups deepened product and business understanding.Startup experience offers intense learning, faster execution, and visible impact.Moving from IC to manager requires mindset change, feedback, and self-awareness.Hybrid work balances flexibility with in-person collaboration and team bonding. Acquisitions vary: autonomy depends on overlap, integration model, and business uniqueness.AI is a major productivity enabler, but domain knowledge remains essential.AI-generated code and documents still need clear human direction and review.Career advice: learn, adapt, and work hard—smartly and consistently.Late-career focus shifts toward impact, enjoyment, experimentation, and grounded personal practices.https://www.linkedin.com/in/arun-subash-manickam-768b1416/arunsubashm@gmail.com

Learn, Adapt, Work Hard with Arun Subash Manickam

My guest today is Dr. Kishore Reddy, co-founder of & Chief Strategy Officer at ProHance.Conversation highlights:Background & Early Life:<ul><li>Kishore grew up across India—moving from Gujarat to Delhi and eventually settling in Bangalore, which he considers his home.</li></ul>Medical Career & Transition to IT:<ul><li>Completed his MBBS from Bangalore Medical College with plans to pursue neurology residency in the US, inspired by family members.</li><li>After facing US visa denials (under section 214B), his brother Kiran suggested exploring the booming IT field around 1998–1999.</li><li>Approached Sudhir Sharma at Network Solutions to learn IT on the job without demanding a salary.</li><li>Leveraged his medical background's intensive reading habits to quickly master IT manuals.</li></ul>Early IT Experience & Growth:<ul><li>Had early exposure to computers during childhood thanks to his father and brother, including learning GW-BASIC.</li><li>Worked on a World Bank-funded Health Information System (HIS) / Hospital Management Information System (HMIS) project for the Government of Karnataka.</li><li>Mentored by DVN Sarma, gaining early exposure to data analytics and statistics.</li><li>Network Solutions was acquired by IBM in 2005, leading to Kishore working at IBM for four and a half years.</li></ul>Founding Jamocha Tech:<ul><li>Decided to start his own venture in October 2008 and teamed up with Rajesh (his former colleague from Network Solutions).</li><li>Received early mentorship and backing from Sudhir Sharma.</li><li>Named the company Jammocha Tech over coffee at Barista, driven by their passion for Java technology.</li></ul>Evolution to ProHance:<ul><li>Initially built multiple products (e.g., network management, energy management) before streamlining focus.</li><li>Shifted roles based on advice: Kishore transitioned to sales/technology head, while Rajesh handled delivery and support.</li><li>Coined the name ProHance from "Productivity Enhancement" ("Pro" + "Hance").</li><li>Rebranded completely to Prohands to avoid market confusion between the company and product names.</li><li>Formally established ProHance India Private Limited in 2020, with ChrysCapital taking a majority stake in 2023.</li></ul>Key Entrepreneurial Takeaways:<ul><li>Adaptability: Expect the journey not to be a straight line and remain flexible.</li><li>Team Building: Recognize that while founders start the journey, the team drives the company's ultimate success.</li><li>Brand Focus: Avoid confusing customers with too many entity/product names; stick to one strong identity.</li></ul> <a href="https://www.linkedin.com/in/kishore-r-2a37aa5/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/kishore-r-2a37aa5/</a>Experienced Chief Technology Officer with a demonstrated history of working in the information technology and services industry. Strong product engineering skills. Built and rolled out several large enterprise class products across various domains.

My guest today is Dr. Kishore Reddy, co-founder of & Chief Strategy Officer at ProHance.Conversation highlights:Background & Early Life:Kishore grew up across India—moving from Gujarat to Delhi and eventually settling in Bangalore, which he considers his home.Medical Career & Transition to IT:Completed his MBBS from Bangalore Medical College with plans to pursue neurology residency in the US, inspired by family members.After facing US visa denials (under section 214B), his brother Kiran suggested exploring the booming IT field around 1998–1999.Approached Sudhir Sharma at Network Solutions to learn IT on the job without demanding a salary.Leveraged his medical background's intensive reading habits to quickly master IT manuals.Early IT Experience & Growth:Had early exposure to computers during childhood thanks to his father and brother, including learning GW-BASIC.Worked on a World Bank-funded Health Information System (HIS) / Hospital Management Information System (HMIS) project for the Government of Karnataka.Mentored by DVN Sarma, gaining early exposure to data analytics and statistics.Network Solutions was acquired by IBM in 2005, leading to Kishore working at IBM for four and a half years.Founding Jamocha Tech:Decided to start his own venture in October 2008 and teamed up with Rajesh (his former colleague from Network Solutions).Received early mentorship and backing from Sudhir Sharma.Named the company Jammocha Tech over coffee at Barista, driven by their passion for Java technology.Evolution to ProHance:Initially built multiple products (e.g., network management, energy management) before streamlining focus.Shifted roles based on advice: Kishore transitioned to sales/technology head, while Rajesh handled delivery and support.Coined the name ProHance from "Productivity Enhancement" ("Pro" + "Hance").Rebranded completely to Prohands to avoid market confusion between the company and product names.Formally established ProHance India Private Limited in 2020, with ChrysCapital taking a majority stake in 2023.Key Entrepreneurial Takeaways:Adaptability: Expect the journey not to be a straight line and remain flexible.Team Building: Recognize that while founders start the journey, the team drives the company's ultimate success.Brand Focus: Avoid confusing customers with too many entity/product names; stick to one strong identity.https://www.linkedin.com/in/kishore-r-2a37aa5/Experienced Chief Technology Officer with a demonstrated history of working in the information technology and services industry. Strong product engineering skills. Built and rolled out several large enterprise class products across various domains. 

From Stethoscope to Software with Dr. Kishore Reddy

In this episode of Software People Stories, Gayathri Kalyanaraman speaks with Vasu Vadlamani, a technology leader, architect, entrepreneur and Professor of Practice, about a career that has evolved alongside the software industry itself. About his accidental start to an AI Era tech leader who’s defining mantra has been Every role has an expiration date! Vasu takes us back to the early 1990s, when software meant client-server systems, handwritten notes and face-to-face communication. From his early work with Citibank to working with Sun Microsystems, building a professional services organization, experiencing the disruption that followed Oracle’s acquisition of Sun, and later taking on technology and architecture roles at HCL and Cognizant, his journey reflects several waves of technology transformation.But perhaps the most interesting transition came later.While working at Cognizant, Vasu found himself asking a fundamental question: Why should the gap between college education and industry readiness be so large?This led him to work with educational institutions with a very practical goal — to make graduates industry-ready much sooner. Eventually, that became the driving force behind his move from corporate technology leadership to becoming a Professor of Practice.Today, Vasu sees himself less as a software professional and more as someone whose purpose is to help people do their best — in technology, in their careers and in their interactions with others.The conversation explores:<ul><li>The early days of software and how dramatically the industry has evolved</li><li>Why business understanding helped Vasu become a better software professional</li><li>Building and scaling a technology services organization from zero to 150 people</li><li>Navigating the difficult period when the Sun Microsystems ecosystem disappeared</li><li>Moving from customer-facing roles to architecting internal enterprise systems</li><li>The philosophy of making software development “zero maintenance”</li><li>Why the gap between education and industry continues to matter</li><li>Making graduates “production ready” rather than simply degree ready</li><li>Why professors also need exposure to real-world engineering</li><li>Creating safe, sandboxed opportunities for faculty and students to work on real enterprise use cases</li><li>What AI means for technology careers</li><li>Why roles will change, but technology itself isn't going away</li><li>The importance of resilience, curiosity, teamwork and being “an engineer at heart”</li></ul>﻿At the heart of the conversation is a simple message from Vasu:Don't worry about the future of technology. Keep learning, keep adapting, and keep building. There will always be a place for people who are willing to do the work and find their way.Quotable Quotes“Don’t worry about AI. Roles will change. The industry will still be there.”“If you fail, use your knowledge to get up and rise again faster.”“IT is a team’s play. One person alone cannot run the ship.”“The younger generation will always be smarter than me. If I can succeed, Gen Z will definitely succeed.”“If Vasu can find a way, you are much smarter than me. You will find a better way.” Vasu Vadlamani is an accomplished IT Professional offering 30 years of experience in integrating Technical and Domain expertise (Financial Services), focusing on Large Complex Digital Transformation Initiatives. An efficient Communicator possessing strong Coordination, Interpersonal, Mentoring and Team Management Skills. Cross Functional Services Leader managing multi geo, multi service line deliveries for over $440+M. Vasu was  CTO of ADM Insurance Domain, responsible to create and execute an Information Technology Strategy to modernize enterprise technological applications, moving away from their legacy apps to modern On Cloud tech stack. Co-authored the (C)ontain, (M)aintain (I)nvest philosophy so significantly enhance the business value of applications.His  research interests span Artificial Intelligence & Machine Learning, Cloud & Distributed Systems, Data Science, Software Engineering practices, and CS Education & Pedagogy. He is  particularly interested in how emerging technologies reshape both industry workflows and the way Computer Science itself should be taught at the graduate and postgraduate level.Vasu can be reached at <a href="https://www.linkedin.com/in/vasuvadlamani/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/vasuvadlamani/</a>

