Software People Stories

In this episode, Chitra reconnects with Srini, a long-time technologist and futurist, for a wide-ranging conversation about what AI means right now and where it could take us. They cover multi-tool AI workflows, generational shifts in adopting technology, information fatigue, and the diverging futures AI could create.Key points in the episode00:00 Welcome, and why this revolution is different: it competes with the human brain02:32 Who's really at risk? Srini argues it's people with jobs today, not only the already underprivileged05:10 What AI has changed most for Srini: planning with unstructured data, using three tools to curate, critique and refine09:03 Aha moments: the AI that cited his own findings back as "anecdotal data," and the one that zipped past a checkpoint11:25 What his generation contributed: helping people adapt, with lessons from railway and bank computerization14:42 Learning from his son, nephews using AI on legacy code, and AI-set question papers19:36 Text vs images vs video, and why he'd like everything back in a spreadsheet25:46 Rapid fire: what AI has made more human, and what it has made less human27:24 Five years out: a K-shaped world, two possible paths, and why AI plus robotics is his biggest concern30:21 Why people are asking for face-to-face conversations again

“AI gives you wings,” “Wrong things in, rogue things out,” and “Each one, teach one.”From “What is this?” to an indispensable companionIn this episode of Software People Stories – AI and Me, I speak with Ramesh Rajagopal about how AI has moved from something unfamiliar and experimental to an everyday companion that helps him learn, explore, solve problems and make decisions.Ramesh describes his relationship with AI through some wonderful analogies—from Jeeves and Man Friday to Hanuman—capturing how quickly AI has become his go-to source for help.From information search to personal problem solvingOne of Ramesh’s most interesting observations is how dramatically AI has changed access to information. While exploring the life and legacy of Malcolm X, he was able to ask a series of questions and quickly understand what happened to Malcolm X’s family, his organisation and the events surrounding his assassination—something that would previously have required hours of searching.But it is his very real-world examples that bring the conversation alive.When a huge tree fell on the compound of his property in Bengaluru during heavy rains, Ramesh used AI to figure out whom to contact, which numbers to call and what options were available. After several attempts, the right contact was eventually found and the tree was cleared.And when his Lenovo laptop froze, he simply asked AI what to do, followed the instructions and fixed it himself.These moments led to perhaps the most powerful insight of the conversation: AI gives you wings.AI as a thinking partnerRamesh also uses AI to explore alternatives and support decision-making. Whether it is designing a solution for people travelling from India to the US, evaluating different approaches, or looking at investment decisions, he uses AI to generate options, compare pros and cons and structure his thinking.But he draws an important boundary:The human remains in the loop.AI can provide alternatives and analysis, but decisions—particularly decisions involving people—still need human judgment and accountability.Everyone has a role in shaping AIA particularly important part of our conversation is Ramesh’s view that not everyone needs to build an AI model to contribute to AI.The AI architecture may be developed by a relatively small group of specialists, but the knowledge that AI learns from comes from everyone.Blogs, experiences, expertise, documentation and shared knowledge all contribute to the ecosystem.His warning is equally important:“Wrong things in, rogue things out.”As AI multiplies and redistributes information at enormous speed, the quality and accuracy of what we contribute becomes increasingly important.Turning institutional knowledge into AIRamesh shares a fascinating example from PM Power, where years of accumulated expertise from experienced consultants has been captured through blogs and knowledge contributions.That knowledge has now been brought together into an internal AI system called Power Guru, where people can ask questions about management, careers, leadership and workplace situations and receive advice based on the collective experience of the organisation.It is a beautiful example of how institutional memory can become an AI-powered knowledge companion.The AI future: optimism with cautionWhen asked what he hopes AI can achieve over the next five years, Ramesh imagines a world where AI helps us produce food more efficiently, conserve water, generate electricity efficiently and ultimately create a happier, more comfortable world.But he also has a concern: AI used for warfare and destruction.For him, regulation, awareness and human responsibility will be essential to ensuring that the technology serves humanity rather than the other way around.Rapid FireOne AI tool you can't live without?LLMs.One thing you'll never delegate to AI?“My consciousness.”One word to describe your relationship with AI?Love.Your AI aha moment?Every day. Ramesh compares watching AI evolve to watching a child grow—there is always something new that makes you say, “Wow!”One final messageRamesh leaves us with a simple but powerful thought:You cannot ignore AI. Learn it. Use it. Contribute to it. And help others learn it.He sees a new divide emerging between people who understand AI and those who don't. His answer is beautifully simple:Each one, teach one.Because the future of AI isn't just about the people building the models. It is also about all of us who use them, contribute knowledge to them, question them and decide how they should be used.Ramesh can be reached at https://www.linkedin.com/in/ramesh-br-32a5111/?isSelfProfile=false 

