Software Without Borders

About Software Without Borders

Software Without Borders is the essential listen for technology leaders and business owners in the software sector who crave insights from the industry’s top minds. Picture a relaxed, coffee-driven chat where tech veterans discuss cutting-edge projects and business strategies shaping their industry. Tune in to join conversations that traverse the intersections of technology and business, helping you stay ahead in a rapidly evolving industry.

Publisher

Andy Hilliard - Accelerance

Category

business · technology

Language

en

Explicit

No

First episode

26 Jun 2024

Latest episode

5 May 2026

Latest episodes

53 episodes in the feed.

1. 

   5 May 2026

   Inside Real-World AI Systems (VIDEO)

   In this episode of Software Without Borders, hosts Thomas Hilliard and Olivier Pollard sit down with Ben Coffman, SVP of Engineering and Product, to break down how AI is being implemented inside modern software organizations. From computer vision and 3D modeling workflows to large-scale data infrastructure, Ben shares real-world insights on scaling engineering teams, improving system performance, and building AI-driven platforms. This conversation dives into software development, engineering leadership, artificial intelligence, and the strategies teams are using to turn emerging technology into real business results. Guest Introduction:Ben Coffman is the SVP of Engineering and Product at STACK Construction Technologies, where he leads high-performing teams at the intersection of software development, product strategy, and business execution. With a background spanning engineering leadership, AI-driven platforms, and large-scale data systems, Ben brings a practical, real-world perspective on how modern software organizations are built and scaled. Known for combining technical depth with strategic thinking, he focuses on improving workflows, accelerating performance, and helping teams turn complex systems into measurable business outcomes. Key Takeaways:• How AI is actually being deployed inside real software systems, not just discussed in theory • What it takes to scale engineering teams from early-stage builds to complex, high-performance platforms • How computer vision, 3D modeling, and data infrastructure are shaping the future of software development • The mindset leaders need to successfully implement AI and adapt to constant technological change • Why improving system speed and performance is critical when building AI-driven platforms • How modern engineering teams are turning emerging technology into measurable business results • What separates teams that successfully build AI systems from those that get stuck in experimentation • How early curiosity in technology can shape a career in engineering leadership and innovation Chapter Markers:00:00 – Introduction to the Show00:45 – Ben’s Background and Leadership Experience01:10 – How Did Your Career in Technology Begin?03:00 – What Shaped Your Professional Journey?05:00 – What Drew You to Software and Engineering?07:00 – Early Inspiration: Thinking About the Future of Technology09:00 – Transitioning from Interest to Real-World Systems11:30 – What Does It Take to Build Real Software Systems?14:00 – How Is AI Actually Implemented in Production?17:00 – Where AI Fits in Modern Software Architecture20:00 – Challenges of Integrating AI into Existing Systems23:00 – How Do You Scale Engineering Teams Effectively?26:00 – Improving Speed, Performance, and Output29:00 – Leadership Lessons from Scaling Complex Systems32:00 – How Do You Drive Real Business Results with Technology?35:00 – The Mindset Required to Lead Through Change38:00 – What Teams Get Wrong About AI and Innovation41:00 – Looking Ahead: The Future of AI and Software43:30 – Final Thoughts and Takeaways Keywords:AI, artificial intelligence, software development, software engineering, engineering leadership, AI in production, machine learning, data infrastructure, scalable systems, system architecture, computer vision, 3D modeling, tech leadership, engineering teams, building AI systems

2. 

   5 May 2026

   Inside Real-World AI Systems (AUDIO)

