Drag & Drop

AI is changing what it means to be a software developer. But what happens when developers no longer need to check everything AI creates?
In this episode of Drag & Drop, Feroz Khan sits down with Owen Corstens from Harmony Group to explore how AI agents are changing software development, enterprise architecture, AI governance, OutSystems, and the role of the developer. Owen shares why developers may shift from creating software to owning outcomes, why enterprises need a clearer view of AI ROI, and why technical professionals need to think beyond a single platform.  
Owen also shares his unconventional route into technology without a university degree and why he believes hands-on learning, determination and continuous upskilling can be just as important as traditional credentials. 
In this episode, you’ll learn:
➤ Will AI replace developers or change what they do?
 ➤ Why developers may shift from creating to owning outcomes
 ➤ Why AI ROI is still unclear for many enterprises
 ➤ Why some companies move too fast while others get stuck in POCs
 ➤ How AI governance changes with agents
 ➤ Where enterprises should build and orchestrate AI agents
 ➤ Why developers need skills beyond a single platform
 ➤ How Owen built a successful technology career without a degree
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.
ITRAC helps organizations build Enterprise AI capability.
We support enterprise teams through:
• Specialist AI & OutSystems Talent
• Enterprise AI Training & Enablement
• OutSystems Training & Solutions
• Enterprise AI Community
From developing your existing teams to finding specialist talent, ITRAC helps organizations build the skills and capability needed to adopt AI effectively.
ITRAC | Building Enterprise AI capability through talent, training and community.

AI coding tools are generating more code than ever, but enterprise engineering teams are not necessarily delivering software faster.

In this episode of Drag & Drop, Feroz Khan sits down with Martin Reynolds, Field CTO at Harness, to explore the AI velocity paradox and what it means for software delivery, DevOps, AgentOps, platform engineering, and AI agents in production.

Martin explains why building an AI agent can be relatively easy, but deploying one safely requires a completely different level of governance, identity, testing, observability and accountability.

The conversation explores why code is no longer the main bottleneck, why traditional delivery processes are struggling to keep pace with AI-generated output and what engineering organizations need to operate increasingly autonomous systems safely at scale.

In this episode, you’ll learn:

➤ Why faster code generation isn’t producing faster software delivery
➤ What prevents AI agents from reaching production
➤ Why choosing the right AI model is only a small part of the challenge
➤ Why governance and guardrails cannot be added afterwards
➤ How AgentOps extends DevOps from code changes to autonomous decisions
➤ When deterministic automation is better than AI
➤ Why AI agents need identities, permissions and escalation paths
➤ How observability prevents autonomous systems from becoming dangerous black boxes
➤ What engineering teams need to operate AI safely at scale
➤ How Harness approaches everything that happens after code
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.
ITRAC helps organizations build Enterprise AI capability.
We support enterprise teams through:
• Specialist AI & OutSystems Talent
• Enterprise AI Training & Enablement
• OutSystems Training & Solutions
• Enterprise AI Community
From developing your existing teams to finding specialist talent, ITRAC helps organizations build the skills and capability needed to adopt AI effectively.
ITRAC | Building Enterprise AI capability through talent, training and community.

AI is lowering the barrier to building software.

But it is not lowering the bar for initiative, judgment, or solving real problems.

In this episode of Drag & Drop, Feroz Khan sits down with Lazar Jovanovic, the first Vibe Coding Engineer at Lovable, to discuss how he went from a non-technical background to building software at one of the fastest-growing AI companies globally.

Lazar shares how building in public, learning by doing, and solving real problems helped him create an opportunity before the role even existed.

They also explore how AI is changing who can build software, why generalists have an advantage, and what enterprises need to do to enable more employee-led innovation without creating a new generation of application silos.

In this episode, you’ll learn:

➤ How Lazar became Lovable’s first Vibe Coding Engineer
➤ Why generalists have an AI advantage
➤ How building in public creates opportunity
➤ Why “vibe coding” has moved beyond prototypes
➤ How AI is changing the build versus buy decision
➤ How a $1 million tool can be built for less than $5,000
➤ Why people closest to the problem can now build the solution
➤ How enterprises can prevent AI sprawl
➤ Where to start if you want to build an AI role inside your organization
➤ Why good judgment will matter more than raw effort
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.
ITRAC helps organizations build Enterprise AI capability.
We support enterprise teams through:
• Specialist AI & OutSystems Talent
• Enterprise AI Training & Enablement
• OutSystems Training & Solutions
• Enterprise AI Community
From developing your existing teams to finding specialist talent, ITRAC helps organizations build the skills and capability needed to adopt AI effectively.
ITRAC | Building Enterprise AI capability through talent, training and community.

Most organizations don’t have a shortage of AI pilots.

The real challenge is getting them governed, connected, and into production.

In this episode of Drag & Drop, Feroz Khan sits down with Scott Ditch, Principal Solutions Architect at OutSystems, to discuss what it will take for US government agencies to move beyond AI experimentation and create measurable value.

Scott shares what he is seeing across the public sector, including why many AI agents remain trapped in a “never-ending proof-of-concept state” and how disconnected projects could create the next generation of technology silos.

In this episode, you’ll learn:

➤ Why trust remains one of the biggest barriers to government AI adoption
➤ What prevents AI pilots from reaching production
➤ Why agentic systems require a different development lifecycle
➤ How agencies can govern an entire portfolio of AI systems
➤ Why human accountability remains essential in high-stakes decisions
➤ How AI can modernize decades-old government systems
➤ How organizations can preserve institutional knowledge as experienced employees retire
➤ How AI is changing the roles of developers, architects and technology teams
➤ Why one agent or one AI model cannot solve every problem
➤ How model selection and token costs affect enterprise AI architecture
➤ How agencies can adapt when AI evolves faster than procurement cycles
➤ Whether AI could eventually make traditional applications disappear
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.
ITRAC helps organizations build Enterprise AI capability.
We support enterprise teams through:
• Specialist AI & OutSystems Talent
• Enterprise AI Training & Enablement
• OutSystems Training & Solutions
• Enterprise AI Community
From developing your existing teams to finding specialist talent, ITRAC helps organizations build the skills and capability needed to adopt AI effectively.
ITRAC | Building Enterprise AI capability through talent, training and community.

In this episode of Drag & Drop, I’m joined by Chris Merz from Siemens to discuss how enterprise AI is moving beyond chatbots, copilots, and isolated use cases.

We talk about why moving fast with AI is not enough, why data context and governance matter more than ever, and how platforms like Mendix are evolving beyond low-code into a much bigger enterprise AI conversation.

Chris shares his perspective on what enterprises are getting right, where many are going wrong, and why AI adoption needs to be connected to real business outcomes, not just individual productivity.

We also discuss the role of partners, the future of developers, the risk of creating AI silos, and what organizations need to think about if they want to move from AI experiments to scalable, governed AI systems.

If you’re involved in enterprise AI, application development, low-code, digital transformation, or technology strategy, this conversation is for you.
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.
ITRAC helps organizations build Enterprise AI capability.
We support enterprise teams through:
• Specialist AI & OutSystems Talent
• Enterprise AI Training & Enablement
• OutSystems Training & Solutions
• Enterprise AI Community
From developing your existing teams to finding specialist talent, ITRAC helps organizations build the skills and capability needed to adopt AI effectively.
ITRAC | Building Enterprise AI capability through talent, training and community.