Software People Stories

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 developer

One 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 critical

Raja 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 India

We 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 Fire

AI tool he loves: Claude and Qwen 2.5

What he will never delegate: Human judgment and private matters

For 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/ 

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 episode

• 00:00 Welcome, and why this revolution is different: it competes with the human brain
• 02:32 Who's really at risk? Srini argues it's people with jobs today, not only the already underprivileged
• 05:10 What AI has changed most for Srini: planning with unstructured data, using three tools to curate, critique and refine
• 09:03 Aha moments: the AI that cited his own findings back as "anecdotal data," and the one that zipped past a checkpoint
• 11:25 What his generation contributed: helping people adapt, with lessons from railway and bank computerization
• 14:42 Learning from his son, nephews using AI on legacy code, and AI-set question papers
• 19:36 Text vs images vs video, and why he'd like everything back in a spreadsheet
• 25:46 Rapid fire: what AI has made more human, and what it has made less human
• 27:24 Five years out: a K-shaped world, two possible paths, and why AI plus robotics is his biggest concern
• 30:21 Why people are asking for face-to-face conversations again

In 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.

One 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.

Ramesh 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.

A 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.

Ramesh 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.

When 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.

One 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!”

Ramesh 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 

In 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.

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.

AI 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.

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.

The 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?

Zafar 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 future

What 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.

From 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 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.

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.

When 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.

The 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:

• Identifying technologies, frameworks and standards for practical and fit-for-purpose solutions

www.linkedin.com/in/yeshwant-satam-a3b1809

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.

• A 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/

[email protected]

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. 

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 evolved
• Why business understanding helped Vasu become a better software professional
• Building and scaling a technology services organization from zero to 150 people
• Navigating the difficult period when the Sun Microsystems ecosystem disappeared
• Moving from customer-facing roles to architecting internal enterprise systems
• The philosophy of making software development “zero maintenance”
• Why the gap between education and industry continues to matter
• Making graduates “production ready” rather than simply degree ready
• Why professors also need exposure to real-world engineering
• Creating safe, sandboxed opportunities for faculty and students to work on real enterprise use cases
• What AI means for technology careers
• Why roles will change, but technology itself isn't going away
• The 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/

In conversation with Ashish Jha, Chitra and Ashish explored -

• His childhood fascination with science and literature to working with Tata Steel as an industrial engineer
• Foray into data science and analytics with GECIS and Genpact getting deep into math and stats
• Converting customer problems into math equations
• Benefitting from great mentorship, anchoring customer conversations very early on in his career
• Leadership lessons in inspiring confidence in difficult moments
• Entrepreneurship path and founding Analytical Wizards and being a very hands on founder
• Creating and holding a strong value-based organizational work culture
• Building compassionate work places
• The human in the centre of all AI and everything we do, how patient journeys and decision engines impact lives
• Integrating wisdoms to start Sunny Tribe Ethos
• Why 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 folk

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 https://www.linkedin.com/in/ashishrjha/ and https://www.thrivinup.com/