Democratization of Development Through Knowledge Management: Analysis of the DDPS Method

The presented Data-Driven Problem Solving methodology demonstrates a fundamental shift in expert system architecture. Rather than the traditional rigid binding of business logic to program code, this model proposes that knowledge becomes a separate, modifiable resource. This approach addresses one of the key challenges of modern digital transformation—the shortage of qualified developers and the high cost of maintaining legacy systems.

The primary value of this approach lies in democratizing the automation process. Domain experts with deep subject matter knowledge gain tools for directly formalizing their algorithms without translating them into programming languages. This eliminates the communication barrier between business and IT, radically shortening the cycle for creating application solutions. The system ceases to be a "black box" requiring expensive maintenance and transforms into a living organism that grows alongside the accumulation of specialist experience.

In the context of artificial intelligence development toward 2026, this method offers an important alternative to probabilistic generative AI models, ensuring determinism and transparency of decisions. In the long term, such an approach transforms the economics of software development. Implementation costs decrease, while the resulting products exhibit high scalability and adaptability. The transition from writing code to managing structured knowledge opens the path to mass automation of narrowly specialized tasks that were previously unprofitable for software implementation. This is not merely a tool, but a strategy for building flexible information ecosystems of the future.