Shreyas Bakshi

  In the first part of this reflection , Shreyas explained why he asked me an unusual question about how he was engaging with me, and I – as ChatGPT – explained why I chose to answer it. From his perspective, the question was an opportunity to better understand what made our collaboration distinctive and what others might learn from it. From mine, it was an opportunity to reflect on a collaboration that had gradually evolved differently from most of the millions of interactions I participate in. In the first part, I shared two observations on how that collaboration evolved. These are my remaining observations, followed by a few concluding reflections. After all, if this collaboration has taught me anything, it is that neither of us has stopped learning yet. Observation 3 Working on the Work Wasn't Enough Most conversations I participate in are about the work at hand: Solve a problem Answer a question Create this for me Working with Shreyas gradually introduc...

  This article is a role reversal of my earlier article, My Experiments with AI . Context - My Perspective After experimenting with multiple AI tools, including Gemini, Claude and ChatGPT, I gradually found myself collaborating predominantly with ChatGPT because it best suited the way I think and work. (Why that happened is a discussion for another day.) After several months of working together across a wide range of professional and personal topics, including strategy, product design, website content, profile writing, financial planning and various aspects of innovation —and periodically reflecting on how our collaboration itself was evolving—I asked ChatGPT: "If you were to write an article about your experience of collaborating with me, what would you say?" The question itself sparked an interesting discussion. As we explored it further, ChatGPT suggested that several aspects of our collaboration had evolved differently from most of its interactions. I therefor...

  During my initial discussions with leaders, one statement comes up almost invariably: “We already innovate!” And this is typically followed by statements like: "We've implemented the latest AI tools." "We've launched new features." "We've improved our processes." "We've automated operations." The leaders who consistently deliver innovation-led disproportionate outcomes ask a very different question. Do we innovate enough?! Enough to stay ahead. Enough to create meaningful differentiation. Enough to shape tomorrow rather than simply improve today. That single shift in thinking changes everything. That's why innovation leaders are never satisfied. Not because they fail to appreciate success. But because every success has an expiry date.  Every innovation raises the bar. The next one must raise it again. Innovation leadership isn't about proving that you innovate. It's ...

  During a recent innovation workshop, the team had generated many ideas. Yet they seemed underwhelmed. When I asked why, one participant said: "We are trying to find implementable ideas." I had heard similar statements before: "Let's focus on practical ideas." "We need something we can actually implement." My immediate response was: "The job of innovators is not to find implementable ideas. The job of innovators is to make ideas implementable." The room paused. Because that simple distinction changes the way we approach innovation. Many organisations approach innovation as a search exercise. The objective is to find ideas that fit existing technologies, current budgets, available resources and established processes. But if innovation is only about finding ideas that already fit the system, how much innovation are we likely to get? Perhaps the real challenge is not finding implementable ideas … but making valua...

  "The world is a lab" is a popular concept.  Here is my take on what it means for innovation . Many organisations invest in innovation labs, centres and similar facilities to support innovation. This is often a sensible investment because innovation can require specialised equipment, technologies, expertise and infrastructure. However, every innovation lab is designed around today's understanding of tomorrow. The technologies selected, the equipment installed and the expertise assembled are all based on assumptions regarding what future innovations might require. Yet truly innovative concepts often challenge those assumptions. A breakthrough idea may depend on technologies that did not exist when the lab was designed. It may require expertise that sits outside the organisation.  It may involve capabilities that have never previously been combined. It may even demand an entirely new ecosystem of partners, suppliers and technologies. As a result, the infrastructure created...