From democratizing intelligence to redefining how we lead, work and remain humanIn this episode of Software People Stories, Gayatri Kalyanaraman reconnects with Zafar, who brings nearly four and a half decades of experience across technology and multiple waves of transformation—from mainframes and personal computing to the internet, cloud and digital transformation.His observation about AI is simple but profound: previous technology shifts gave humans more powerful tools; AI is beginning to democratize intelligence. And with AI agents, even execution is being democratized.Beyond AI adoption: where is the business value?Zafar is enthusiastic about AI's potential, but cautious about the hype.Giving thousands of employees access to AI tools is not, by itself, transformation. The real question is: what has changed in the way the organization creates value?For him, meaningful enterprise value will come from redesigning workflows, integrating data, changing decision rights and building domain-specific AI systems—not simply adding AI assistants to existing processes.The leader of the futureAI also changes what leadership means.When information, analysis and execution are increasingly available on demand, leaders cannot rely simply on having the answers. Their role shifts towards asking better questions, creating clarity, setting context, exercising judgment, aligning people and taking accountability.The future may be less about managing people or technology and more about orchestrating human and AI capabilities around outcomes.What happens to our human capabilities?Perhaps the most thought-provoking part of the conversation is Zafar's concern about cognitive over-dependence.We already outsource calculation to calculators and recall to search engines. AI takes this much further by allowing us to outsource drafting, analysis and even parts of reasoning.His question is not whether we should use AI—we clearly should—but:What mental capabilities do we deliberately continue to exercise ourselves?He argues that productive struggle—the process of wrestling with a problem, making mistakes and changing our minds—is part of how we develop critical thinking and intellectual independence.AI and the human relationshipThe conversation then moves from cognition to something even more fundamental: human relationships.AI is infinitely patient, always available and highly personalized. But what happens if frictionless AI relationships begin replacing the messy, challenging and sometimes uncomfortable relationships we have with real people?That raises a bigger question about human agency: are we eventually going to outsource not only memory and reasoning, but also judgment, empathy and emotional support?The responsibility that comes with intelligenceZafar also reflects on the societal implications of increasingly autonomous AI.AI has extraordinary dual-use potential—it can accelerate scientific discovery and healthcare, while also being used for surveillance, manipulation, cybercrime and misinformation.As AI becomes increasingly agentic, his message is clear: governance and human oversight need to advance alongside capability.He argues for a risk-based approach to AI governance: a tool rewriting an email should not face the same level of scrutiny as an AI making decisions about healthcare, employment, credit or public security.Ultimately, this is a conversation about much more than AI technology.It is about what happens to organizations when intelligence becomes abundant, what happens to leaders when answers become cheap, and what happens to humans when machines become increasingly capable.And perhaps the most important question we leave with is:As AI becomes better at thinking for us, what must we continue learning to think for ourselves?Zafar can be reached at https://www.linkedin.com/in/zafar-ahmad-4704b76/ 

My guest today is Paramu Kurumathur: IT Leader, Author. Here is the snippets of interesting stories around how AI has changed his life and how he’s impacting AI - From building AI in 1980 to using AI to code, write, research and imagine the futureWhat makes Paramu's story unusual is that his AI journey actually began in 1980, when his M.Tech project explored automatic program generation using structured data and if-then rules. Four decades later, he finds himself using generative AI in almost every facet of his life.AI as a companionFrom preparing a draft of his family will to asking Gemini to explain a television show, AI has become a surprisingly useful personal companion for Paramu.At work, he uses AI coding tools such as Cursor to turn ideas into working software—even when he doesn't know the programming language particularly well. One of his recent projects used AI, Python and a vector database to help people discover government schemes they may be eligible for.For Paramu, this ability to take an idea and quickly turn it into something tangible is one of the biggest "aha moments" of AI.AI and the authorAI has also found its way into Paramu's writing. He uses it for Sanskrit transliteration, translations, research, introductions and making his writing more conversational.But he is equally conscious of AI's limitations. Hallucinations become particularly problematic when dealing with subjects where the available data is limited, such as astronomy and ancient Indian texts. This leads to an important observation about the need for good foundational data.What should remain human?Perhaps the most interesting question in the conversation is what Paramu would never delegate to AI.His answer: the core idea of his books, personal relationships and the human connections involved in coaching and consulting.AI can help us create, research and accelerate—but there are parts of our lives where the relationship itself is the work.AI for social goodWhen asked what is underrated about AI, Paramu points to its potential for social and collective benefit.From identifying potholes and holding contractors accountable to helping people discover government benefits, he believes some of the most meaningful applications of AI could emerge outside traditional productivity use cases.The conversation ends with a glimpse into the future—from AI agents that can behave in surprisingly autonomous ways to Paramu's wish that technology could help people communicate when they cannot express themselves easily, or even objectively understand pain.And, of course, there is a rapid-fire round before we finish—with one final thought: perhaps five years from now, Paramu might return to the podcast… in AI form!A conversation about AI, human judgment, social good and what we choose to keep uniquely human.And finally… a rapid fireThe conversation ends with a rapid-fire round.Favorite AI use case?A tool.What is overrated about AI?Nothing.What is underrated?AI for social and collective benefit.What would you never delegate?The core message of his work—and the human relationships that matter.And perhaps the perfect closing thought: when Gayatri imagines that five years from now Paramu might be sitting next to her in AI form, Paramu signs off by saying he enjoyed the "stimulating" discussion—while joking that he always confuses stimulating with simulating.A fitting end to a conversation about humans, machines and everything in between.Paramu can be reached at https://www.linkedin.com/in/paramu-kurumathur-01489a6/and paramukurumathur.com 

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