Tech Talks Daily

• 3246: Why Most Startups Fail and What to Do Differently with Tekyz Inc.

  What does it really take to build a software startup that doesn’t crash before it can fly? In this episode of Tech Talks Daily, I sit down with David Hirschfeld, founder of Tekyz Inc., a software veteran who’s spent over 35 years working across more than 90 startups. From his early days studying physics at UCLA to becoming the top national salesperson at Computer Associates, and later founding and selling his own successful software company, David has seen the full arc of startup life—success, failure, and the lessons in between. In our conversation, David unpacks the patterns he’s observed over decades in the field and the epiphany that led him to create the “Launch 1st Method.” Rather than falling into the trap of building first and validating later, David’s approach challenges founders to prove product-market fit and generate real revenue before a single line of production code is written. He shares how this model not only reduces time, cost, and reliance on outside investment, but also offers a better chance of startup survival by confronting real-world customer demand from day one. We also explore how generative AI is reshaping software development, both in terms of speed and in shifting user expectations. David explains which areas of software development are accelerating most, where AI still struggles, and why even the best tools can't substitute for deep customer insight and thoughtful architecture. He also breaks down the artifacts that distinguish exceptional development teams—from weekly status reports to estimation accuracy—and how these practices shape delivery quality and team alignment. But perhaps most importantly, David offers a grounded look at what makes founders succeed. He emphasizes the value of falling in love with a problem, not a product idea, and staying relentlessly focused on understanding customers and their willingness to pay. Whether you're just starting out or rethinking your strategy, this episode delivers practical insights on how to derisk innovation, build smarter, and stay resilient in a fast-moving AI era. Are you building what people need, or what you hope they want? Let’s explore that further.

  --------  

  33:47
• 3245: How Trello is Tackling Task Overload with AI and Design Thinking

  What happens when one of the world’s most loved productivity tools decides to reinvent itself for the age of AI? At Team 25 in Anaheim, I sat down with Gaurav Kataria, Head of Product for Trello at Atlassian, to unpack the biggest release in Trello’s history and what it means for individuals and teams navigating the chaos of modern work. Gaurav describes the new Trello as “an AI-powered to-do list,” built not to replace project management tools like Jira but to complement them—especially for those personal tasks, scattered action items, and mental notes that get lost in a sea of email, Slack messages, and SaaS app notifications. With half a million users opting into the beta within 48 hours of launch, it's clear that the new direction is resonating. In our conversation, we explore how Atlassian is using AI to enhance, not overwhelm, individual productivity—by capturing inputs from everywhere, organizing them intelligently, and helping users block time visually with integrations into Google and Microsoft calendars. This isn’t about automating your life; it’s about giving you clarity and control without friction. We also talk about how Trello remains deeply personal. From list colors to card covers and mobile widgets, the design philosophy centers on reducing cognitive load and sparking focus. Trello isn’t trying to be a super app. It’s trying to be the app that respects your mental model, works the way your brain works, and empowers you to get meaningful work done on your own terms. If you’re overwhelmed by task sprawl or skeptical of AI’s growing role in daily workflows, this episode offers a grounded look at what thoughtful, user-centered innovation looks like in action. How do you strike the balance between simplicity, automation, and human creativity? Let’s explore that together.

  --------  

  29:09
• 3244: From Mainframes to AI: Paula Paul on Building Software That Lasts

  What happens when four decades of hands-on engineering experience meet today’s fast-moving AI and open-source ecosystem? In this episode of Tech Talks Daily, I sit down with Paula Paul, Founder and Distinguished Engineer at Greyshore, to explore that intersection. Paula began her tech career in the early 1980s writing code for IBM mainframes and has since become a trusted voice in enterprise modernization, cloud adoption, and open-source governance. Today, she advises organizations on how to build with confidence in an era defined by complex software supply chains, generative AI, and evolving SaaS models. We recorded this conversation during a time when many organizations are feeling the pressure to adopt AI and modernize legacy systems, but struggle with where to begin. Paula offers grounded insights on how to break down replatforming into value-driven streams and why a “big bang” transformation approach is often more risk than reward. She also talks about the critical role of open source in business today—not just from a tooling standpoint, but in terms of responsibility, transparency, and community. Paula’s perspective is refreshingly practical. She believes AI is a natural evolution of decades of computing and storage expansion but urges companies to start with targeted experiments and thoughtful team collaboration. She also shares her experiences as a woman in tech since the 1980s, reflecting on what’s changed and what hasn’t and how leadership dynamics continue to shape opportunities for women in the industry. Beyond the code, Paula draws a fascinating parallel between music and technology. As a board member of the Brookline Music School and an oboe and English horn student, she explores how musical thinking can enhance software development's rhythm, structure, and leadership. If you’re navigating modernization, curious about AI’s role in development, or wondering how to make open source work for your organization—technically and strategically—this episode has something for you. How are you balancing technical ambition with long-term value? Let’s continue the conversation.

