In this episode, we explore a quiet but powerful shift in how product teams handle documentation. Gone are the days when specs, PRDs, and decision logs live solely in Confluence or Google Docs. As AI agents start generating and consuming documentation, and as systems become more complex, the natural home for product knowledge is moving closer to the code itself.

We discuss why writing docs in GitHub repos, "where they evolve with the system and are immediately accessible to both humans and AI" is becoming the new standard. From AI-assisted drafts to frictionless updates with a single prompt, this episode unpacks how product documentation is evolving from static artifacts into living parts of the build system.

Tune in to understand why documentation is no longer just a support function, but a critical lever for scaling, clarity, and collaboration in an AI-first product workflow.

This podcast is generated by Google NotebookLM and is a podcast version of articles written on ⁠⁠⁠vinaysachdeva.com⁠⁠⁠.

For more details, visit ⁠⁠⁠vinaysachdeva.com⁠⁠⁠ or reach out to me on LinkedIn: ⁠⁠⁠linkedin.com/in/vinaysachdeva⁠⁠⁠.

In this episode, we explore the journey from vibe coding to building real, production-grade infrastructure with AI agents. While AI makes it possible to go from idea to working code faster than ever, speed can be deceptive. Prototypes are easy. Demos are forgiving. Infrastructure is not.

We discuss what happens when AI-assisted development moves beyond toy apps and mockups into systems that must run continuously, scale over time, and survive failure. From Kubernetes clusters and private clouds to technical debt, system design, and judgment, this episode unpacks where AI agents shine, where they fall short, and why engineering fundamentals still matter.

This is not a story about AI replacing engineers. It is about how builders, product leaders, and system thinkers can use AI as leverage, without losing sight of constraints, tradeoffs, and reality.

Tune in to understand why getting from zero to one is easy, why one to scale is hard, and what it really takes to build durable systems in the AI era.

This podcast is generated by Google NotebookLM and is a podcast version of articles written on ⁠⁠vinaysachdeva.com⁠⁠.

For more details, visit ⁠⁠vinaysachdeva.com⁠⁠ or reach out to me on LinkedIn: ⁠⁠linkedin.com/in/vinaysachdeva⁠⁠.

In this episode, we dive into why most teams fail, not because their solutions are weak, but because they never truly understood the problem in the first place. While everyone agrees that defining the problem is the first step to solving it, in practice, assumptions often replace clarity, and speed often replaces alignment. We discuss why rushing to solutions without context leads to missteps, and how simple practices — like restating the problem, asking the right questions, and challenging assumptions — can completely change outcomes.

Tune in to uncover why problem clarity is the real competitive edge in building lasting solutions.

This podcast is generated by Google NotebookLM and is a podcast version of articles written on ⁠vinaysachdeva.com⁠.

For more details, visit ⁠vinaysachdeva.com⁠ or reach out to me on LinkedIn: ⁠linkedin.com/in/vinaysachdeva⁠.

In this episode, we explore why the true competitive edge in enterprise AI isn’t just about intelligence—it’s about context. While large language models and AI systems are becoming more powerful, their effectiveness in business settings depends on how well they understand the specific workflows, data, and nuances of an organization. We discuss why companies that master contextual AI will outpace those relying solely on raw intelligence. Tune in to uncover how enterprises can harness AI effectively and stay ahead in this evolving landscape.

This podcast is generated by Google NotebookLM and is a podcast version of articles written on vinaysachdeva.com.

For more details, visit vinaysachdeva.com or reach out to me on LinkedIn: linkedin.com/in/vinaysachdeva.

In this episode, we explore the importance of the closed-loop framework in product development and workflow design. Many product features and processes fail not because of bad ideas, but because they leave the loop incomplete—missing critical feedback, automation, or iteration steps. We discuss why closing the loop is essential for building effective, scalable, and user-centric products. Tune in to understand how to identify gaps in workflows and ensure your product decisions drive real impact.

This podcast is generated by Google NotebookLM and is a podcast version of articles written on vinaysachdeva.com.

For more details, visit vinaysachdeva.com or reach out to me on LinkedIn: linkedin.com/in/vinaysachdeva.

In this episode, we break down the fundamentals of passive investing and help you understand how to choose the right index for your portfolio. From the S&P 500 to niche sector indices, we explore the options available and provide guidance on how to select the best one based on your financial goals, risk tolerance, and investment strategy. Whether you're new to investing or looking to refine your approach, this episode offers valuable insights on how to start passive investing the smart way.

This podcast is generated by Google NotebookLM and is an audio version of articles written on ⁠⁠⁠⁠⁠⁠⁠vinaysachdeva.com⁠⁠⁠⁠⁠⁠⁠.

For more details, visit ⁠⁠⁠⁠⁠⁠⁠vinaysachdeva.com⁠⁠⁠⁠⁠⁠⁠ or reach out to me on LinkedIn: ⁠⁠⁠⁠⁠⁠⁠linkedin.com/in/vinaysachdeva⁠⁠⁠⁠⁠⁠⁠.

In this episode, we delve into how large language models (LLMs) can revolutionize the process of writing Product Requirement Documents (PRDs). We explore how these AI tools can assist product managers in creating clear, concise, and effective PRDs that align with both business goals and technical requirements. Tune in for insights on using LLMs to streamline documentation processes and improve collaboration across product teams.

This podcast is generated by Google NotebookLM and is an audio version of articles written on ⁠⁠⁠⁠⁠⁠vinaysachdeva.com⁠⁠⁠⁠⁠⁠.

For more details, visit ⁠⁠⁠⁠⁠⁠vinaysachdeva.com⁠⁠⁠⁠⁠⁠ or reach out to me on LinkedIn: ⁠⁠⁠⁠⁠⁠linkedin.com/in/vinaysachdeva⁠⁠⁠⁠⁠⁠.

In this episode, we explore the transformative potential of asking the right questions when interacting with large language models (LLMs). How does the quality of the questions we ask influence the output we get, and how can we use this to push LLMs to a higher level of performance? We discuss the power of effective communication with AI, offering insights on how asking the right questions can lead to more accurate, insightful, and impactful responses.

This podcast is generated by Google NotebookLM and is an audio version of articles written on ⁠⁠⁠⁠⁠⁠vinaysachdeva.com⁠⁠⁠⁠⁠⁠.

For more details, visit ⁠⁠⁠⁠⁠⁠vinaysachdeva.com⁠⁠⁠⁠⁠⁠ or reach out to me on LinkedIn: ⁠⁠⁠⁠⁠⁠linkedin.com/in/vinaysachdeva⁠⁠⁠⁠⁠⁠.