Reimagining the Application Landscape with GenAI and Agentic Frameworks

The emergence of Generative AI (GenAI) and agentic frameworks marks a paradigm shift in the way applications will be conceived, built, and operated. Applications have primarily served as tools designed to assist humans in performing specific tasks, relying heavily on structured user interfaces and predefined business logic. However, this traditional approach will likely be disrupted by a new wave of technological advancements that promise to revolutionize how software applications function and interact with the world.

In this article, I explore how GenAI and agentic frameworks will expand the boundaries of the software industry.

From redefining the Total Addressable Market (TAM) to enabling richer input modalities, decentralizing business logic, and facilitating peer-to-peer interactions, these innovations will reshape the application landscape in profound ways. As we navigate this transformation, it’s clear that the future of applications will be more dynamic, efficient, and autonomous than ever before.

TAM (Total Addressable Market)

Current applications handle only the process part of it, meaning humans interact with systems to capture data, and based on that data, certain processes are kicked off. This is the current paradigm, where applications are primarily tools used by humans to achieve parts of their jobs.

The change in the landscape with GenAI and agentic frameworks is that the Total Addressable Market will expand. It will no longer cover just the tool space (the doing part), but also the part of the human interaction with the system. Agentic frameworks can now take over functions humans perform during system interactions.

In this sense, the overall addressable market for the software industry will grow significantly. This will be one major change driven by GenAI.

Disrupting SAAS and Traditional Application Development Model

The second thought is about how applications today function. They consist of business logic and retain data. Systems, especially system-of-record systems, hold the data, becoming the single source or copy of truth, with business logic layered on top to execute and govern processes.

With agentic frameworks and GenAI implementations, business logic will be much more loosely defined. Agents and GenAI will dynamically apply business rules, unlike current applications where logic is codified into the system.

This means business logic will now be part of the agents, leaving only the data and CRUD operations outside. This shift could significantly change SaaS applications, potentially reducing the need for centralized SaaS implementations. Data would no longer need to reside in a single database; it could be distributed across various persistent stores, with Agents/GenAI driving the logic.

This marks a significant transformation from how applications are written today and could lead to the emergence of new applications powered primarily by GenAI, capable of functioning with data stored anywhere across the enterprise.

Modality and Richness of Input Data

The third thought is about how current applications are constrained. They primarily rely on a visual UI, requiring users to enter data manually as text or through APIs. This dependency limits how current applications operate.

GenAI and agentic frameworks will significantly change this. They allow for data input through various modalities beyond text, including audio, video, sensory data, touch, and more, while still supporting text data.

This means applications powered by GenAI won’t need humans to enter data manually. Conversations on the phone, captured images, and recorded videos can all be synthesized, creating a much richer dataset for applications to operate on.

This shift in input modalities will majorly transform the application landscape, enabling new capabilities for data processing and synthesis. The variety and richness of input data will greatly expand, allowing applications to operate more dynamically and effectively, marking another significant impact of GenAI.

Peer to Peer Autonomous Interactions

The final thought is about how current applications rely on human interaction with the system through a UI. In contrast, with agentic frameworks, interactions could shift to peer-to-peer without humans in the loop.

For example, consider recruitment portals today. A recruiter posts a job on a platform like LinkedIn/Indeed/etc., candidates manually search for jobs, apply, and recruiters review applications to proceed. This process is human-centric and often inefficient.

With agentic frameworks, we could eliminate intermediaries like LinkedIn. Each company could have its own recruiter agent, and each candidate their own candidate agent. The candidate agent would proactively scour recruiter agents across multiple companies to identify fitting job opportunities. Similarly, recruiter agents would engage in agentic conversations to assess the best candidate matches.

This would transform the current process, removing humans from the loop and enabling peer-to-peer interactions that are more thorough, specific, and efficient. The job-hunting process, in this case, would become much more streamlined.

One critical aspect of enabling peer-to-peer interactions is trust. Blockchain frameworks could play a key role here by defining and enforcing contracts between agents, ensuring trust and reliability in these interactions.

As peer-to-peer applications become more common, the combination of blockchain and agentic frameworks could form a strong foundation, making processes highly efficient and no longer reliant on human intervention. This represents another significant shift in how the application landscape will evolve due to agentic frameworks.

Conclusion: A New Era of Applications

The transformative potential of GenAI and agentic frameworks is undeniable. From expanding the total addressable market to decentralizing business logic, enabling richer data modalities, and fostering peer-to-peer autonomous interactions, these innovations will likely reshape the software industry at its core.

The fusion of GenAI, agentic frameworks, and complementary technologies like blockchain has the power to redefine efficiency, creativity, and scalability in the application landscape. By harnessing these advancements, we can create a future where software is not just a tool but an intelligent partner that drives progress across industries.

The next wave of innovation has already begun — those who recognize its potential early will lead the way in shaping a more dynamic and interconnected world.