  --------  

  22:08
• 3243: How Atlassian CTO Turned Developer Joy Into a Performance Metric

  What does it really mean to build software with joy? At the Team 25 event in Anaheim, I had the opportunity to sit down with Rajeev Rajan, CTO of Atlassian, to explore how one of the world’s most influential engineering organizations is redefining developer experience from the ground up. Rajeev shares how developer joy became a guiding principle for Atlassian, not as a feel-good initiative but as a core driver of performance and innovation. Rather than focusing solely on velocity or throughput, Atlassian measured how productive developers felt in their codebases. That metric has now improved from 49 percent to 75 percent, thanks to a deliberate strategy built on three pillars: better tools, stronger engineering culture, and empowered teams. We also dive into how this cultural shift helped accelerate the delivery of Rovo, Atlassian’s most ambitious AI product to date. Built-in record time, Rovo didn’t emerge from a top-down push but from an environment where engineers were supported to move fast without cutting corners. That includes training internal teams through AI School, rolling out dev agents, and prioritizing transparency over automation for automation’s sake. Rajeev also reflects on how India has become a global engine for AI and software development and why Atlassian invests in its global teams with the same level of trust and ownership as any other location. From ship-it hackathons to hands-on leadership and a grounded view of where AI helps and where it still falls short, this conversation highlights what it takes to build modern engineering teams that are both productive and fulfilled. So, if you’re building AI strategies, leading engineering teams, or rethinking how to scale innovation responsibly, what would change if developer happiness were your benchmark?

  --------  

  21:27
• 3242: L.E.K. Consulting on Using AI to Balance Speed, Risk, and Growth

  What if most product launches fail not because of bad ideas—but because of broken processes? In today’s episode of Tech Talks Daily, I’m joined by Stuart Jackson, Vice Chair of L.E.K. Consulting and co-author of the forthcoming book Predictable Winners (Stanford University Press, 2025). Stuart brings nearly four decades of experience in strategic growth and innovation, and his insights offer a much-needed reframe for businesses navigating the high-stakes world of new product and service development. We sat down to explore a topic many leaders shy away from: why 70–90% of product launches still miss the mark. Stuart breaks down the structural weaknesses that often derail innovation and explains why relying on gut instinct is no longer enough. Instead, we discuss how a rigorous, data-backed approach—augmented by AI—can dramatically reduce the risk profile of innovation while improving speed, accuracy, and return on investment. Stuart shares how leading organizations are integrating AI into every phase of their innovation pipeline—from idea screening and predictive analytics to launch planning and ongoing iteration. He outlines the rise of long-horizon thinking and how AI is enabling companies to identify emerging demand signals well before the competition. What I found particularly refreshing was Stuart’s take on what top innovators do differently. It’s not just about having better ideas—it’s about building the right systems. That means empowering cross-functional teams, systematically disaggregating risk, and knowing when to pivot versus when to persevere. This conversation isn’t about theory. It’s a pragmatic look at how to move from product guesswork to predictable success—whether you're building in-house or buying through M&A. For founders, product leaders, and anyone trying to modernize their innovation model, this episode offers grounded advice and a clear framework that you can start applying today. How are you thinking about AI as a tool for risk reduction in innovation? Are your product strategies built for speed or sustainability—or both? Let me know what you think.

  --------  

  23:14

Weitere Technologie Podcasts

Trending Technologie Podcasts

Über Tech Talks Daily