In this episode of Software People Stories, Gayathri Kalyanaraman speaks with Vasu Vadlamani, a technology leader, architect, entrepreneur and Professor of Practice, about a career that has evolved alongside the software industry itself. About his accidental start to an AI Era tech leader who’s defining mantra has been Every role has an expiration date! Vasu takes us back to the early 1990s, when software meant client-server systems, handwritten notes and face-to-face communication. From his early work with Citibank to working with Sun Microsystems, building a professional services organization, experiencing the disruption that followed Oracle’s acquisition of Sun, and later taking on technology and architecture roles at HCL and Cognizant, his journey reflects several waves of technology transformation.But perhaps the most interesting transition came later.While working at Cognizant, Vasu found himself asking a fundamental question: Why should the gap between college education and industry readiness be so large?This led him to work with educational institutions with a very practical goal — to make graduates industry-ready much sooner. Eventually, that became the driving force behind his move from corporate technology leadership to becoming a Professor of Practice.Today, Vasu sees himself less as a software professional and more as someone whose purpose is to help people do their best — in technology, in their careers and in their interactions with others.The conversation explores:The early days of software and how dramatically the industry has evolvedWhy business understanding helped Vasu become a better software professionalBuilding and scaling a technology services organization from zero to 150 peopleNavigating the difficult period when the Sun Microsystems ecosystem disappearedMoving from customer-facing roles to architecting internal enterprise systemsThe philosophy of making software development “zero maintenance”Why the gap between education and industry continues to matterMaking graduates “production ready” rather than simply degree readyWhy professors also need exposure to real-world engineeringCreating safe, sandboxed opportunities for faculty and students to work on real enterprise use casesWhat AI means for technology careersWhy roles will change, but technology itself isn't going awayThe importance of resilience, curiosity, teamwork and being “an engineer at heart”﻿At the heart of the conversation is a simple message from Vasu:Don't worry about the future of technology. Keep learning, keep adapting, and keep building. There will always be a place for people who are willing to do the work and find their way.Quotable Quotes“Don’t worry about AI. Roles will change. The industry will still be there.”“If you fail, use your knowledge to get up and rise again faster.”“IT is a team’s play. One person alone cannot run the ship.”“The younger generation will always be smarter than me. If I can succeed, Gen Z will definitely succeed.”“If Vasu can find a way, you are much smarter than me. You will find a better way.”Vasu Vadlamani is an accomplished IT Professional offering 30 years of experience in integrating Technical and Domain expertise (Financial Services), focusing on Large Complex Digital Transformation Initiatives. An efficient Communicator possessing strong Coordination, Interpersonal, Mentoring and Team Management Skills. Cross Functional Services Leader managing multi geo, multi service line deliveries for over $440+M. Vasu was  CTO of ADM Insurance Domain, responsible to create and execute an Information Technology Strategy to modernize enterprise technological applications, moving away from their legacy apps to modern On Cloud tech stack. Co-authored the (C)ontain, (M)aintain (I)nvest philosophy so significantly enhance the business value of applications.His  research interests span Artificial Intelligence & Machine Learning, Cloud & Distributed Systems, Data Science, Software Engineering practices, and CS Education & Pedagogy. He is  particularly interested in how emerging technologies reshape both industry workflows and the way Computer Science itself should be taught at the graduate and postgraduate level.Vasu can be reached at https://www.linkedin.com/in/vasuvadlamani/

Don't Worry About AI. Keep Learning with Vasu Vadlamani

In conversation with Ashish Jha, Chitra and Ashish explored - <ul><li>His childhood fascination with science and literature to working with Tata Steel as an industrial engineer</li><li>Foray into data science and analytics with GECIS and Genpact getting deep into math and stats</li><li>Converting customer problems into math equations</li><li>Benefitting from great mentorship, anchoring customer conversations very early on in his career</li><li>Leadership lessons in inspiring confidence in difficult moments</li><li>Entrepreneurship path and founding Analytical Wizards and being a very hands on founder</li><li>Creating and holding a strong value-based organizational work culture</li><li>Building compassionate work places</li><li>The human in the centre of all AI and everything we do, how patient journeys and decision engines impact lives</li><li>Integrating wisdoms to start Sunny Tribe Ethos</li><li>Why he strongly believes that humans should build strong, irreplaceable foundations and grow as “a whole person”.</li><li>Being self aware as a message for all young and aspiring tech folk</li></ul> Guest Bio: Ashish Jha is an entrepreneur and co-founder of Sunnytribe Ethos, where he is building and scaling Thrivin’Up, a holistic personal development platform that maps 21 dimensions of growth ranging from sleep and fitness to emotional balance, resilience, deep work, and purpose.He began his career as an Industrial Engineer at Tata Steel in 1999, and later moved into data science with GE Capital. Most recently, he co-founded Analytical Wizards, a technology-driven data science company, where he led India Operations, HR, and the Data Science vertical.After a deliberate hiatus exploring literature, music, and meditation, Ashish returned with renewed clarity to focus on empowering individuals and guiding technology founders in building collaborative, resilient cultures.Beyond work, he enjoys spending time with his family, learning music, and writing. Ashish is reacheable via <a href="https://www.linkedin.com/in/ashishrjha/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/ashishrjha/</a> and <a href="https://www.thrivinup.com/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.thrivinup.com/</a>

In conversation with Ashish Jha, Chitra and Ashish explored -His childhood fascination with science and literature to working with Tata Steel as an industrial engineerForay into data science and analytics with GECIS and Genpact getting deep into math and statsConverting customer problems into math equationsBenefitting from great mentorship, anchoring customer conversations very early on in his careerLeadership lessons in inspiring confidence in difficult momentsEntrepreneurship path and founding Analytical Wizards and being a very hands on founderCreating and holding a strong value-based organizational work cultureBuilding compassionate work placesThe human in the centre of all AI and everything we do, how patient journeys and decision engines impact livesIntegrating wisdoms to start Sunny Tribe EthosWhy he strongly believes that humans should build strong, irreplaceable foundations and grow as “a whole person”.Being self aware as a message for all young and aspiring tech folkGuest Bio:Ashish Jha is an entrepreneur and co-founder of Sunnytribe Ethos, where he is building and scaling Thrivin’Up, a holistic personal development platform that maps 21 dimensions of growth ranging from sleep and fitness to emotional balance, resilience, deep work, and purpose.He began his career as an Industrial Engineer at Tata Steel in 1999, and later moved into data science with GE Capital. Most recently, he co-founded Analytical Wizards, a technology-driven data science company, where he led India Operations, HR, and the Data Science vertical.After a deliberate hiatus exploring literature, music, and meditation, Ashish returned with renewed clarity to focus on empowering individuals and guiding technology founders in building collaborative, resilient cultures.Beyond work, he enjoys spending time with his family, learning music, and writing.Ashish is reacheable via https://www.linkedin.com/in/ashishrjha/ and https://www.thrivinup.com/ 

Data Science and Human Foundations with Ashish Jha

My guest today is Vijays Kadiala, ,Executive Director  for Architecture, Engineering, AI, Data, Cloud in DBS Tech India talks about his accidental start to an AI Era tech leader who’s defining mantra has been Every role has an expiration date! Conversation highlights00:32 — 25 years of a career that wasn't plannedVijay introduces his journey across startups, TCS, Infosys, Capgemini, JPMorgan Chase and DBS, with data and data-intensive applications as a recurring theme.02:35 — From a two-bedroom startup to the corporate worldVijay recalls his unexpected entry into entrepreneurship after graduating with no job offers and describes the freedom, ownership and lack of bureaucracy that made those early startup years memorable.05:39 — Why he left the startupA fascinating look at how social and family expectations influenced career decisions in the early 2000s—and why working for a recognised IT company mattered so much at that time.07:57 — Has entrepreneurship become a label?Vijay reflects on today's startup culture and the difference between genuinely solving a customer problem and simply wanting to be called an entrepreneur.10:02 — Are GCCs really global capability centres?Vijay offers his perspective on GCCs, suggesting that organisations should think beyond the label and focus on what makes an India-based technology centre genuinely different and valuable.11:09 — The “expiration date” of a career roleOne of the central ideas of the conversation: every role has a lifespan. Vijay's approach has been to find a problem, solve it in roughly 18 months, create customer value and move on to the next challenge.14:19 — Make yourself redundantGayatri shares her own three-year theory, while Vijay explains why he believes professionals should constantly create enough value for their current role to become unnecessary.15:19 — Choosing the uncomfortable pathFrom production support to PL/SQL to data architecture, Vijay describes several career decisions where he deliberately entered unfamiliar territory.18:10 — Moving to the US as a data architectA new role, a new country, a new culture and a new way of communicating. Vijay talks about the challenges of his first international assignment.19:29 — Taking the biggest career betIn 2018, Vijay chose to move from people management into an executive individual-contributor role at JPMorgan Chase—putting his promotion trajectory at risk in the process.22:26 — You have to make the decisionA powerful discussion about career choices, risk and the importance of betting on yourself. Even a wrong decision, Vijay argues, can cost only a year or two in a career that may span 35–50 years.23:11 — Building a second identity through writingVijay explains how his leadership talks evolved into his first book and why his leadership philosophy begins outside the workplace.24:58 — What driving can teach us about leadershipHis unusual leadership framework connects everyday driving behaviour with leadership behaviours—how we respond to rules, pressure, uncertainty, other people and unexpected situations.26:57 — Writing with the help of LLMsVijay and his son began putting their ideas on paper and then using LLMs to help develop them. His philosophy is simple: the ideas and experiences remain human; AI becomes a tool to help express them.28:01 — Giving back to the next generationVijay has spent nearly 14 years visiting universities and colleges, sharing practical experiences with students and helping them accelerate their journeys.40:01 — Learn across culturesVijay encourages professionals to work with organisations from different parts of the world—not only to gain technical experience, but to understand how culture influences leadership, communication and behaviour.45:01 — What will technology careers look like in 2031?Vijay predicts that AI agents will transform traditional roles such as business analysis, testing and software development. Instead of specialised roles operating in isolation, he sees a future of professionals combining technical depth, domain knowledge and AI capabilities.50:00 — From I-shaped to M-shaped professionalsVijay describes the evolution from deep expertise in one area to professionals who have multiple areas of technical depth combined with domain understanding.52:00— Four skills for the AI era<ol><li>Curiosity — the ability to keep asking “Why?”</li><li>Domain experience — understanding the business and context behind the technology.</li><li>Orchestration — knowing what humans should do, what agents can do and where humans and agents should work together.</li><li>Judgment — making decisions when AI produces ambiguous, conflicting or potentially incorrect answers.</li></ol>55:00— Why curiosity mattersVijay reflects on how traditional cultures can sometimes discourage questioning and argues that curiosity will become one of the most important capabilities in an AI-driven world.56:00 — Five movies that imagined the AI futureVijay recommends Terminator 2, I, Robot, Surrogates, Passengers and WALL-E as interesting ways to think about different dimensions of an AI-driven future. Key TakeawaysYour first career decision doesn't have to define your career.Sometimes the best opportunities begin with circumstances you didn't choose.Get comfortable being uncomfortable. Vijay's biggest career moves often came when he knew very little about the new role.Don't wait for your role to become obsolete. Create value, make the role redundant and move forward.Take calculated bets on yourself—even when the safer option is available.Build your career across people, technology and cultures.Leadership is not something that exists only inside a workplace; it is reflected in our everyday behaviour.AI will not simply replace technology roles—it will reshape them.The future professional will combine technical depth with domain knowledge and the ability to orchestrate AI.Curiosity and judgment remain deeply human capabilities. Vijaya Kadiyala is a technology leader with over two decades of experience spanning data, AI, cloud and enterprise transformation. Having worked with organisations such as TCS, Infosys, JPMorgan Chase and DBS Bank, he has evolved from a deep technical specialist into a leader shaping technology at GCC scale.At DBS Tech India, Vijaya works at the intersection of Data, AI, Cloud and enterprise transformation, helping build technology capabilities for a highly regulated financial-services environment. His journey also includes patents, innovation awards, mentoring and building high-performing technology teams.What makes Vijaya's story particularly interesting is the evolution of his career—from being a hands-on technologist and database expert to becoming a technology and transformation leader navigating the rapidly changing world of AI. Vijay can be reached at <a href="https://www.linkedin.com/in/vijaya-kadiyala/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/vijaya-kadiyala/</a>

