Software People Stories copertina

Software People Stories

Software People Stories

Di: PM Power Consulting
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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.

Copyright 2020 PM Power Consulting Economia Ricerca del lavoro Successo personale
Episodi
  • An Idea Today, an Outcome Tomorrow with Mathangi Sri Ramachandran

    An Idea Today, an Outcome Tomorrow with Mathangi Sri Ramachandran
    Jul 17 2026
    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 ...
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    37 min
  • Enabling Better Decisions Through Data with Sree Krishna Kumaraswamy

    Enabling Better Decisions Through Data with Sree Krishna Kumaraswamy
    Jul 13 2026


    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

    • traces his journey from growing up in Chennai with an expected engineering path to discovering mathematics and statistics through the Indian Statistical Institute
    • Talks 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 thoughtfully
    • Stresses 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 roles
    • 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.


    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/
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    49 min
  • AI, Integration, and Innovation with Elangovan Shanmugam

    AI, Integration, and Innovation with Elangovan Shanmugam
    Jul 3 2026

    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 engineering
    • Shares 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

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    51 min
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