What happens when AI stops being just a tool and becomes the team that designs, builds, tests, secures, documents, deploys, and even maintains your software?In this episode of the M365 FM Podcast, Mirko Peters speaks with Mark Smith [MVP], widely known as NZ365Guy, about the transition from traditional Microsoft development toward AI-first software engineering. Mark brings decades of experience across Microsoft technologies, Dynamics 365, Power Platform, Copilot, AI platforms, consulting, training, podcasting, and software development.The conversation goes far beyond Microsoft Copilot. Mark explains how he is building his own AI software factory with specialized autonomous agents, why he uses OpenCLAW as an AI harness, how multiple AI models can work together, why context engineering is becoming more important than basic prompt engineering, and what developers and IT professionals should learn to prepare for the Intelligence Age.
FROM MICROSOFT TRAINING TO THE AI ERA
Mark's journey into the Microsoft ecosystem started around 30 years ago. What began with an interest in learning web design eventually led him into IT training, Microsoft infrastructure, networking, management, Dynamics CRM, Power Platform, Copilot, and AI.He recalls the early days of the web, when technologies such as HTML and CSS were still relatively new to many organizations and Microsoft NT4 was becoming increasingly important. Over seven years, Mark progressed from selling technical training to delivering courses himself and eventually becoming general manager of the company.That experience created the foundation for a career that would continuously evolve alongside Microsoft's technology stack.
FROM DYNAMICS CRM TO POWER PLATFORM AND AI
Mark describes how his Microsoft journey moved from early Microsoft CRM into Dynamics 365 and later Power Platform. He was attracted to CRM not simply as a sales system, but as a platform that could be used to create many different kinds of business applications.Power Platform continued that evolution through low-code development. But Mark believes the next transition is significantly larger.AI is changing the interface between humans and software development itself. Instead of spending hours navigating configuration screens and traditional user interfaces, developers increasingly have the ability to communicate their desired outcomes through prompts, APIs, MCP interfaces, command-line tools, and AI agents.For Mark, this represents a fundamental shift away from traditional low-code development toward AI-first software creation.
THE MOMENT GENERATIVE AI CHANGED EVERYTHING
Mark began exploring AI years before ChatGPT, particularly around machine learning and Microsoft's Cognitive Services. However, the arrival of ChatGPT in November 2022 made the scale of the coming transformation much clearer.Another important moment came when he experimented with early Copilot capabilities inside Power Platform. During a Microsoft MVP session, he was able to prompt an application into existence while the technology was being demonstrated.That experience reinforced an idea that would increasingly shape his work: software creation was becoming conversational.
WHY MARK EXPANDED BEYOND THE MICROSOFT AI ECOSYSTEM
Although Mark has spent decades working with Microsoft technology, his current AI environment is deliberately multi-model.He discusses his experience with OpenAI, Anthropic, Microsoft models, Chinese AI models, European models, and other providers. Rather than designing systems around one vendor, he wants the ability to select the best model for a particular task.This approach reduces dependency on any single AI provider and allows the underlying models to change without rebuilding the entire system.The model becomes a replaceable component rather than the center of the architecture.
TRUST, DATA SOVEREIGNTY AND MICROSOFT AI
The discussion also explores why Microsoft's ecosystem remains important for enterprise AI.For regulated organizations, the location where AI inference happens can matter significantly. Data sovereignty, compliance requirements, infrastructure location, and third-party model providers can all affect whether an AI architecture is acceptable.Mark explains that he is developing software where Microsoft's own models and infrastructure can provide an important trust advantage. Organizations that already trust Microsoft's cloud environment may prefer AI workloads that remain within that ecosystem.This becomes particularly important in countries and industries where data cannot easily leave a specific jurisdiction.
WHAT IS AN AI SOFTWARE FACTORY?
One of the central topics of the episode is Mark's concept of an AI software factory.Traditionally, software projects require multiple specialized roles: requirements analysts, architects, developers, engineering managers, testers, security specialists, documentation teams, and release managers.Mark asked a different question:What happens if each of thos...