My guest today is Vijays Kadiala, ,Executive Director  for Architecture, Engineering, AI, Data, Cloud in DBS Tech India talks about his accidental start to an AI Era tech leader who’s defining mantra has been Every role has an expiration date! Conversation highlights00:32 — 25 years of a career that wasn't plannedVijay introduces his journey across startups, TCS, Infosys, Capgemini, JPMorgan Chase and DBS, with data and data-intensive applications as a recurring theme.02:35 — From a two-bedroom startup to the corporate worldVijay recalls his unexpected entry into entrepreneurship after graduating with no job offers and describes the freedom, ownership and lack of bureaucracy that made those early startup years memorable.05:39 — Why he left the startupA fascinating look at how social and family expectations influenced career decisions in the early 2000s—and why working for a recognised IT company mattered so much at that time.07:57 — Has entrepreneurship become a label?Vijay reflects on today's startup culture and the difference between genuinely solving a customer problem and simply wanting to be called an entrepreneur.10:02 — Are GCCs really global capability centres?Vijay offers his perspective on GCCs, suggesting that organisations should think beyond the label and focus on what makes an India-based technology centre genuinely different and valuable.11:09 — The “expiration date” of a career roleOne of the central ideas of the conversation: every role has a lifespan. Vijay's approach has been to find a problem, solve it in roughly 18 months, create customer value and move on to the next challenge.14:19 — Make yourself redundantGayatri shares her own three-year theory, while Vijay explains why he believes professionals should constantly create enough value for their current role to become unnecessary.15:19 — Choosing the uncomfortable pathFrom production support to PL/SQL to data architecture, Vijay describes several career decisions where he deliberately entered unfamiliar territory.18:10 — Moving to the US as a data architectA new role, a new country, a new culture and a new way of communicating. Vijay talks about the challenges of his first international assignment.19:29 — Taking the biggest career betIn 2018, Vijay chose to move from people management into an executive individual-contributor role at JPMorgan Chase—putting his promotion trajectory at risk in the process.22:26 — You have to make the decisionA powerful discussion about career choices, risk and the importance of betting on yourself. Even a wrong decision, Vijay argues, can cost only a year or two in a career that may span 35–50 years.23:11 — Building a second identity through writingVijay explains how his leadership talks evolved into his first book and why his leadership philosophy begins outside the workplace.24:58 — What driving can teach us about leadershipHis unusual leadership framework connects everyday driving behaviour with leadership behaviours—how we respond to rules, pressure, uncertainty, other people and unexpected situations.26:57 — Writing with the help of LLMsVijay and his son began putting their ideas on paper and then using LLMs to help develop them. His philosophy is simple: the ideas and experiences remain human; AI becomes a tool to help express them.28:01 — Giving back to the next generationVijay has spent nearly 14 years visiting universities and colleges, sharing practical experiences with students and helping them accelerate their journeys.40:01 — Learn across culturesVijay encourages professionals to work with organisations from different parts of the world—not only to gain technical experience, but to understand how culture influences leadership, communication and behaviour.45:01 — What will technology careers look like in 2031?Vijay predicts that AI agents will transform traditional roles such as business analysis, testing and software development. Instead of specialised roles operating in isolation, he sees a future of professionals combining technical depth, domain knowledge and AI capabilities.50:00 — From I-shaped to M-shaped professionalsVijay describes the evolution from deep expertise in one area to professionals who have multiple areas of technical depth combined with domain understanding.52:00— Four skills for the AI eraCuriosity — the ability to keep asking “Why?”Domain experience — understanding the business and context behind the technology.Orchestration — knowing what humans should do, what agents can do and where humans and agents should work together.Judgment — making decisions when AI produces ambiguous, conflicting or potentially incorrect answers.55:00— Why curiosity mattersVijay reflects on how traditional cultures can sometimes discourage questioning and argues that curiosity will become one of the most important capabilities in an AI-driven world.56:00 — Five movies that imagined the AI futureVijay recommends Terminator 2, I, Robot, Surrogates, Passengers and WALL-E as interesting ways to think about different dimensions of an AI-driven future.Key TakeawaysYour first career decision doesn't have to define your career.Sometimes the best opportunities begin with circumstances you didn't choose.Get comfortable being uncomfortable. Vijay's biggest career moves often came when he knew very little about the new role.Don't wait for your role to become obsolete. Create value, make the role redundant and move forward.Take calculated bets on yourself—even when the safer option is available.Build your career across people, technology and cultures.Leadership is not something that exists only inside a workplace; it is reflected in our everyday behaviour.AI will not simply replace technology roles—it will reshape them.The future professional will combine technical depth with domain knowledge and the ability to orchestrate AI.Curiosity and judgment remain deeply human capabilities.Vijaya Kadiyala is a technology leader with over two decades of experience spanning data, AI, cloud and enterprise transformation. Having worked with organisations such as TCS, Infosys, JPMorgan Chase and DBS Bank, he has evolved from a deep technical specialist into a leader shaping technology at GCC scale.At DBS Tech India, Vijaya works at the intersection of Data, AI, Cloud and enterprise transformation, helping build technology capabilities for a highly regulated financial-services environment. His journey also includes patents, innovation awards, mentoring and building high-performing technology teams.What makes Vijaya's story particularly interesting is the evolution of his career—from being a hands-on technologist and database expert to becoming a technology and transformation leader navigating the rapidly changing world of AI.Vijay can be reached at https://www.linkedin.com/in/vijaya-kadiyala/ 

Accidental Start to an AI-Era Technology Leader with Vijaya Kadiyala

Intro:Jithu Gopal is a fintech product leader based in Bangalore, with 18+ years across engineering, consulting, and product. He is AVP Product at Scripbox and currently owns the charter of building the advisory experience that'll help a million families make confident choices about their portfolios.Before Scripbox he co-founded Nilenso, a boutique technology consulting firm, where he built a social network, rewrote the checkout experience for a ticketing platform, and took on a few other projects.He is curious about what creates habits and what motivates people.Shownotes:In this conversation, Jithu Gopal and Chitra Gurjar explore -<ul><li>Working as a software engineer and an early observer of the cost of quality in work</li><li>Active community-based learning from Java and Ruby user groups in early career</li><li>Building a social network , learning the “ethics” of software engineering, recognizing and applying design patterns </li><li>Work at Nilenso, an employee-owned cooperative-like company, applying functional programming principles</li><li>Living the principles of “being agile”, using Test-Driven-Development to shape a problem and approach it from the outside, rather than just build, staying in the problem space</li><li>The versions of software engineering, 1.0 and 2.0</li><li>Indispensable systems thinking</li><li>Shifts in Product Management, building strong foundations of working with engineering using high agency and trust </li><li>AI Mavens, followers, the power and tools to leverage knowledge and do way more</li><li>Examining AI in layers for any organization or system </li><li>How we organize ourselves differently in the age of machines</li><li>Keeping the “Why” in focus with organization memory and problem memory</li><li>What “post AI” looks like - awakening consciousness and invoking agency, AI cycles bringing more value add</li><li>Social bonding as a key to young people’s future of work and life</li><li>Books that have had a powerful influence on him.</li><li>For aspiring software engineers to keep building and asking about what “good” looks like</li></ul> Few conversations flow back and forth in time, not unlike when you meet friends from childhood. In this episode of the Software People Stories podcast, I found myself having tremendous deja-vu moments as Jithu Gopal shared his flow of thoughts across various aspects of software engineering through his 18 plus years of work, how his interests and ways of connecting what he reads, experiences and works with have significance and relevance in the AI whorl that seems to be sweeping us with it and what habits and disciplines can hold us through as we begin to figure out new ways of working, learning and what the future might hold for our children and aspiring engineers. Listen on.

Intro:Jithu Gopal is a fintech product leader based in Bangalore, with 18+ years across engineering, consulting, and product. He is AVP Product at Scripbox and currently owns the charter of building the advisory experience that'll help a million families make confident choices about their portfolios.Before Scripbox he co-founded Nilenso, a boutique technology consulting firm, where he built a social network, rewrote the checkout experience for a ticketing platform, and took on a few other projects.He is curious about what creates habits and what motivates people.Shownotes:In this conversation, Jithu Gopal and Chitra Gurjar explore -Working as a software engineer and an early observer of the cost of quality in workActive community-based learning from Java and Ruby user groups in early careerBuilding a social network , learning the “ethics” of software engineering, recognizing and applying design patterns Work at Nilenso, an employee-owned cooperative-like company, applying functional programming principlesLiving the principles of “being agile”, using Test-Driven-Development to shape a problem and approach it from the outside, rather than just build, staying in the problem spaceThe versions of software engineering, 1.0 and 2.0Indispensable systems thinkingShifts in Product Management, building strong foundations of working with engineering using high agency and trust AI Mavens, followers, the power and tools to leverage knowledge and do way moreExamining AI in layers for any organization or system How we organize ourselves differently in the age of machinesKeeping the “Why” in focus with organization memory and problem memoryWhat “post AI” looks like - awakening consciousness and invoking agency, AI cycles bringing more value addSocial bonding as a key to young people’s future of work and lifeBooks that have had a powerful influence on him.For aspiring software engineers to keep building and asking about what “good” looks likeFew conversations flow back and forth in time, not unlike when you meet friends from childhood. In this episode of the Software People Stories podcast, I found myself having tremendous deja-vu moments as Jithu Gopal shared his flow of thoughts across various aspects of software engineering through his 18 plus years of work, how his interests and ways of connecting what he reads, experiences and works with have significance and relevance in the AI whorl that seems to be sweeping us with it and what habits and disciplines can hold us through as we begin to figure out new ways of working, learning and what the future might hold for our children and aspiring engineers. Listen on.

