Drag & Drop

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 builds AI-ready, low-code-enabled teams.

We help organizations move from AI pilots to real production execution through:

• Strategic Staffing
• Enterprise AI & Low-Code Training
• Agentic AI Bootcamps
• CoE & Governance Advisory

AI creates momentum.
Execution creates advantage.

Whether you're scaling delivery or building your AI capability — we help you build it right.

Enterprise AI is moving fast… but most companies still aren’t ready to operate it at scale.

In this episode of Drag & Drop, Feroz Khan is joined by Hugo Fragoso, Director, Strategic Customers - EMEA at OutSystems, to discuss what enterprise leaders are getting wrong about AI adoption, governance, internal capability, and scaling delivery in an AI-driven world.

As organizations rush to experiment with Agentic AI, copilots, and automation platforms, many are discovering that building something quickly is the easy part. The real challenge is creating the operating model, governance, and internal capability needed to run AI reliably inside the enterprise.

Hugo shares insights from working directly with strategic enterprise customers across EMEA and explains why the companies succeeding with AI are thinking far beyond individual use cases.

What you’ll learn in this episode:

• Why the most successful enterprises are “building factories” instead of individual apps
• The biggest mistake companies are making with AI strategy right now
• Why platform governance matters more than choosing a single LLM
• The danger of relying on “hero developers” inside enterprise teams
• Why internal enablement is critical for long-term low-code and AI success
• How enterprises should balance partners vs internal capability
• The role architecture, governance, and operating models play in scaling AI
• Why security and risk teams need to be involved from day one
• What separates enterprises that scale from those that stall
• Why governed AI will define the winners over the next few years

The conversation around AI is shifting.

From simply generating outputs…to building systems that enterprises can actually trust, govern, scale, and operate long term.
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.

ITRAC builds AI-ready, low-code-enabled teams.

We help organizations move from AI pilots to real production execution through:

• Strategic Staffing
• Enterprise AI & Low-Code Training
• Agentic AI Bootcamps
• CoE & Governance Advisory

AI creates momentum.
Execution creates advantage.

Whether you're scaling delivery or building your AI capability — we help you build it right.

Will AI replace developers… or completely change what developers focus on?
In this episode of Drag & Drop, Feroz Khan is joined by Elyse Gilbert to discuss her journey from music performance major to OutSystems developer, the evolution of low-code development, and how AI is rapidly reshaping the future of software delivery.
As AI becomes more embedded into modern development platforms, the role of the developer is starting to shift away from repetitive manual work and toward architecture, user experience, business thinking, and human-centered design.
Elyse shares her experience transitioning into tech without a traditional engineering background, learning OutSystems under pressure, and why mindset and adaptability are becoming more important than ever in the AI era.
What you’ll learn in this episode:
• How Elyse transitioned from music performance into software development
• The challenges of learning OutSystems and low-code development
• Why mindset plays a major role in succeeding in tech
• How AI is changing the day-to-day role of developers
• Why development is shifting from manual work to higher-level thinking
• The growing importance of user experience and human behavior in software
• How AI is improving requirements gathering and development workflows
• Why developers who ignore AI risk falling behind
• The importance of community, continuous learning, and adaptability
The developer role isn’t disappearing.
But it is evolving faster than ever.
And the developers who learn how to work alongside AI - rather than compete against it - will have a massive advantage over the next few years.
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.

ITRAC builds AI-ready, low-code-enabled teams.

We help organizations move from AI pilots to real production execution through:

• Strategic Staffing
• Enterprise AI & Low-Code Training
• Agentic AI Bootcamps
• CoE & Governance Advisory

AI creates momentum.
Execution creates advantage.

Whether you're scaling delivery or building your AI capability — we help you build it right.

AI made development faster… but has it actually made it better?
In this episode of Drag & Drop, Feroz Khan is joined by OutSystems MVP Krishnnambal Sundaram to break down what’s really changing in software development and why speed is no longer the advantage it once was. 
As AI tools and “vibe coding” make it possible to build applications in minutes, the real challenge is shifting somewhere else entirely. It’s no longer about how fast you can create something… it’s about whether you can trust it, scale it, and run it in a real-world environment.
Krishnnambal shares her journey from traditional development into low-code, training over 2,000 developers, and what she’s seeing firsthand as AI reshapes how teams build, deploy, and think about software.
What you’ll learn in this episode:
 Why speed is no longer the key differentiator in modern development 
 The gap between building quickly and running in production 
 The biggest misconceptions around low-code and why they still exist 
 How AI is changing (and not changing) the role of developers 
 Why many developers struggle to understand the code AI generates 
 The difference between prototype-ready and production-ready systems 
 How platforms are evolving to bring governance, trust, and context into AI development 
 What developers should focus on now to stay relevant 
 The importance of architectural thinking in an AI-driven world 
 Certifications vs real experience and what actually matters in hiring 
The shift is already happening.
From building faster…to understanding what you’ve built…and being able to run it when it actually matters.
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.

ITRAC builds AI-ready, low-code-enabled teams.

We help organizations move from AI pilots to real production execution through:

• Strategic Staffing
• Enterprise AI & Low-Code Training
• Agentic AI Bootcamps
• CoE & Governance Advisory

AI creates momentum.
Execution creates advantage.

Whether you're scaling delivery or building your AI capability — we help you build it right.

Why are AI agents easy to build… but so hard to run in the enterprise?

In this episode of Drag & Drop, Feroz Khan is joined by OutSystems MVP Lotte Kuiper to explore what really happens when AI moves from prototype to production and why many teams are unprepared for what comes next.

As AI becomes more accessible, teams are rapidly building agents, automations, and new workflows. But while it’s easier than ever to create something that works, running it in a secure, governed, and trusted environment is a completely different challenge.

Lotte shares insights from working closely with enterprise teams, testing new platform capabilities, and building real-world AI solutions that go beyond experimentation.

What you’ll learn in this episode:
- Why AI agents are easy to build but much harder to run in production
- The biggest risks when moving from prototype to real-world deployment
- Why data, structure, and process still matter in an AI-first world
- The challenge of trust and why AI still feels like a “black box”
- How enterprises should think about governance and control for AI systems
- What developers often underestimate when working with AI in low-code platforms
- How AI is reshaping the gap between high-code and low-code development
- Why “vibe coding” and rapid builds can create hidden technical risk
- How the role of developers is evolving into orchestration and system design

The shift is already happening.

From building AI quickly…to making sure it actually works when it matters.
Tell us what you loved about this Episode.
Website: itracusa.com
Contact: Feroz Khan
🎙️ This episode is brought to you by ITRAC.

ITRAC builds AI-ready, low-code-enabled teams.

We help organizations move from AI pilots to real production execution through:

• Strategic Staffing
• Enterprise AI & Low-Code Training
• Agentic AI Bootcamps
• CoE & Governance Advisory

AI creates momentum.
Execution creates advantage.

Whether you're scaling delivery or building your AI capability — we help you build it right.