   In this episode of Software Without Borders, hosts Thomas Hilliard and Olivier Pollard sit down with Ben Coffman, SVP of Engineering and Product, to break down how AI is being implemented inside modern software organizations. From computer vision and 3D modeling workflows to large-scale data infrastructure, Ben shares real-world insights on scaling engineering teams, improving system performance, and building AI-driven platforms. This conversation dives into software development, engineering leadership, artificial intelligence, and the strategies teams are using to turn emerging technology into real business results. Guest Introduction:Ben Coffman is the SVP of Engineering and Product at STACK Construction Technologies, where he leads high-performing teams at the intersection of software development, product strategy, and business execution. With a background spanning engineering leadership, AI-driven platforms, and large-scale data systems, Ben brings a practical, real-world perspective on how modern software organizations are built and scaled. Known for combining technical depth with strategic thinking, he focuses on improving workflows, accelerating performance, and helping teams turn complex systems into measurable business outcomes. Key Takeaways:• How AI is actually being deployed inside real software systems, not just discussed in theory • What it takes to scale engineering teams from early-stage builds to complex, high-performance platforms • How computer vision, 3D modeling, and data infrastructure are shaping the future of software development • The mindset leaders need to successfully implement AI and adapt to constant technological change • Why improving system speed and performance is critical when building AI-driven platforms • How modern engineering teams are turning emerging technology into measurable business results • What separates teams that successfully build AI systems from those that get stuck in experimentation • How early curiosity in technology can shape a career in engineering leadership and innovation Chapter Markers:00:00 – Introduction to the Show00:45 – Ben’s Background and Leadership Experience01:10 – How Did Your Career in Technology Begin?03:00 – What Shaped Your Professional Journey?05:00 – What Drew You to Software and Engineering?07:00 – Early Inspiration: Thinking About the Future of Technology09:00 – Transitioning from Interest to Real-World Systems11:30 – What Does It Take to Build Real Software Systems?14:00 – How Is AI Actually Implemented in Production?17:00 – Where AI Fits in Modern Software Architecture20:00 – Challenges of Integrating AI into Existing Systems23:00 – How Do You Scale Engineering Teams Effectively?26:00 – Improving Speed, Performance, and Output29:00 – Leadership Lessons from Scaling Complex Systems32:00 – How Do You Drive Real Business Results with Technology?35:00 – The Mindset Required to Lead Through Change38:00 – What Teams Get Wrong About AI and Innovation41:00 – Looking Ahead: The Future of AI and Software43:30 – Final Thoughts and Takeaways Keywords:AI, artificial intelligence, software development, software engineering, engineering leadership, AI in production, machine learning, data infrastructure, scalable systems, system architecture, computer vision, 3D modeling, tech leadership, engineering teams, building AI systems

3. 

   5 May 2026

   Everything Broke at Once: The Shift to AI-Native Organizations (VIDEO)

   AI is accelerating software development at a pace most organizations aren’t ready for. In this episode of Software Without Borders, Duncan Grazier, Chief AI Officer at Build, breaks down what happens when code creation becomes nearly free—and why that doesn’t translate to better outcomes. From broken pipelines to misaligned metrics, this conversation explores how AI is forcing leaders to rethink how teams operate, how performance is measured, and what actually drives value. Duncan shares why judgment and “taste” are becoming the most important skills in engineering, where AI is delivering real impact today, and how companies can avoid the trap of moving faster without moving smarter. Guest Introduction: Today’s guest is Duncan Grazier, Chief AI Officer at BuildOps, where he’s helping lead the shift from traditional software companies to AI-native organizations. Duncan has spent his career scaling engineering teams and building high-performance systems, including taking an organization from roughly 30 engineers to over 300 through hypergrowth and IPO. Beyond his leadership roles, Duncan is known for his deep thinking around engineering, AI, and how companies actually operate under rapid change. He’s focused on how AI is reshaping not just how software gets built, but how teams are structured, how performance is measured, and how businesses create real leverage in this next era of technology. Key Takeaways: AI has made code creation fast and cheap, but it has exposed bottlenecks in validation, alignment, and decision-making across teams. More output does not guarantee better outcomes; organizations must shift from measuring activity to measuring real business impact. The gap between junior and senior engineers is shrinking, which puts greater emphasis on judgment, context, and decision quality. The biggest breakdowns are not technical—they come from misaligned metrics and lack of coordination between leadership, product, and engineering. Companies that win with AI will focus on integrating it into systems that drive core business results, not just using it to increase speed or volume. Chapter Markers: 00:00 – Intro & Guest Introduction 02:30 – Why AI Is Breaking Traditional Software Models 05:00 – The First Bottleneck: From Code to Production 08:30 – Why More Output Doesn’t Mean Better Results 10:00 – Rethinking Teams, Roles, and Headcount 11:30 – Where AI Is Actually Delivering Value 13:30 – The Gap Between Prototype and Production 15:00 – Where Companies Are Getting AI Wrong 18:30 – The Real Challenge: Organizational Alignment 21:30 – Final Thoughts & Key Takeaways Keywords: AI, artificial intelligence, software development, engineering leadership, AI tools, machine learning, software engineering, product development, tech leadership, startups, scaling teams, automation, developer productivity, SaaS, digital transformation

Reach and audience

Public platform figures. Ratings count people who left a rating, not total listeners.

Apple Podcasts (US)

5.0 / 5

5 ratings

Podcast Authority Score: 18 / 100

A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.

Quality

24

Social presence

0

YouTube

0

Engagement

32

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Guest appearances

Does not typically book guests

Based on episode analysis; this does not confirm that the show is currently accepting guests.