Systems thinking, Social bonding & new contracts with Jithu Gopal

In this episode of Software People Stories, I speak with Mario Lewis, a manufacturing specialist turned IT expert with over 35 years of experience. He talks about his career that began far away from software—in mechanical engineering, manufacturing, operations, and quality—and eventually found its way into the software services world. We talk about what manufacturing can teach software teams, why domain knowledge and business understanding matter, how to stay adaptable through career transitions, and Mario’s experiment with AI-assisted software development through Project Klyve. It’s a thoughtful conversation about learning, reinvention, and doing meaningful work—even when the path is unexpected. Highlights from this conversation: <ul><li>Early passion for aviation led to mechanical engineering, manufacturing, and operations research.</li><li>Manufacturing taught lessons in process rigor, quality, planning, and business constraints.</li><li>Software became a chosen path, not a passion, but Mario approached it with discipline and curiosity.</li><li>Adaptability emerges as a key career skill across industries and eras of change.</li><li>Mario argues that technology is an enabler; real value comes from solving business problems.</li><li>Domain depth and tacit knowledge are becoming more important, especially in GCC-style models.</li><li>Project Klyve tested how far AI and agentic tools could go in building a complete application.</li><li>Advice for early-career professionals: master fundamentals, understand hardware, networks, data, and security.</li><li>Advice for mid-career professionals: keep learning, build domain depth, and understand market forces.</li><li>Retirement feels comfortable because IT was meaningful work, but not Mario’s core passion.</li><li> </li></ul>Mario began his career on the shop floor with planning and manufacturing optimization roles in machine tool and switchgear manufacturing. That early focus on physical manufacturing and basic operations grounded his transition into IT services and enterprise software, where he spent over 35 years leading delivery, consulting, operations and business teams. Along the way, in 2006, he authored a book on the realities of IT service offshoring based on his practical experience in the field. At the end of 2024, Mario stepped away from full-time corporate roles into retirement. He spent that time building Klyve, an automated desktop software factory that implemented an SDLC to build full software applications using agentic AI. It was built around strict engineering controls, deterministic design, and local data privacy. For Mario, managing career shifts comes down to fundamentals. Staying useful across changing industries requires an openness to lifelong learning, disciplined routine, steady execution, and personal standards while tracking industry and technology trends." Mario may be reached at: mariolewis @ gmail.com. The Klyve repo is at <a href="https://github.com/mariolewis/klyve_factory" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://github.com/mariolewis/klyve_factory</a> His book (from 2006) is available at <a href="https://www.amazon.in/Application-Service-Offshoring-Insiders-Guide/dp/0761935258" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.amazon.in/Application-Service-Offshoring-Insiders-Guide/dp/0761935258</a>

In this episode of Software People Stories, I speak with Mario Lewis, a manufacturing specialist turned IT expert with over 35 years of experience. He talks about his career that began far away from software—in mechanical engineering, manufacturing, operations, and quality—and eventually found its way into the software services world. We talk about what manufacturing can teach software teams, why domain knowledge and business understanding matter, how to stay adaptable through career transitions, and Mario’s experiment with AI-assisted software development through Project Klyve. It’s a thoughtful conversation about learning, reinvention, and doing meaningful work—even when the path is unexpected.Highlights from this conversation:Early passion for aviation led to mechanical engineering, manufacturing, and operations research.Manufacturing taught lessons in process rigor, quality, planning, and business constraints.Software became a chosen path, not a passion, but Mario approached it with discipline and curiosity.Adaptability emerges as a key career skill across industries and eras of change.Mario argues that technology is an enabler; real value comes from solving business problems.Domain depth and tacit knowledge are becoming more important, especially in GCC-style models.Project Klyve tested how far AI and agentic tools could go in building a complete application.Advice for early-career professionals: master fundamentals, understand hardware, networks, data, and security.Advice for mid-career professionals: keep learning, build domain depth, and understand market forces.Retirement feels comfortable because IT was meaningful work, but not Mario’s core passion.Mario began his career on the shop floor with planning and manufacturing optimization roles in machine tool and switchgear manufacturing. That early focus on physical manufacturing and basic operations grounded his transition into IT services and enterprise software, where he spent over 35 years leading delivery, consulting, operations and business teams. Along the way, in 2006, he authored a book on the realities of IT service offshoring based on his practical experience in the field.At the end of 2024, Mario stepped away from full-time corporate roles into retirement. He spent that time building Klyve, an automated desktop software factory that implemented an SDLC to build full software applications using agentic AI. It was built around strict engineering controls, deterministic design, and local data privacy.For Mario, managing career shifts comes down to fundamentals. Staying useful across changing industries requires an openness to lifelong learning, disciplined routine, steady execution, and personal standards while tracking industry and technology trends."Mario may be reached at: mariolewis @ gmail.com.The Klyve repo is at https://github.com/mariolewis/klyve_factoryHis book (from 2006) is available at https://www.amazon.in/Application-Service-Offshoring-Insiders-Guide/dp/0761935258 

Business Before Technology with Mario

In this episode of Software People Stories, I speak with Saraswathi, a marketing leader with over 15 years of cross-industry experience,  about the role of marketing in technology—especially how product marketers translate technical ideas into stories customers can understand and care about. We talk about digital communication, customer empathy, product adoption, AI in marketing, useful metrics, and practical career advice for anyone curious about moving into marketing. It is a thoughtful conversation on bridging products, people, and business impact.Among the highlights from this conversation are:<ul><li>Marketing fundamentals stay consistent, but customer pain points differ across industries.</li><li>Digital content must be concise, compelling, and quick to capture attention.</li><li>Audience niches and personalization help messages resonate better.</li><li>Product marketers act as the bridge between product, UX, sales, and customers.</li><li>Training works best when broken into short, accessible, in-product learning moments.</li><li>Email remains effective when segmented and relevant to the audience.</li><li>AI helps with competitive research, brainstorming, mockups, and faster first drafts.</li><li>Brand voice can be protected by giving AI clear style guides, examples, and do’s and don’ts.</li><li>Marketing impact should connect to opportunities, conversions, and revenue—not only vanity metrics.</li><li>Support tickets offer unfiltered customer insight and can shape better messaging and product decisions.</li><li>Career switchers can use transferable skills and start by getting closer to customers.</li><li>Planning, yoga, short walks, and pausing before reacting help Saraswathi stay calm and grounded.</li></ul>﻿Saraswathi Shanth Kumar (Sara) is a marketing leader with over 15 years of cross-industry experience translating complex products into compelling market stories. Her career spans advertising, journalism, SaaS, and Big Tech, leading to her current role at an edtech company in the Bay Area. Sara sees product marketing as the critical translator between product and market — and approaches every challenge with a problem-solver's mindset and a startup's appetite for experimentation. Outside of work, you can find her gardening, practicing yoga, and hiking the many trails in the Bay. My LinkedIn: <a href="http://www.linkedin.com/in/saraskumar" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">http://www.linkedin.com/in/saraskumar</a>

In this episode of Software People Stories, I speak with Saraswathi, a marketing leader with over 15 years of cross-industry experience,  about the role of marketing in technology—especially how product marketers translate technical ideas into stories customers can understand and care about. We talk about digital communication, customer empathy, product adoption, AI in marketing, useful metrics, and practical career advice for anyone curious about moving into marketing. It is a thoughtful conversation on bridging products, people, and business impact.Among the highlights from this conversation are:Marketing fundamentals stay consistent, but customer pain points differ across industries.Digital content must be concise, compelling, and quick to capture attention.Audience niches and personalization help messages resonate better.Product marketers act as the bridge between product, UX, sales, and customers.Training works best when broken into short, accessible, in-product learning moments.Email remains effective when segmented and relevant to the audience.AI helps with competitive research, brainstorming, mockups, and faster first drafts.Brand voice can be protected by giving AI clear style guides, examples, and do’s and don’ts.Marketing impact should connect to opportunities, conversions, and revenue—not only vanity metrics.Support tickets offer unfiltered customer insight and can shape better messaging and product decisions.Career switchers can use transferable skills and start by getting closer to customers.Planning, yoga, short walks, and pausing before reacting help Saraswathi stay calm and grounded.﻿Saraswathi Shanth Kumar (Sara) is a marketing leader with over 15 years of cross-industry experience translating complex products into compelling market stories. Her career spans advertising, journalism, SaaS, and Big Tech, leading to her current role at an edtech company in the Bay Area. Sara sees product marketing as the critical translator between product and market — and approaches every challenge with a problem-solver's mindset and a startup's appetite for experimentation. Outside of work, you can find her gardening, practicing yoga, and hiking the many trails in the Bay.My LinkedIn: http://www.linkedin.com/in/saraskumar

