Does Agentic AI Mark the End of Software Agencies?
The advent of Agentic AI has sparked a profound shift in how businesses approach software development. Companies like Replit are pioneering platforms that enable developers, citizen developers, and even non-coders to leverage AI-driven agents in building applications and automating complex tasks. This capability is reshaping the need for traditional software development services, raising the question: will Agentic AI replace software agencies?
Agentic AI uses multiple AI agents, sometimes multimodal, to handle complex functions across development and customer-facing applications. These systems can write code, generate content, create workflows, and more—often without extensive input from a human coder. Platforms such as Replit , which offer easy-to-use AI development environments, are at the forefront, allowing businesses to automate and reduce dependency on external software providers.
But does this mean the end of software agencies? Not necessarily. Here’s why, along with five strategies software agencies can use to thrive in the age of Agentic AI.
What is Agentic AI, and Replit?
Agentic AI refers to a system of intelligent agents designed to work independently or in concert to accomplish tasks typically requiring human expertise or extensive coding knowledge.
For example, Replit provides a platform for building, deploying, and collaborating on applications that uses agentic models to help developers code faster and smarter. Replit’s recent advancements focus on enabling multimodal interactions, where AI agents can read, write, and execute code based on simple instructions, opening doors for people with minimal coding skills to develop powerful applications.
1. Build at the Intersection of Deep Domain Capabilities and Technology
Agentic AI is versatile but generally lacks deep industry-specific knowledge. Software agencies with a strong understanding of particular verticals—such as healthcare, finance, or manufacturing—can provide tailored insights and solutions that generic AI cannot. By focusing on specific domains, agencies can differentiate their offerings and act as specialists who can leverage Agentic AI as a tool, rather than a competitor.
Building at this intersection means investing in domain experts and technologists who can navigate industry nuances, regulatory requirements, and unique challenges. For example, in healthcare, domain-specific regulations like HIPAA compliance in the U.S. require expertise that AI alone cannot replicate. By marrying domain knowledge with AI, agencies become indispensable partners rather than replaceable vendors.
2. Upgrade to an Enterprise-Grade Stack
Agentic AI may excel in handling individual tasks or generating code snippets, but enterprises often require robust, scalable, and secure systems. Agencies can offer value by creating enterprise-grade software with high-performance architecture, data security, and compliance measures—standards that AI-driven platforms alone may struggle to meet.
Investing in infrastructure to support large-scale applications, multi-region deployments, and compliance management can set agencies apart. Enterprise clients seek resilience, which requires a human touch, customized solutions, and a level of accountability that Agentic AI cannot yet provide.
3. Prioritize Value-Addition Work
AI can handle repetitive, low-value tasks, but it struggles with high-impact, strategic projects that require creativity, problem-solving, and innovation. Agencies can shift their focus from routine development to areas where they add unique value, such as innovation consulting, custom system integration, or strategic planning. For instance, designing customer journeys, aligning software with business goals, and developing user-centric products are areas where agencies can excel over AI.
By identifying and prioritizing high-value, high-touch services, agencies can adapt their offerings to deliver enduring value in ways that Agentic AI cannot duplicate. Value addition here means actively improving the client’s business outcomes rather than just delivering code.
4. Build Agentic AI Centers of Excellence (CoE)
Rather than resisting the wave of Agentic AI, agencies can embrace it by establishing Centers of Excellence dedicated to Agentic AI capabilities. These CoEs can train teams, create best practices, and guide clients in integrating Agentic AI into their workflows.
This shift positions agencies as leaders in the AI field, able to consult on implementing, optimizing, and scaling Agentic AI solutions. CoEs can help clients navigate complex AI integrations, offering insights and expertise that drive successful adoption. For example, agencies can use these centers to demonstrate AI’s potential to handle customer support inquiries or streamline operational processes, offering clients a hybrid solution where human and AI resources work together seamlessly.
5. Onboard More Elastic Projects
Geoffrey Hinton famously said that AI wouldn’t replace elastic jobs—those requiring adaptability and human discretion— and the same principle applies to elastic projects. Elastic projects are those that require continuous iteration, adaptation, and a blend of automated and human input. These projects are often exploratory, evolving, and demand unique insights that AI alone cannot provide.
In software, elastic projects may include ongoing software evolution, complex integrations, or projects requiring a human-led agile approach. By focusing on elastic projects, agencies can provide a more adaptive, iterative, and nuanced service offering that Agentic AI tools aren’t designed to handle.
For example, a project requiring ongoing adaptation based on user feedback or regulatory changes benefits from human oversight. While Agentic AI can support such projects by automating parts of the work, agencies offer the oversight and flexibility that ensure long-term success.
Conclusion
Agentic AI is transforming the software industry, providing businesses with tools to develop software with unprecedented speed and efficiency. However, the technology lacks the depth, flexibility, and specialized expertise required for many complex, enterprise-grade, and domain-specific projects. Software agencies can survive—and even thrive—by focusing on areas where human expertise and creativity remain irreplaceable.
About CodeNinja :
CodeNinja is an enterprise software services, AI, and full-stack GCC solutions company. Founded a decade ago, CodeNinja's mission is to land-up at a point where helping global businesses with their technology initiatives and improving societies where its engineering hubs are located come together as one holistic outcome - often referred to as 'Impact Engineering'.
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Interesting take on the future of software agencies! Emphasizing domain expertise and adaptability seems key to navigating these changes. How do you see agencies leveraging these strengths in their client relationships?