In this episode, Peter Maddison and Dave Sharrock sit down with Josh Hill, an HR innovator who's challenging the traditional transactional approach to people management. Josh shares his unconventional journey from the Australian military to progressive HR, where he's pioneering the concept of "work as a product" at marketing agency Tier 11 and through his recruiting venture, Super Hired.

Josh explains how HR teams can shift from rushing to solutions toward discovery-led approaches that treat employees as customers. He walks through real examples of iterative onboarding improvements, the importance of understanding jobs to be done in hiring, and why talent density matters more than filling seats quickly.

The conversation explores compensation dynamics, the value of matchmaking over recruiting, and how small experiments can build momentum for broader HR transformation. Whether you're leading people operations or navigating organizational change, this episode offers practical insights on making HR less transactional and more intentional.

Key Takeaways:

1. Start with discovery, not solutions – Before building HR processes or solutions, take time to interview employees, understand their stories and experiences, and map out what's actually obstructing outcomes. Even 10 minutes of discovery beats rushing to a result.
2. HR as a matching exercise, not a numbers game – Recruitment and people management generate real value when viewed as careful matchmaking between what work a company offers and what employees are looking for, rather than just transactional headcount filling.
3. Make HR less transactional – Slow down important conversations around hiring, onboarding, and employee experience. These decisions deserve the same rigor companies apply to external product development, not just checkbox processes.

Product managers and product owners are drowning in documentation, vision statements, roadmaps, and backlogs. But what if AI could handle the heavy lifting, freeing you up to actually talk to customers?

In this episode, Dave and Peter explore how large language models are changing product management. They go beyond the obvious use cases (like generating user stories) to discuss upstream opportunities: building product strategy, validating market positioning, and testing ideas against competitors.

You'll learn:

• Why documenting your product strategy matters (and why most PMs skip it)
• How to prompt AI to be critical, not just complimentary
• The danger of accepting AI outputs without evaluation
• Temperature settings, context windows, and other practical techniques
• What to do with the time you get back (hint: talk to real customers)

Dave and Peter also share a key practice: write down what you expect before you prompt. This simple step helps you critically evaluate AI responses instead of accepting them at face value.

If you're a product manager, product owner, or anyone building digital products, this conversation will help you use AI as a tool for better thinking, not just faster output.

In this episode, Peter Maddison and Dave Sharrock welcome Justin Trombold, President and Founder of Antison Advisors, to discuss the parallels between agile transformation and generative AI adoption in organizations.

Justin shares insights from his work helping companies navigate generative AI readiness, revealing that the biggest challenges aren't technical; they're organizational. From end-user proficiency to cross-functional collaboration, the conversation explores why companies struggle to move beyond "toy apps" to create real business value with AI.

Key topics covered:
• Why organizations need an AI strategy before investing in tools
• The critical importance of end-user proficiency with LLMs
• How cross-functional collaboration enables AI success
• Why annual planning cycles may be holding your AI initiatives back
• The parallels between agile adoption and AI transformation
• Moving from efficiency gains to true value creation

Whether you're leading AI initiatives, managing agile transformations, or wondering why your organization's AI investments aren't paying off, this conversation offers practical frameworks for thinking about organizational readiness in the age of generative AI.

THREE KEY TAKEAWAYS:

1. End-user proficiency is everything.
2. Define the sandbox before choosing the toys.
3. Innovation in planning matters as much as innovation in products.

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