Making Products Matter with Saraswathi Shant Kumar

My guest today is Chander Sankaran, an ERP and change management Specialist. With a professional background in finance and accounting, he has played many cross-functional roles that bridge the gap between finance and information technology.  In this conversation, Chander talks about<ul><li>Beginning his career in finance and accounting, then entering software through early ERP implementation work in a manufacturing plant in India.</li><li>His move to the U.S. in the late 1990s</li><li>How his accounting and operational background helped him stand out in consulting by giving him stronger context for business requirements.</li><li>Critical factors for smooth go-lives</li><li>The importance of change management for any enterprise technology work </li><li>How factors such as global teams and hybrid work models require flexibility</li><li>The benefits of AI in improving individual productivity</li><li>Some concerns about AI’s environmental footprint and its potential effect on entry-level roles.</li><li>He also shares practical career advice including keeping a resume updated, understanding that everyone is replaceable</li><li>His personal practices for staying grounded</li></ul> Chander S is an ERP Specialist based in Texas, and originally from Chennai, India. With a professional background in finance and accounting, he has played in cross-functional roles that bridge the gap between finance and information technology. Outside of work, Chander enjoys yoga, trekking, and volunteering in his local community. He may be contacted at <a href="https://www.linkedin.com/in/chander-sankaran-9027503/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/chander-sankaran-9027503/</a>

My guest today is Chander Sankaran, an ERP and change management Specialist. With a professional background in finance and accounting, he has played many cross-functional roles that bridge the gap between finance and information technology. In this conversation, Chander talks aboutBeginning his career in finance and accounting, then entering software through early ERP implementation work in a manufacturing plant in India.His move to the U.S. in the late 1990sHow his accounting and operational background helped him stand out in consulting by giving him stronger context for business requirements.Critical factors for smooth go-livesThe importance of change management for any enterprise technology work How factors such as global teams and hybrid work models require flexibilityThe benefits of AI in improving individual productivitySome concerns about AI’s environmental footprint and its potential effect on entry-level roles.He also shares practical career advice including keeping a resume updated, understanding that everyone is replaceableHis personal practices for staying groundedChander S is an ERP Specialist based in Texas, and originally from Chennai, India. With a professional background in finance and accounting, he has played in cross-functional roles that bridge the gap between finance and information technology. Outside of work, Chander enjoys yoga, trekking, and volunteering in his local community.He may be contacted at https://www.linkedin.com/in/chander-sankaran-9027503/

Accounting, ERP and Change management with Chander Sankaran

My guest today is Mathangi Sri Ramachandran, Co-Founder of YuVerse. The conversation included Mathangi ’s early fascination with data-driven decision-making → AI as a force for democratisation → empathy at scale → career choices driven by impact → sustaining a long career as a woman → the ecosystem behind innovation and patents.00:00 – Introduction: A life and career deeply rooted in AIMathangi introduces herself as someone whose “heart and soul” are in AI. She talks about her role as CEO and co-founder of U-verse, a last-mile AI company focused on taking frontier AI models beyond experimentation and applying them to real business workflows and outcomes.01:20 – What does “last-mile AI” really mean?Mathangi explains the gap between powerful frontier models and actual enterprise outcomes. She discusses how AI transformation requires bringing together technology, workflows and the human elements of work—across banking, insurance, real estate, retail and other industries.02:30 – A 20-year journey in data scienceLong before the current generative AI wave, Mathangi was working in data science and analytics. She reflects on the long history of AI and reminds us that data-driven decision-making, machine learning and conversational technologies have been evolving for decades.03:50 – The campus interview that changed her career directionA simple example during a GE campus interview at NIT Trichy—using data to decide where windmills should be located—sparked Mathangi’s interest in scientific, data-driven decision-making. That idea became a defining theme throughout her career.05:00 – Using data to improve decisions at scaleFrom marketing analytics to risk scorecards in financial services, Mathangi saw first-hand how large-scale data could improve enterprise decision-making. She shares her belief that moving from human judgement alone towards data-informed systems can help reduce bias and democratise access.06:30 – Can machines deliver empathy at scale?In one of the most thought-provoking parts of the conversation, Mathangi challenges the assumption that machines cannot be empathetic. Drawing from her experience with conversational AI, she argues that machines can deliver consistent empathy across hundreds or thousands of difficult interactions in ways that are extremely challenging for human agents.07:40 – Why difficult customer conversations can escalateUsing debt collection conversations as an example, Mathangi explains the emotional burden placed on human agents who may handle a hundred difficult calls every day. She demonstrates how quickly a human-to-human interaction can escalate—and how well-designed conversational AI can maintain consistency and bring the emotional temperature down.09:35 – From an idea today to an outcome tomorrowThe arrival of large language models has dramatically shortened the distance between an idea and its implementation. For Mathangi, this makes the current era one of the most exciting times to work in AI.10:55 – What continues to motivate her after two decades?The answer is simple: possibilities. Mathangi talks about her desire to use technology to build a better world by reducing bias, improving decision-making and democratising access to services.11:20 – AI, financial inclusion and a more equitable worldBetter decision-making can enable deeper financial inclusion and expand access to capital. Mathangi connects AI and data science to a larger societal purpose: ensuring that more deserving people can access opportunities without being excluded by individual biases or subjective judgements.12:50 – AI and access to healthcare and emotional supportMathangi explores the possibilities of AI in healthcare and therapy, particularly for people in underserved communities. She imagines a woman in a remote village being able to safely access a culturally aware, local-language AI companion when human support may be unavailable or difficult to approach.14:45 – Why this is the best time to be working in AIIdeas that once took years to reach the market can now move from concept to implementation at extraordinary speed. Mathangi reflects on why she has never enjoyed her work more than she does today.15:55 – Where the rubber meets the road: making AI deliver impactLooking across her career, Mathangi describes her current entrepreneurial journey as particularly impactful because she can not only build AI solutions but also take them directly into enterprises—improving processes such as customer conversations, underwriting and claims processing.17:40 – The AI tailwind and pressure from the boardroomAI adoption is increasingly being driven from the top. Boards are asking organisations what they have done with AI and, importantly, what measurable impact it has created. Mathangi discusses both the opportunities and the risks of this pressure.18:35 – Leadership is hard 95% of the timeMathangi offers a candid perspective on leadership: most days can be difficult and can test your sense of purpose. But the small percentage of moments when you see meaningful impact can make all that difficulty worthwhile.19:15 – Choosing a bigger canvas over compensationThroughout her career, Mathangi has made decisions based on one guiding principle: where can she create the maximum impact? At times, that has meant walking away from significant compensation and lifestyle benefits in exchange for a larger canvas on which to build and contribute.20:55 – A lesson from her mother: “Keep your job”Mathangi shares one of the most important pieces of advice she received from her mother. Through motherhood, travel, guilt and the many pressures women encounter, she remained determined not to compromise on her career.21:40 – Designing life around a career, not a career around everything elseRather than fitting her career around domestic responsibilities, Mathangi says she consciously worked to organise her personal life so that her career could continue. She reflects on the grit required to sustain a career over more than two decades.23:20 – The invisible infrastructure behind a long careerMathangi speaks with gratitude about mentors, organisations and, especially, her family. She explains why support at home is foundational to sustaining a demanding career—and why a headwind at home can be far harder to overcome than challenges at work.25:00 – Staying rooted in Bangalore while building a global careerDespite opportunities to relocate internationally, Mathangi made a conscious decision to keep Bangalore as her family’s home base. Instead of treating that as a limitation, she built her career around the constraint—travelling extensively while remaining rooted in one place.27:00 – The story behind nearly 100 patentsMathangi credits the innovation ecosystem at [24]7.ai for creating the conditions in which patentable ideas could flourish. She discusses why innovation requires more than individual creativity—it also needs organisational encouragement, funding, legal support and processes.28:20 – What makes an idea patent-worthy?Not every mathematically sophisticated model becomes a patent. Mathangi explains that patentable ideas need novelty, meaningful technological application and executability. She reflects on what she learned about innovation, prior art and protecting ideas during her time in an organisation that actively encouraged invention.29:58 – The ecosystem that enables innovationReflecting on Mathangi’s experience of filing nearly 100 patents, the conversation highlights how innovation is rarely an individual effort alone. A supportive organisational ecosystem—including encouragement from the team, financial resources, processes and institutional support—can make a significant difference in turning ideas into protected innovations.31:15 – Career advice for young women: build grit and resilienceMathangi’s first piece of advice is particularly for young women entering the workforce: develop the grit not only to grow, but first to survive and persist. She speaks candidly about the headwinds women can encounter over the course of a career, including societal biases, workplace biases and even self-imposed pressures.31:50 – Why biases can become more visible as women progressMathangi reflects on something she wishes she had understood earlier: biases may become more pronounced as women move into more senior positions. Being aware of this possibility, she says, can help women build the resilience needed to navigate difficult moments without being completely shaken by them.32:55 – “Resilience is the crux of a long career”Her advice is simple and powerful: don’t give up. For women in particular, where the headwinds may be stronger, resilience and the ability to keep going are fundamental to sustaining a long career.33:10 – Advice for AI professionals: start with the problem, not the technologyWhether the technology is AI, LLMs, data science, machine learning or whatever comes next, one thing remains constant: the problem. Mathangi urges technology professionals to develop genuine empathy for the person experiencing the problem they are trying to solve.33:35 – Let the problem guide the solutionRather than starting with a technology and searching for a problem to fit it into, Mathangi advocates the reverse: understand and empathise with a meaningful problem, and then use your skills and technology to solve it. Finding the right problem to work on, she suggests, can shape as much as 90% of a career.34:00 – Exposure, curiosity and finding problems worth solvingFinding meaningful problems requires stepping outside one’s immediate world—speaking with people, seeking different perspectives and actively looking for opportunities to contribute. This mindset is valuable whether someone is just beginning their career or is already a senior executive.34:25 – Ending where the conversation began: empathyThe episode comes full circle. What began as a discussion about empathy in AI ends with empathy as Mathangi’s central piece of career advice: understand the people and problems you are solving for. Alongside grit and resilience, empathy becomes the connecting thread across technology, innovation, leadership and a long career. <h3>Quotable quotes</h3>“Machines can do empathy at scale,” “Give me a handkerchief, I’ll make it into a huge blanket and then paint on it,” “Whatever it is, I’m not going to compromise my career—and I’m unabashedly so.” Brief Bio Mathangi Sri Ramachandran is an accomplished technology leader, data scientist, and AI practitioner with extensive experience in building and scaling data-driven products, platforms, and teams. Over the course of her career, she has worked at the intersection of technology, data, artificial intelligence, and business, helping organisations translate complex technical possibilities into meaningful outcomes.Beyond her professional achievements, Mathangi is passionate about building strong technology communities, mentoring the next generation of professionals, and encouraging more women to grow and thrive in technology and leadership roles. She brings a valuable combination of deep technical expertise, leadership experience, curiosity, and a practical perspective on how technology continues to shape the way we work and build.In this conversation, we explore Mathangi’s journey through the world of technology and data, the experiences and choices that have shaped her career, and the lessons she has gathered along the way. Mathangi can be reached at <a href="https://www.linkedin.com/in/mathangisri/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/mathangisri/</a>

