Agentic AI is transforming traditional software development by replacing hardcoded control logic in applications. In conventional systems, business logic is typically coded by software developers and structured into a multi-tier architecture. This architecture consists of a front end that interacts with users, a middle tier that exposes business logic via APIs, and a backend where CRUD operations manage data storage. Other architectures, like microservices, break down an application into smaller, independent services, each focused on a specific business function. Let's limit this discussion to multi-tiered architecture to simplify our understanding of Agentic AI transforming the software business. (however, the same could be applied to other software architectures as well)
With the advent of Agentic AI, this traditional model is shifting. For instance, consider a scenario where a business needs to identify the top 10 suppliers in the country and display this information visually. In the past, a Python developer would spend an hour or two writing logic to query the database and generate a graph using libraries like Matplotlib.
In an Agentic AI world, the control logic is essentially eliminated. The developer only needs to provide a simple prompt, such as "Fetch me the top 10 suppliers in the country for XXX and show them in a bar graph." That's the entirety of the task.
If the requirement shifts to pulling supplier details for the top performer in each state segment, there's no need for code revision. Instead, the prompt is simply modified, and the underlying LLM or RAG handles the data processing. This approach eliminates the need for control logic changes, testing, and new releases, significantly saving time, resources, and effort.
This revolution in software development will redefine how developers approach their work. Companies will increasingly seek developers skilled in training purpose-built models, leading to the creation of lightweight applications. Furthermore, the reliance on specific vendors and APIs for backend and data management will diminish, fostering a more democratized development environment.
For anyone aspiring to enter software development, it's essential to adapt and refocus their skills by:
- Embracing the role of assistive developers who leverage AI tools for faster coding. For example - Watson Code Assistant
- Shifting their architectural mindset to build and design solutions using Agentic AI methodologies.
Also, as we see this shift happening very fast, current software developers must adapt to this new Agentic AI era that is taking the industry by storm.
