Low Down on Low-Code

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.

In this episode, James Duez, CEO of Rainbird, dives into the intricacies of how knowledge and context are represented within AI systems. We explore how structured knowledge graphs, deterministic reasoning engines, and hybrid architectures can elevate AI decision-making and trustworthiness. Whether you're a product manager, AI developer, or business leader, this conversation clarifies how to architect AI solutions that are explainable, auditable, and reliable.
The distinction between case context (transaction-specific data) and policy context (knowledge and rules) in AI systems.
How Rainbird leverages knowledge graphs and ontologies to formalize and reason over policy and tacit organizational knowledge.
The limitations of large language models (LLMs) in reasoning and the importance of keeping them outside the core decision logic.
The role of inference engines in building deterministic, auditable AI decision layers grounded in policy and knowledge.
The evolution from traditional knowledge management tools like SharePoint to advanced knowledge elicitation and modeling using AI.
The concept of knowledge as a first-class citizen in AI architecture, enabling faster and more reliable decision-making.
The risks of relying solely on LLMs, including hallucinations, model drift, and lack of explainability, and how hybrid architectures mitigate these issues.
The importance of roles like knowledge engineers and business analysts in managing and architecting organizational knowledge layers.
Rainbird's reusable, enterprise-grade platform for building, managing, and reasoning over knowledge graphs, separable from data sources.
The future of hybrid AI architectures: combining symbolic reasoning with probabilistic models to balance flexibility and trust.

In this episode, John Rymer and Rick Greenwald explore the complexities of data copying versus accessing data in place, focusing on performance, freshness, correctness, and consistency. They discuss how these factors impact data management strategies, especially in the context of AI and modern data access challenges.
Key Topics
Data copying vs in-place access
Performance implications of data access
Data freshness and latency
Data correctness and consistency
Distributed data challenges
Data governance and compliance

In this episode, Francis Carden and Rob explore the evolving role of models in software development, AI, and business processes. They discuss how structured models can revolutionize code, automation, and business agility, emphasizing the importance of explicit, understandable, and reusable frameworks.
Key topics
The role of models in software and AI development
How structured models improve maintainability and changeability
The impact of AI on code generation and business logic
The importance of explicit, understandable models for business agility
The potential of models to reduce repetitive work and increase reuse
Challenges and risks of unstructured AI-generated code
The future of model-driven platforms and AI vendors
keywords

#Models, #AI, #Software Development, #Business Processes, #Low-Code, #No-Code, #Automation, #Structure, #Reusability, #AI-Generated Code

In this episode, Francis Carden challenges traditional views on software development, reimagining computing, and the future of AI in application creation. Join us for a provocative conversation on how legacy systems are evolving and what that means for businesses today.
Keywords
Reimagining computing and application development
The impact of AI on coding and software creation
Legacy systems and their evolution in modern business
The role of low code/no code platforms in digital transformation
The importance of reusable components and modular architecture