My guest today is Mathangi Sri Ramachandran, Co-Founder of YuVerse. The conversation included Mathangi ’s early fascination with data-driven decision-making → AI as a force for democratisation → empathy at scale → career choices driven by impact → sustaining a long career as a woman → the ecosystem behind innovation and patents.00:00 – Introduction: A life and career deeply rooted in AIMathangi introduces herself as someone whose “heart and soul” are in AI. She talks about her role as CEO and co-founder of U-verse, a last-mile AI company focused on taking frontier AI models beyond experimentation and applying them to real business workflows and outcomes.01:20 – What does “last-mile AI” really mean?Mathangi explains the gap between powerful frontier models and actual enterprise outcomes. She discusses how AI transformation requires bringing together technology, workflows and the human elements of work—across banking, insurance, real estate, retail and other industries.02:30 – A 20-year journey in data scienceLong before the current generative AI wave, Mathangi was working in data science and analytics. She reflects on the long history of AI and reminds us that data-driven decision-making, machine learning and conversational technologies have been evolving for decades.03:50 – The campus interview that changed her career directionA simple example during a GE campus interview at NIT Trichy—using data to decide where windmills should be located—sparked Mathangi’s interest in scientific, data-driven decision-making. That idea became a defining theme throughout her career.05:00 – Using data to improve decisions at scaleFrom marketing analytics to risk scorecards in financial services, Mathangi saw first-hand how large-scale data could improve enterprise decision-making. She shares her belief that moving from human judgement alone towards data-informed systems can help reduce bias and democratise access.06:30 – Can machines deliver empathy at scale?In one of the most thought-provoking parts of the conversation, Mathangi challenges the assumption that machines cannot be empathetic. Drawing from her experience with conversational AI, she argues that machines can deliver consistent empathy across hundreds or thousands of difficult interactions in ways that are extremely challenging for human agents.07:40 – Why difficult customer conversations can escalateUsing debt collection conversations as an example, Mathangi explains the emotional burden placed on human agents who may handle a hundred difficult calls every day. She demonstrates how quickly a human-to-human interaction can escalate—and how well-designed conversational AI can maintain consistency and bring the emotional temperature down.09:35 – From an idea today to an outcome tomorrowThe arrival of large language models has dramatically shortened the distance between an idea and its implementation. For Mathangi, this makes the current era one of the most exciting times to work in AI.10:55 – What continues to motivate her after two decades?The answer is simple: possibilities. Mathangi talks about her desire to use technology to build a better world by reducing bias, improving decision-making and democratising access to services.11:20 – AI, financial inclusion and a more equitable worldBetter decision-making can enable deeper financial inclusion and expand access to capital. Mathangi connects AI and data science to a larger societal purpose: ensuring that more deserving people can access opportunities without being excluded by individual biases or subjective judgements.12:50 – AI and access to healthcare and emotional supportMathangi explores the possibilities of AI in healthcare and therapy, particularly for people in underserved communities. She imagines a woman in a remote village being able to safely access a culturally aware, local-language AI companion when human support may be unavailable or difficult to approach.14:45 – Why this is the best time to be working in AIIdeas that once took years to reach the market can now move from concept to implementation at extraordinary speed. Mathangi reflects on why she has never enjoyed her work more than she does today.15:55 – Where the rubber meets the road: making AI deliver impactLooking across her career, Mathangi describes her current entrepreneurial journey as particularly impactful because she can not only build AI solutions but also take them directly into enterprises—improving processes such as customer conversations, underwriting and claims processing.17:40 – The AI tailwind and pressure from the boardroomAI adoption is increasingly being driven from the top. Boards are asking organisations what they have done with AI and, importantly, what measurable impact it has created. Mathangi discusses both the opportunities and the risks of this pressure.18:35 – Leadership is hard 95% of the timeMathangi offers a candid perspective on leadership: most days can be difficult and can test your sense of purpose. But the small percentage of moments when you see meaningful impact can make all that difficulty worthwhile.19:15 – Choosing a bigger canvas over compensationThroughout her career, Mathangi has made decisions based on one guiding principle: where can she create the maximum impact? At times, that has meant walking away from significant compensation and lifestyle benefits in exchange for a larger canvas on which to build and contribute.20:55 – A lesson from her mother: “Keep your job”Mathangi shares one of the most important pieces of advice she received from her mother. Through motherhood, travel, guilt and the many pressures women encounter, she remained determined not to compromise on her career.21:40 – Designing life around a career, not a career around everything elseRather than fitting her career around domestic responsibilities, Mathangi says she consciously worked to organise her personal life so that her career could continue. She reflects on the grit required to sustain a career over more than two decades.23:20 – The invisible infrastructure behind a long careerMathangi speaks with gratitude about mentors, organisations and, especially, her family. She explains why support at home is foundational to sustaining a demanding career—and why a headwind at home can be far harder to overcome than challenges at work.25:00 – Staying rooted in Bangalore while building a global careerDespite opportunities to relocate internationally, Mathangi made a conscious decision to keep Bangalore as her family’s home base. Instead of treating that as a limitation, she built her career around the constraint—travelling extensively while remaining rooted in one place.27:00 – The story behind nearly 100 patentsMathangi credits the innovation ecosystem at [24]7.ai for creating the conditions in which patentable ideas could flourish. She discusses why innovation requires more than individual creativity—it also needs organisational encouragement, funding, legal support and processes.28:20 – What makes an idea patent-worthy?Not every mathematically sophisticated model becomes a patent. Mathangi explains that patentable ideas need novelty, meaningful technological application and executability. She reflects on what she learned about innovation, prior art and protecting ideas during her time in an organisation that actively encouraged invention.29:58 – The ecosystem that enables innovationReflecting on Mathangi’s experience of filing nearly 100 patents, the conversation highlights how innovation is rarely an individual effort alone. A supportive organisational ecosystem—including encouragement from the team, financial resources, processes and institutional support—can make a significant difference in turning ideas into protected innovations.31:15 – Career advice for young women: build grit and resilienceMathangi’s first piece of advice is particularly for young women entering the workforce: develop the grit not only to grow, but first to survive and persist. She speaks candidly about the headwinds women can encounter over the course of a career, including societal biases, workplace biases and even self-imposed pressures.31:50 – Why biases can become more visible as women progressMathangi reflects on something she wishes she had understood earlier: biases may become more pronounced as women move into more senior positions. Being aware of this possibility, she says, can help women build the resilience needed to navigate difficult moments without being completely shaken by them.32:55 – “Resilience is the crux of a long career”Her advice is simple and powerful: don’t give up. For women in particular, where the headwinds may be stronger, resilience and the ability to keep going are fundamental to sustaining a long career.33:10 – Advice for AI professionals: start with the problem, not the technologyWhether the technology is AI, LLMs, data science, machine learning or whatever comes next, one thing remains constant: the problem. Mathangi urges technology professionals to develop genuine empathy for the person experiencing the problem they are trying to solve.33:35 – Let the problem guide the solutionRather than starting with a technology and searching for a problem to fit it into, Mathangi advocates the reverse: understand and empathise with a meaningful problem, and then use your skills and technology to solve it. Finding the right problem to work on, she suggests, can shape as much as 90% of a career.34:00 – Exposure, curiosity and finding problems worth solvingFinding meaningful problems requires stepping outside one’s immediate world—speaking with people, seeking different perspectives and actively looking for opportunities to contribute. This mindset is valuable whether someone is just beginning their career or is already a senior executive.34:25 – Ending where the conversation began: empathyThe episode comes full circle. What began as a discussion about empathy in AI ends with empathy as Mathangi’s central piece of career advice: understand the people and problems you are solving for. Alongside grit and resilience, empathy becomes the connecting thread across technology, innovation, leadership and a long career.Quotable quotes“Machines can do empathy at scale,” “Give me a handkerchief, I’ll make it into a huge blanket and then paint on it,” “Whatever it is, I’m not going to compromise my career—and I’m unabashedly so.”Brief BioMathangi Sri Ramachandran is an accomplished technology leader, data scientist, and AI practitioner with extensive experience in building and scaling data-driven products, platforms, and teams. Over the course of her career, she has worked at the intersection of technology, data, artificial intelligence, and business, helping organisations translate complex technical possibilities into meaningful outcomes.Beyond her professional achievements, Mathangi is passionate about building strong technology communities, mentoring the next generation of professionals, and encouraging more women to grow and thrive in technology and leadership roles. She brings a valuable combination of deep technical expertise, leadership experience, curiosity, and a practical perspective on how technology continues to shape the way we work and build.In this conversation, we explore Mathangi’s journey through the world of technology and data, the experiences and choices that have shaped her career, and the lessons she has gathered along the way.Mathangi can be reached at https://www.linkedin.com/in/mathangisri/ 

