Agentic AI in Software Development: How Dev Teams Are Evolving

AI agents understand complex goals, determine actions, and work toward achieving them without constant oversight, meaning AI can now directly contribute to team workflows, helping to write, test, debug, and optimize code at a level previously unimaginable.

Multiple ways of working with AI on software development projects are emerging, and you may have come across the terms no-code, low-code and pro-code. Whilst the majority of senior devs (pro-coders) are leveraging AI to optimise their workflows, at the other end of the spectrum, no-coders are building applications from scratch, and many are working as freelancers, charging for developer services.

Blurred Lines Between No-Code Platforms and No-Coders

The rise of no-code platforms like Wix, Shopify, and Bubble has revolutionized how people approach software development. These platforms democratized tech by empowering non-technical users to create websites, apps, and digital products with drag-and-drop simplicity. What was once the exclusive domain of pro-coders has become accessible to entrepreneurs, small businesses, and freelancers looking for quick, functional solutions.

However, as no-code tools grow more powerful, the term no-coders is no longer limited to platform users. Increasingly, it describes a new breed of creators who blend no-code solutions with advanced AI tools, APIs, and automation frameworks to build more sophisticated digital products.

On forums like r/NoCode, which has over 50,000 members, conversations range from selecting the right no-code platform to freelancers offering custom web app development services. This evolution blurs the lines between no-code platform users and software developers.

This transition has sparked debates about the quality, scalability, and security of no-code solutions. While no-code has enabled a wider audience to participate in software development, its rapid adoption raises questions about technical debt, vulnerability to cyberattacks, and scalability challenges.

Agentic AI’s Role in Software Development

Adding to this dynamic is the emergence of agentic AI — autonomous AI tools capable of executing multi-step tasks with minimal human input. These tools, such as OpenAI’s evolving agent models, are being used for everything from automating repetitive tasks to generating large portions of code.

This is not a new concept by any stretch of the imagination as many experts have been predicting this rise of Agentic AI for a while. “I think AI agentic workflows will drive massive AI progress this year — perhaps even more than the next generation of foundation models. This is an important trend, and I urge everyone who works in AI to pay attention to it.” ~Andrew Ng, Co-Founder of Coursera on X in Q1 2024.

Even heavy weights like Nvidia CEO Jensen Huang have chimed in. Speaking in November 2024, Huang commented that “We’re starting to see enterprise adoption of agentic AI really is the latest rage,” implying that we’re already seeing adoption of agentic AI in businesses worldwide. Despite this foresight, Agentic AI has only started to take off as a hot topic at the turn of 2025.

The potential for future expansion and seems to be endless, as highlighted by Aaron Levie, CEO of Box who posted on X in Jan 2025, “AI Agents have unlimited attention span and you can run them in parallel.”

Low-risk development tasks such as creating landing pages or automating simple workflows are increasingly being delegated to AI agents. This enables rapid iteration and experimentation, especially for startups and teams working with limited resources. However, complex development tasks — including crafting API routes, ensuring secure authentication, and implementing database operations — often require close supervision by experienced developers to ensure robustness and security.

Rigorous Testing and Optimization Needed

As no-coders, low-coders, and agentic AI continue to reshape contemporary software development, rigorous testing and source code optimization become even more critical. With AI tools generating substantial portions of code, the risk of introducing vulnerabilities or inefficiencies increases. Automated testing suites, static code analysis tools, and human oversight are essential to maintaining code quality and ensuring long-term stability.

This is an exposure for pure no-coder projects which has not gone unnoticed in the developer community. Speaking on X, David from Made Responsively commented:

“How do you feel about the risks around security and the other aspects of the app that could spiral and become costly if something goes wrong? How are you managing those? I do worry for people trying to build production apps.”

The challenge for development teams will be balancing speed and innovation with security and scalability. Inadequate testing and reliance on AI-generated code without proper validation can lead to costly issues down the road, from broken systems to security breaches.

How Role of Senior Developers Might Evolve

Arguably, this shift might result in considerable evolution of the role of senior developers who may operate more like technical architects or senior project managers who supervise and orchestrate the work of no-coders, low-coders, and agentic AI. These senior developers will be responsible for defining system architecture, ensuring best practices, and maintaining high-quality code standards.

• Supervision of AI Outputs: Senior developers will review and refine AI-generated code to ensure it meets the project’s requirements and aligns with industry standards.
• Oversight of No-Coders and Low-Coders: While no-coders may handle simpler development tasks, senior developers will guide them on complex integrations, scalability considerations, and compliance with security protocols.
• Focus on Testing and Validation: Senior developers will emphasize automated testing, continuous integration, and rigorous validation to mitigate risks posed by AI-generated code and ensure robust performance.

This shift redefines software development as a collaborative process, where no-coders, low-coders, AI agents, and pro-coders each play a critical role. Senior developers, acting as technical architects, will ensure these diverse contributors align to deliver cohesive, secure, and scalable software solutions.

The Future: A Hybrid “Augmentation” Model?

As software development evolves, the integration of agentic AI and no-code approaches opens new opportunities and challenges. Low-risk tasks can increasingly be delegated to AI, while complex and high-stakes development work requires the expertise of seasoned professionals.

For senior developers, the future lies in embracing this change, taking on roles as architects who guide diverse contributors and maintain the rigor needed for successful projects. In a world where speed and innovation often take precedence, their expertise will remain crucial to navigating the challenges of security, scalability, and quality in software development. The orchestration of AI, no-coders, and professional developers into unified teams could redefine the industry, enabling a future where creativity and efficiency coexist.