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by PM Power Consulting
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.
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- 1 weeks ago26 min
From Writing Code to Orchestrating Intelligence with Raja Subramanian
In this episode of Software People Stories – AI and Me, I catch up with Raja Subramanian to explore how AI is changing his world as a developer, consultant and software practitioner.AI and the developerOne of Raja’s biggest AI use cases is legacy code refactoring. What was once risky and time-consuming can now be done much faster, allowing him to move legacy systems closer to the clean, maintainable code that developers have always aspired to build.But for Raja, the bigger change is how AI separates thinking from coding.Instead of spending all his energy on the mechanical act of writing functions and passing parameters, he can focus on architecture, design and domain thinking while AI does much of the implementation. He describes himself increasingly as the thinker and navigator, with multiple AI agents helping execute the work.Human judgment remains criticalRaja doesn't believe AI should make decisions blindly.Whether it is code, business decisions or personal matters, he sees AI as a consulting partner that provides options, while the human remains responsible for judgment.Even when AI writes code, Raja reviews it, challenges its design and guides it towards better abstractions.Building for IndiaWe also talk about Raja’s vision for the future of AI.He expects smaller, local LLMs to become increasingly accessible and sees an opportunity for India to build affordable technology for its own people.His philosophy is particularly compelling:We don't necessarily have to build everything from scratch. We can use what exists and make it better.Projects such as his MyBeacon platform, which uses AI to help students break down complex physics problems, are examples of that approach.Rapid FireAI tool he loves: Claude and Qwen 2.5What he will never delegate: Human judgment and private mattersFor Raja, the opportunity with AI isn't simply about writing more code. It is about thinking better, building better and using technology to make life better.Raja can be reached at https://www.linkedin.com/in/raja-subramanian-kamakshi-iyer-87aa7a54/
- 2 weeks ago30 min
From Creator to Reviewer, Human & good Humans with S. Srinivasan
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
- 3 weeks ago28 min
You cannot ignore AI. Contribute to it. And help others learn AI with Ramesh
“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<span style="
- 4 weeks ago33 min
AI, Human Capability and the Future of Leadership with Zafar
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 lev
- Oct 4, 202626 min
From Punch Cards to AI Companions
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?</s
- Sep 25, 202653 min
From Soldering to Software with Yeshwant Satam
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
- Sep 18, 202653 min
Learn, Adapt, Work Hard with Arun Subash Manickam
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
- Sep 11, 20261h 0m
From Stethoscope to Software with Dr. Kishore Reddy
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 en
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