Why AI Needs a New Era of Probabilistic Adaptability

Much attention these days has been focused on how AI will disrupt the software development paradigm, specifically Gen AI’s ability to generate code and render low-code, no-code tools obsolete.

The assumption fails to recognize that AI will change the characteristics of every application we build, disrupting the paradigm of software development as we know it.

The reason is simple. Almost all IT systems and software applications developed today are deterministic, i.e., you gather requirements and develop applications accordingly. But in the Age of AI, AI will continually uncover unpredictable new findings and insights, so we must prepare for entering a new era of probabilistic operations.

For process, this class of problem can't be easily pre-defined into structured automation and orchestrations that represent the mainstream implementation today.

As a result, deterministic computing is no longer adequate for the Age of AI. Technologies that only speed up the development of deterministic applications will not be adequate either.

For organizations to thrive and reshape their industries in the Age of AI, they must be able to create probabilistic-ready applications.

Therefore, when organizations begin to rethink their application strategies, selecting a next-generation application platform that supports probabilistic use case scenarios is a critical criterion.

One such proven architecture is a metadata-abstraction and model-driven composition-enabled codeless composability architecture free of code generation and compilation and without the need for virtual machines.

AgilePoint was designed and architected in 2003 to deliver such an architecture that enables probabilistic automation and end-to-end business orchestration.

AgilePoint's ultimate vision is to enable the creation of natively AI-ready applications and to provide AI with the ability to dynamically adapt running applications based on continually uncovered real-time findings and insights without modifying code.

The architecture naturally supports business process management and low-code use cases, but it is also more scalable, sustainable, and adaptable without incurring technical debt.

In 2007, Gartner discussed AgilePoint for the first time in its Cool Vendor in Business Process Management Report:“

For processes where the sequence of work is not well understood or that must change dynamically based on the context of the transaction in real-time . . .

This class of process problem is not easily pre-defined into structured automation.

AgilePoint’s internal design enables users to design and deploy processes that can be dynamically changed in real-time.”

The discovery implied that AgilePoint was architected in 2003 to be probabilistic-ready for the Age of AI.