Low Down on Low-Code

In this episode, Burley Kawasaki, VP of Product at Creatio, shares insights on how AI is transforming low-code platforms, the importance of governance in AI deployment, and the evolving strategies for enterprise AI adoption.

Key Topics

• AI integration in low-code platforms
• Governance and control in AI deployment
• Decentralized AI development and AI twin
• Platform and control plane architecture for AI
• Enterprise AI adoption strategies

Keywords

AI, low-code, platform, governance, enterprise, automation, no-code, AI twin, Creatio, digital transformation

Chapters

00:00
Introduction to the episode and guest Burley Kawasaki

01:57
Burley Kawasaki's journey and role at Creatio

04:02
The evolution of AI in low-code platforms

06:51
AI in regulated industries like banking and finance

09:52
The importance of a control plane for AI governance

13:04
Creatio's platform approach and AI Studio

15:55
The role of models and orchestration in AI processes

19:09
Scaling AI development and the importance of governance

22:08
Decentralized AI ideation and AI twin concept

24:05
Key changes for organizations adopting AI platforms

26:04
Future licensing models and platform adoption strategies

In this episode, we explore the future of AI-driven software development with Raza Dawood from Engineering Eleven. We discuss the challenges of vibe coding, the importance of discipline in AI deployment, and how enterprise can leverage AI safely and effectively.

Key Topics

• Challenges of vibe coding in enterprise
• Importance of discipline in AI deployment
• Engineering Eleven's approach to agentic SDLC
• Cost implications of AI models and optimization
• Role of governance and safety in AI development
• Automation and its impact on enterprise scaling
• Balancing creativity and discipline in AI coding
• Future of citizen developers with AI
• Risks of rogue AI and how to mitigate
• The evolution of low-code and AI integration

Sonali Sharma, author of The 90% Code - Rewriting Power For the AI Era discusses the urgent challenges and opportunities of AI, governance, and ethics. Sonali explores how collective intelligence can reshape organizations and address the risks of techno-feudalism and the hero model.

Key Topics

• AI trust and collective intelligence
• The hero model and its limitations
• Techno-feudalism and digital concentration
• Ethical foresight and indigenous governance principles
• Velocity of technological change versus linear governance
• The importance of systemic change over individual heroism
• The impact of AI on democracy and power structures
• Strategies for building ethical and resilient organizations

In this episode, David Eberle, CEO of Typewise, shares his journey from traditional management consulting to pioneering AI-driven customer service solutions. Julie Ask discusses the evolving role of AI in customer experience and the strategic importance for organizations to adapt quickly.

Key Topics

• David Eberle's journey from management consulting to AI entrepreneurship
• The evolution of customer service technology from chatbots to autonomous AI agents
• The importance of integrating AI into customer experience for competitive advantage
• Challenges in scaling AI in contact centers including data silos and staff training
• The role of CIOs and IT in orchestrating AI infrastructure and governance
• The impact of ChatGPT and generative AI on enterprise AI strategies

In this episode, John Rymer and Rick Greenwald explore the real value of AI in business, distinguishing between operational efficiency and strategic advantage, and debunking common misconceptions about AI's capabilities.

Key Topics

• The two ways IT systems deliver value: operational efficiency and strategic advantage
• The impact of AI hype and market expectations
• AI as a tool for operational efficiency and its limitations
• AI's role in strategic advantage and innovation
• The importance of asking the right questions when using AI for business reimagination
• The distinction between AI research and AI application in business
• The non-deterministic nature of AI and its implications for decision-making
• The evolution of AI from a revolutionary to an evolutionary technology
• The importance of critical thinking skills in leveraging AI effectively
• The risks of over-relying on AI for competitive advantage

In this episode, Chris Condo shares his journey from software engineering at Microsoft to becoming a key voice in AI's impact on engineering and organizational change. We explore how AI is transforming software development, the evolving role of engineers, and the systemic changes needed for successful AI adoption.

Key Topics

• Chris Condo's background at Microsoft and Forrester
• Impact of AI on software engineering and organizational change
• Adoption levels of AI in organizations and best practices
• Skills engineers need for AI success
• Systemic change required for AI integration
• Reimagining Agile practices for AI-driven development

In this episode, Val Huber discusses the evolution of rules-based systems, the impact of AI on business logic, and how Gen AI Logic is transforming application development through context engineering and executable models.

Key Topics

• The evolution of rules-based systems and their automation
• The impact of AI on generating business logic and rules
• The concept of context engineering and its role in AI training
• Differences between rules and procedural code in AI applications
• How APIs serve as logic containers in AI-driven architectures

This episode explores the evolving landscape of software pricing, the impact of AI and platform models, and how CIOs can navigate this complex environment. Experts Francis Carden and Andy Bartels share insights on future trends, pricing models, and strategic considerations.

Key Topics

• The shift from perpetual licenses to SaaS and platform models
• The challenges and opportunities of token-based and usage-based pricing
• The impact of AI and large language models on software costs
• The importance of economic analysis and risk management in software investments
• The role of platform vendors and models in reducing technical debt

In this episode, John Rymer and Rob Koplowitz sit down with Dave Marcus to discuss his hands-on evaluation of the fast-moving world of vibe coding, low-code, and process automation platforms.

Dave explains why he chose a CRM-style application as his test case: it had a realistic data model, a third-party integration with Microsoft SharePoint, and a workflow component that would reveal how these tools handle real business complexity rather than simplistic demo apps.

A major theme of the conversation is the difference between prompt-driven development and visual tooling. Dave found that while prompting could generate surprisingly functional applications, the experience often became frustrating when he needed to adjust layout, test changes, or understand dependencies. Visual tooling, when available, often helped—but some platforms treated it as secondary or immature compared to prompting.

The discussion also digs into a critical enterprise concern: maintainability. John and Rob push Dave on what happens when applications need to evolve over time due to changing business, regulatory, security, and workflow requirements. Dave emphasizes that model-based systems still matter because they make dependencies, workflows, and governance visible in ways code-heavy systems often do not.

Another key takeaway is workflow orchestration. Dave argues that workflow is not just a diagram—it is part of the application’s operational logic and must be understandable to domain experts, not just developers. He notes that some pure vibe coding tools bury workflow in code, while some process-centric platforms add complexity that may be more than needed for simpler applications.

In the end, Dave’s conclusion is nuanced: there is no single winner. Different platforms are better suited to different use cases, and the market is evolving too quickly for simplistic “replace everything” narratives to hold up.

Key takeaways

• A realistic evaluation needs a real application, not a toy demo.
• Prompting can produce functional apps, but visual refinement and testing remain important.
• Workflow and dependency visibility are essential for enterprise maintainability.
• No single platform category is best for every scenario.
• The market is evolving quickly, so these tools must be reassessed continuously.

Join us as we delve into the evolving landscape of low-code platforms, AI integration, and citizen development, featuring insights from Jeff Kuo of Ragic. Discover how organizations globally are transforming their workflows, overcoming challenges with AI-driven tools, and embedding citizen developers into their operational fabric.

Key Topics:

• Jeff Kuo’s journey from academic research to leading Ragic's platform development.
• The concept of citizen development and its practical applications in manufacturing and hospitality.
• How low-code platforms like Ragic support complex enterprise needs without traditional coding.
• The impact of AI on democratizing application creation and reducing learning curves.
• Strategies for managing risk, privacy, and governance in AI-assisted development environments.
• Cultural differences in application building, especially between Western and Asian markets.
• The future role of AI in enabling non-technical users to design and deploy systems seamlessly.