Low Down on Low-Code

In this episode, Roland Boulos, VP of Solution Consulting at UnifyApps, discusses the future of AI platforms, the architecture of UnifyApps, and how organizations can leverage AI to transform their business processes. He shares insights on building a foundational AI platform, reimagining applications, and the evolving role of solution partners.
Key Topics
UnifyApps platform architecture
AI agent building and orchestration
Data ontology and knowledge graphs in AI
Reimagining enterprise applications with AI
Role of solution partners in AI transformation

New name, same podcast format. We're changing the name of Low Down on Low-Code to The Low-Down from Analysis.Tech. John Rymer and Rob Koplowitz discuss the market drivers that drove the decision. The key learning here: Low-Code models and platforms are more important than ever. Just the name is changing.

In this insightful interview, Robert Stackowiak the author of Design Thinking in Software and AI Projects: Proving Ideas Through Rapid Prototyping joins Rick Greenwald and Rob Koplowitz to discuss the principles of design thinking and its application to software, AI, and database systems. Guest Robert shares how this approach fosters collaboration, improves project success, and enhances organizational innovation.
Key Topics
Design thinking principles in software and AI
Application of design thinking to database and system design
Organizational collaboration and silos in tech projects

Pardon the provocative title, but the term "low-code" is certainly passe. Even the guy that invented the term agrees. ;)
Here's the thing though; much of the functionality of low-code platforms will become more critical than ever. In this episode of Low Down on Low-Code the entire Analysis.Tech research team discusses:
How vibing and vibe coding have forever changed the world of development 
The opportunities for a new world of business-first developers to build new classes of applications
The critical role of a model in building and maintaining man applications
How a well-designed platform can be leveraged to drive consistency, lower costs and avoid risk
Why we are at a moment in time where over-rotation on AI development could be very unwise

In this episode of 'The Low Down on Low-Code', Rick Greenwald, John Rymer, Tony Baer, and Matthew Housley discuss the intricate relationship between developers and data management, the impact of AI on data practices, and the importance of data governance. They explore the tensions between speed and quality in software development, the need for collaboration through fusion teams, and the challenges posed by AI in data management. The conversation emphasizes the necessity of understanding data quality, security risks, and the future of data architecture in an increasingly AI-driven landscape.
Takeaways
Developers often prioritize speed over data quality.
Data governance is essential for ensuring data correctness.
AI can significantly impact data management practices.
Collaboration between developers and data professionals is crucial.
Understanding data context is vital for effective governance.
Security risks are heightened with the use of AI and agents.
Fusion teams can help bridge the gap between business and tech.
Data quality issues can lead to significant business risks.
Training on data risks is often lacking in the industry.
Starting simple with AI and orchestration is a best practice.