An Idea Today, an Outcome Tomorrow with Mathangi Sri Ramachandran

My guest today is Sree Krishna Kumaraswamy, known more popularly as Krishna, a data and analytics leader with over 20 years of experience spanning consulting and large enterprise technology companies In this conversation, Krishna <ul><li>traces his journey from growing up in Chennai with an expected engineering path to discovering mathematics and statistics through the Indian Statistical Institute</li><li>Talks about his early work in applied statistics and computer vision,applying concepts of  machine learning before “data science” became a mainstream term.</li><li>Describes how Carnegie Mellon’s Knowledge Discovery and Data Mining program deepened his exposure to algorithms, natural language processing, unstructured data, and the business applications of predictive modeling.</li><li>Emphasizes that generative AI is powerful but costly, and the need to use it thoughtfully</li><li>Stresses that responsibility for ethical data use is shared across organizations, including data scientists, engineers, governance teams, risk leaders, executives, and users.</li><li>Touches on data poisoning, cyber threats, and the growing need for systems that can detect fast-moving patterns without overreacting to every small data change.</li><li>His career advice for those aspiring to enter or switch to data science roles</li><li>Shares his grounding principle is the “so what, who cares?” test: work on problems that matter to someone, find partners who care about the outcome, and focus on impact rather than technology for its own sake.</li></ul> Krishna is a data and analytics leader with over 20 years of experience spanning consulting and large enterprise technology companies. With an academic background in statistics and machine learning, he has spent his career turning data and AI into tools that help businesses make better decisions.Most recently, he led data and AI product teams at Salesforce, where he built self-serve analytics and AI tools used by tens of thousands of employees, and predictive systems that helped the company better serve its customers. Throughout his career, he has focused on bridging the gap between technical teams and business needs, bringing a product mindset to data science and AI.He lives in the San Francisco Bay Area with his wife and two kids.His profile : <a href="https://www.linkedin.com/in/kkumaraswamy/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/kkumaraswamy/</a>

My guest today is Sree Krishna Kumaraswamy, known more popularly as Krishna, a data and analytics leader with over 20 years of experience spanning consulting and large enterprise technology companiesIn this conversation, Krishna traces his journey from growing up in Chennai with an expected engineering path to discovering mathematics and statistics through the Indian Statistical InstituteTalks about his early work in applied statistics and computer vision,applying concepts of  machine learning before “data science” became a mainstream term.Describes how Carnegie Mellon’s Knowledge Discovery and Data Mining program deepened his exposure to algorithms, natural language processing, unstructured data, and the business applications of predictive modeling.Emphasizes that generative AI is powerful but costly, and the need to use it thoughtfullyStresses that responsibility for ethical data use is shared across organizations, including data scientists, engineers, governance teams, risk leaders, executives, and users.Touches on data poisoning, cyber threats, and the growing need for systems that can detect fast-moving patterns without overreacting to every small data change.His career advice for those aspiring to enter or switch to data science rolesShares his grounding principle is the “so what, who cares?” test: work on problems that matter to someone, find partners who care about the outcome, and focus on impact rather than technology for its own sake.Krishna is a data and analytics leader with over 20 years of experience spanning consulting and large enterprise technology companies. With an academic background in statistics and machine learning, he has spent his career turning data and AI into tools that help businesses make better decisions.Most recently, he led data and AI product teams at Salesforce, where he built self-serve analytics and AI tools used by tens of thousands of employees, and predictive systems that helped the company better serve its customers. Throughout his career, he has focused on bridging the gap between technical teams and business needs, bringing a product mindset to data science and AI.He lives in the San Francisco Bay Area with his wife and two kids.His profile : https://www.linkedin.com/in/kkumaraswamy/

Enabling Better Decisions Through Data with Sree Krishna Kumaraswamy

My guest today is Elangovan Shanmugam,  a seasoned software professional with over 30 years of experience. Among the multiple roles Elangovan has played are Distinguished Engineer, Director of Engineering, leading strategic AI transformation initiatives in a large organization. In this conversation Elangovan:<ul><li>Traces his journey from FoxPro and 4MB RAM days to AI engineering</li><li>Shares how software evolved from standalone systems to connected business ecosystems.</li><li>A major theme is that the problem often stays the same, but the solution changes.</li><li>Elangovan describes AI agents as digital humans that help people interact naturally with systems.</li><li>He explains that in software patents, the method of solving a problem can be patentable.</li><li>His advice for professionals: embrace AI, keep evolving, and don’t stay in a comfort zone.</li></ul> Elangovan Shanmugam is a seasoned software professional with over 30 years of experience. He has held multiple roles—Distinguished Engineer, Director of Engineering, and now leading strategic AI transformation initiatives. Most recently, he led a 40-person organization through a fundamental shift: teaching traditional engineering teams to think and operate as AI engineering organizations. He has worked at the intersection of deep technical architecture and enterprise leadership—helping CTOs and organizations figure out what changes when AI becomes native to how you build. He also has the distinction of receiving multiple innovation awards and has over 20 patents issued to his credit!He is super passionate about solving tough problems for customers! He may be reached at: elangovan.shanmugam @ gmail.com

My guest today is Elangovan Shanmugam,  a seasoned software professional with over 30 years of experience. Among the multiple roles Elangovan has played are Distinguished Engineer, Director of Engineering, leading strategic AI transformation initiatives in a large organization.In this conversation Elangovan:Traces his journey from FoxPro and 4MB RAM days to AI engineeringShares how software evolved from standalone systems to connected business ecosystems.A major theme is that the problem often stays the same, but the solution changes.Elangovan describes AI agents as digital humans that help people interact naturally with systems.He explains that in software patents, the method of solving a problem can be patentable.His advice for professionals: embrace AI, keep evolving, and don’t stay in a comfort zone.Elangovan Shanmugam is a seasoned software professional with over 30 years of experience. He has held multiple roles—Distinguished Engineer, Director of Engineering, and now leading strategic AI transformation initiatives. Most recently, he led a 40-person organization through a fundamental shift: teaching traditional engineering teams to think and operate as AI engineering organizations. He has worked at the intersection of deep technical architecture and enterprise leadership—helping CTOs and organizations figure out what changes when AI becomes native to how you build. He also has the distinction of receiving multiple innovation awards and has over 20 patents issued to his credit!He is super passionate about solving tough problems for customers!He may be reached at: elangovan.shanmugam @ gmail.com 

AI, Integration, and Innovation with Elangovan Shanmugam

In this episode of Software People Stories, Gayatri Kalyanaraman speaks with Indra Vidyaprakash, Vice President | Workday Chennai Site Leader, for a conversation spanning three decades of technology evolution. From her early fascination with programming in Coimbatore and her journey through Cornell University, Oracle, and Silicon Valley, to returning to Chennai to establish and scale Workday's India presence, Indira shares lessons learned across every major technology shift—from the internet era and enterprise software revolution to today's AI-driven future.The conversation explores product management, customer-centric innovation, leadership, mentorship, women in technology, startup investing, and the importance of staying curious in a rapidly changing world. Through stories of reinvention, growth, and building high-performing teams, Indira offers valuable insights for technology professionals, aspiring leaders, and lifelong learners navigating their own careersTimestamped Show Notes<h3>00:00 – Welcome to Software People Stories</h3>Gayatri introduces Indra Vidyaprakash, Site Leader at Workday India and a technology leader whose career spans Oracle, Workday, product management, and organizational leadership.<h3>00:44 – The Atari That Started It All</h3>Indra reflects on her childhood in Coimbatore and how an Atari gaming console sparked her fascination with logic, programming, and problem-solving. Long before technology became a career, it had already become a passion.<h3>02:19 – PSG Tech, Family Legacy, and the Pursuit of Learning</h3>A discussion about growing up in Coimbatore, studying Computer Science at PSG Tech, the influence of her grandfather J.R. Damodaran, and the importance of education and lifelong learning.<h3>04:00 – HCL, Cornell, and the American Dream</h3>Indra shares her journey from HCL Technologies in Chennai to pursuing a Master's degree at Cornell University, experiencing a new educational culture, and entering the world of advanced computing.<h3>06:30 – Landing in Silicon Valley During the Oracle Era</h3>What it was like to join Oracle in 1997 and witness the rise of enterprise software, internet adoption, and the dot-com boom from the heart of Silicon Valley.<h3>08:10 – Why Engineering Alone Wasn't Enough</h3>After nearly a decade as a software engineer, Indra found herself asking an important question: "Who is actually using what I'm building?" That question ultimately led her toward product management.<h3>10:45 – Reinventing Herself Through Product Management</h3>Indra discusses taking a career break, exploring an MBA, learning new business skills, and ultimately transitioning into product management through curiosity and self-discovery rather than a predefined career plan.<h3>14:08 – Learning Design Thinking Before It Became a Buzzword</h3>How customer empathy, usability testing, user-centered design, and direct customer interaction became foundational to her product leadership approach.<h3>16:00 – The Magic of Product Conferences</h3>Indra reflects on Oracle OpenWorld, customer interactions, product demonstrations, analyst briefings, and how conferences became one of her favorite aspects of product management.<h3>18:38 – Moving from Oracle to Workday</h3>A story about relationships, professional networks, and following trusted colleagues into a new opportunity that would shape the next decade of her career.<h3>20:30 – Why Culture Matters</h3>Indra explains how Workday's employee-centric culture, customer focus, and collaborative environment became major factors in her decision to join the company.<h3>22:17 – Entering the World of HR Technology</h3>The challenges and opportunities of moving into HR and Financial ERP systems, understanding customer trust, compliance, security, and building enterprise software at scale.<h3>26:00 – NEYTHRI and Supporting Women Leaders</h3>Indra discusses joining NEYTHRI, a professional network for South Asian women leaders, and how community-building eventually led her to participate as an investor in NEYTHRI’s venture fund.<h3>28:45 – Why Representation Matters</h3>A conversation about women entrepreneurs, access to capital, and the importance of creating opportunities for women founders and leaders.<h3>30:00 – Returning Home After Three Decades</h3>After nearly 30 years in the United States, Indra shares the story behind her decision to return to Chennai and lead the establishment of Workday's India operations.<h3>32:00 – Building Workday Chennai</h3>How Workday selected Chennai, what it takes to build a new technology center from the ground up, and why creating culture is just as important as creating infrastructure.<h3>34:00 – Scaling Talent and Building Future Leaders</h3>Indra discusses mentoring, leadership development, gender diversity, and the excitement of working with AI-native graduates entering the workforce today.<h3>36:30 – Product Innovation, AI, and Learning Through Experimentation</h3>Lessons from introducing chatbot technology years before today's Generative AI wave, balancing innovation with customer trust, and the importance of thoughtful experimentation.<h3>39:00 – The Importance of Small Experiments</h3>Why successful innovation often begins with a small group of trusted customers, rapid feedback loops, and disciplined iteration.<h3>42:00 – The Most Important Leadership Trait: Growth Mindset</h3>Indra reflects on the influence of lifelong learning, adaptability, and why curiosity has remained her greatest career advantage.<h3>44:00 – AI, Accessibility, and India's Digital Leap</h3>A fascinating discussion on how AI is democratizing access to knowledge, enabling multilingual interaction, and creating opportunities across diverse communities.<h3>46:00 – Human Connections Still Matter</h3>Despite advances in AI, Indra emphasizes that relationships, collaboration, trust, and empathy remain the foundations of meaningful work and leadership.<h3>48:00 – Final Advice: Stay Curious</h3>Indra closes the episode with her advice for the next generation: continue learning, embrace change, remain curious, and never lose sight of the human element behind technology. <a href="https://www.linkedin.com/in/indiravidyaprakash/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/indiravidyaprakash/</a>

In this episode of Software People Stories, Gayatri Kalyanaraman speaks with Indra Vidyaprakash, Vice President | Workday Chennai Site Leader, for a conversation spanning three decades of technology evolution. From her early fascination with programming in Coimbatore and her journey through Cornell University, Oracle, and Silicon Valley, to returning to Chennai to establish and scale Workday's India presence, Indira shares lessons learned across every major technology shift—from the internet era and enterprise software revolution to today's AI-driven future.The conversation explores product management, customer-centric innovation, leadership, mentorship, women in technology, startup investing, and the importance of staying curious in a rapidly changing world. Through stories of reinvention, growth, and building high-performing teams, Indira offers valuable insights for technology professionals, aspiring leaders, and lifelong learners navigating their own careersTimestamped Show Notes00:00 – Welcome to Software People StoriesGayatri introduces Indra Vidyaprakash, Site Leader at Workday India and a technology leader whose career spans Oracle, Workday, product management, and organizational leadership.00:44 – The Atari That Started It AllIndra reflects on her childhood in Coimbatore and how an Atari gaming console sparked her fascination with logic, programming, and problem-solving. Long before technology became a career, it had already become a passion.02:19 – PSG Tech, Family Legacy, and the Pursuit of LearningA discussion about growing up in Coimbatore, studying Computer Science at PSG Tech, the influence of her grandfather J.R. Damodaran, and the importance of education and lifelong learning.04:00 – HCL, Cornell, and the American DreamIndra shares her journey from HCL Technologies in Chennai to pursuing a Master's degree at Cornell University, experiencing a new educational culture, and entering the world of advanced computing.06:30 – Landing in Silicon Valley During the Oracle EraWhat it was like to join Oracle in 1997 and witness the rise of enterprise software, internet adoption, and the dot-com boom from the heart of Silicon Valley.08:10 – Why Engineering Alone Wasn't EnoughAfter nearly a decade as a software engineer, Indra found herself asking an important question: "Who is actually using what I'm building?" That question ultimately led her toward product management.10:45 – Reinventing Herself Through Product ManagementIndra discusses taking a career break, exploring an MBA, learning new business skills, and ultimately transitioning into product management through curiosity and self-discovery rather than a predefined career plan.14:08 – Learning Design Thinking Before It Became a BuzzwordHow customer empathy, usability testing, user-centered design, and direct customer interaction became foundational to her product leadership approach.16:00 – The Magic of Product ConferencesIndra reflects on Oracle OpenWorld, customer interactions, product demonstrations, analyst briefings, and how conferences became one of her favorite aspects of product management.18:38 – Moving from Oracle to WorkdayA story about relationships, professional networks, and following trusted colleagues into a new opportunity that would shape the next decade of her career.20:30 – Why Culture MattersIndra explains how Workday's employee-centric culture, customer focus, and collaborative environment became major factors in her decision to join the company.22:17 – Entering the World of HR TechnologyThe challenges and opportunities of moving into HR and Financial ERP systems, understanding customer trust, compliance, security, and building enterprise software at scale.26:00 – NEYTHRI and Supporting Women LeadersIndra discusses joining NEYTHRI, a professional network for South Asian women leaders, and how community-building eventually led her to participate as an investor in NEYTHRI’s venture fund.28:45 – Why Representation MattersA conversation about women entrepreneurs, access to capital, and the importance of creating opportunities for women founders and leaders.30:00 – Returning Home After Three DecadesAfter nearly 30 years in the United States, Indra shares the story behind her decision to return to Chennai and lead the establishment of Workday's India operations.32:00 – Building Workday ChennaiHow Workday selected Chennai, what it takes to build a new technology center from the ground up, and why creating culture is just as important as creating infrastructure.34:00 – Scaling Talent and Building Future LeadersIndra discusses mentoring, leadership development, gender diversity, and the excitement of working with AI-native graduates entering the workforce today.36:30 – Product Innovation, AI, and Learning Through ExperimentationLessons from introducing chatbot technology years before today's Generative AI wave, balancing innovation with customer trust, and the importance of thoughtful experimentation.39:00 – The Importance of Small ExperimentsWhy successful innovation often begins with a small group of trusted customers, rapid feedback loops, and disciplined iteration.42:00 – The Most Important Leadership Trait: Growth MindsetIndra reflects on the influence of lifelong learning, adaptability, and why curiosity has remained her greatest career advantage.44:00 – AI, Accessibility, and India's Digital LeapA fascinating discussion on how AI is democratizing access to knowledge, enabling multilingual interaction, and creating opportunities across diverse communities.46:00 – Human Connections Still MatterDespite advances in AI, Indra emphasizes that relationships, collaboration, trust, and empathy remain the foundations of meaningful work and leadership.48:00 – Final Advice: Stay CuriousIndra closes the episode with her advice for the next generation: continue learning, embrace change, remain curious, and never lose sight of the human element behind technology.https://www.linkedin.com/in/indiravidyaprakash/ 

Leading Through Every Technology Wave with Indira vidyaprakash

My guest today is Ian Hogg, the Chairman of SolvedBy.ai, an applied AI company helping SaaS vendors embed enterprise-grade forecasting, demand and decision intelligence directly into their platforms. In this conversation,<ul><li>Ian shares his background, from the Royal Navy and Xerox to building early web businesses, a SaaS platform, and an AI-focused company.</li><li>He describes how his SaaS business began by solving his own operational problem and then expanded when others in the industry recognized the same need.</li><li>He shares how, In enterprise AI,  one needs to  distinguish decision-support and forecasting systems from generative AI</li><li>Ian highlights that AI adoption in organizations depends heavily on leadership behavior</li><li>The conversation also covers mindset barriers, the empowerment of non-technical users, and the need to build confidence through hands-on experimentation rather than waiting for formal permission or perfect readiness.</li><li>On branding and customer acceptance, Ian explains that people may resist AI if it feels like replacement, but respond more positively when it is framed as assistive and human-in-the-loop.</li><li>He shares career advice for both newcomers and mid-career professionals</li><li>In closing, he shares aspects that help him stay grounded </li></ul> Ian Hogg is Chairman of SolvedBy.ai, an applied AI company helping SaaS vendors embed enterprise-grade forecasting, demand and decision intelligence directly into their platforms.He has spent his career building, scaling and investing in software businesses, with a particular focus on workforce management, SaaS partnerships and AI-driven operational optimisation.Ian is a strong voice on the “SaaS apocalypse” — the idea that AI will expose weak, seat-based SaaS models while creating huge opportunities for vendors that own deep workflow, data and distribution.At SolvedBy.ai, he is focused on helping SaaS companies add the AI layer their customers now expect, without needing to build specialist AI engines from scratch. Ian may be reached at:<a href="https://x.com/ianhogg88" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://x.com/ianhogg88</a><a href="https://www.linkedin.com/in/ianhoggworktechgroup/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://www.linkedin.com/in/ianhoggworktechgroup/</a><a href="https://solvedby.ai/" rel="noopener noreferrer" target="_blank" style="background-color: transparent; color: rgb(17, 85, 204);">https://solvedby.ai/</a>

My guest today is Ian Hogg, the Chairman of SolvedBy.ai, an applied AI company helping SaaS vendors embed enterprise-grade forecasting, demand and decision intelligence directly into their platforms. In this conversation,Ian shares his background, from the Royal Navy and Xerox to building early web businesses, a SaaS platform, and an AI-focused company.He describes how his SaaS business began by solving his own operational problem and then expanded when others in the industry recognized the same need.He shares how, In enterprise AI,  one needs to  distinguish decision-support and forecasting systems from generative AIIan highlights that AI adoption in organizations depends heavily on leadership behaviorThe conversation also covers mindset barriers, the empowerment of non-technical users, and the need to build confidence through hands-on experimentation rather than waiting for formal permission or perfect readiness.On branding and customer acceptance, Ian explains that people may resist AI if it feels like replacement, but respond more positively when it is framed as assistive and human-in-the-loop.He shares career advice for both newcomers and mid-career professionalsIn closing, he shares aspects that help him stay grounded Ian Hogg is Chairman of SolvedBy.ai, an applied AI company helping SaaS vendors embed enterprise-grade forecasting, demand and decision intelligence directly into their platforms.He has spent his career building, scaling and investing in software businesses, with a particular focus on workforce management, SaaS partnerships and AI-driven operational optimisation.Ian is a strong voice on the “SaaS apocalypse” — the idea that AI will expose weak, seat-based SaaS models while creating huge opportunities for vendors that own deep workflow, data and distribution.At SolvedBy.ai, he is focused on helping SaaS companies add the AI layer their customers now expect, without needing to build specialist AI engines from scratch.Ian may be reached at:https://x.com/ianhogg88https://www.linkedin.com/in/ianhoggworktechgroup/https://solvedby.ai/

From Navy to SaaS to AI with Ian Hogg

Stories of what worked and sometimes what did not, in the course of discovering, designing, developing and delivering software based solutions – as shared by practitioners who went through these situations.

Stories of what worked and sometimes what did not, in the course of discovering, designing, developing and delivering software based solutions – as shared by practitioners who went through these situations.

hubhopper

Software People Stories

hubhopper