Hyther Nizam, President for the Middle East and Africa at Zoho explains how Generative AI complements low-code platforms by boosting application development with rapid solutions and scalability.
Generative AI (Gen AI) is revolutionizing the world of application development, empowering developers to generate quick fixes for repetitive tasks through large language models (LLMs). These systems are capable of processing vast amounts of data and are trained on billions of coding parameters, which has transformed and streamlined the app-building process.
In addition to Gen AI, low-code development platforms have also developed into go-to solutions for businesses seeking agility and speed in their software development life cycles. As the industry debates whether Gen AI can replace these platforms, the answer is a resounding no.
While Gen AI can easily generate specific code blocks based on your prompts, it lacks the human cognition to seamlessly integrate these snippets, understand the impact of component tweaks, or optimize the generated code. This is where low-code platforms shine, providing the necessary abstraction and control to deliver a truly comprehensive app-building experience.
The future is a synergy of low-code and Gen AI
Low-code platforms and Gen AI are intended to coexist and push the boundaries of application development. Imagine a user with no coding background opening a low-code platform and simply typing a text-based prompt to define their needs. The system would then use its code repository and suggest a starting point, data structures, connections, and other elements that a non-developer might overlook.
In the same way, Gen AI within low-code platforms allows both business users and pro-coders to feed in their application requirements. The platform’s internal guardrails can then validate the code based on the overall context and quality, creating a seamless collaboration between human and machine.
Choosing the right low-code platform
The key to unlocking the full potential of this synergy lies in selecting the right low-code platform. Look for one that boasts deep integration with Gen AI and has robust LLM capabilities. A disconnected approach to integrating Gen AI and low-code platforms could lead to subpar applications, compliance problems, and technical debt. It’s important to carefully consider several key factors to ensure successful and secure implementation:
1. Prioritizing platform maturity: It’s tempting to be drawn to low-code platforms solely based on their AI capabilities, but it’s essential to exercise caution. The technology behind Gen AI is still relatively new and evolving. Instead of focusing solely on AI features, businesses should prioritize choosing a mature low-code platform that offers a comprehensive suite of features to support diverse developer personas in building scalable, custom applications.
2. Ensuring privacy and security: Low-code platforms usually interact with a wide range of data, both within and outside the organization, depending on the application use case. Look for a low-code platform that prioritizes data privacy and security at its core and ensures that the same level of protection extends to all of its provisions, including the LLM-based features. This could include measures such as data encryption, access controls, and compliance with industry-specific regulations.
3. Maintaining compliance: Non-compliance can have severe consequences, from heavy fines to the loss of customer trust and business opportunities. When selecting a low-code platform with Gen AI capabilities, it’s essential to choose a vendor that complies with all major regulations in the regions where the platform will be used.
4. Establishing robust governance: As both business users and developers use low-code platforms to solve real-time business problems, having adequate governance measures in place is crucial. This becomes even more critical when introducing LLM-based capabilities, as users may start to incorporate foreign code blocks into the existing codebase. Effective governance measures could include version control, code review processes, and clear guidelines for incorporating Gen AI-generated code snippets. This ensures that the platform maintains a high level of code quality, security, and maintainability, even as the development team leverages the power of generative AI.
Embracing the future of application development
Many leading low-code platforms have started investing in developing and launching their own proprietary large language models (LLMs). This will give them greater control over the output generated by the generative AI capabilities they offer. Additionally, these platforms are deploying contextual, domain-specific LLMs to enable the creation of industry-tailored and use-case-driven applications at scale.
As low-code platforms continue to evolve, we can expect to see the emergence of proprietary LLMs and contextual domain-centric LLMs. These innovations will allow platforms to deliver applications tailored to specific industries and unique business needs more effectively than ever before.
As with any transformative technology, a cautious approach is advised. Start small, evaluate progress, and scale your adoption of the Gen AI-powered low-code platforms. This measured approach will ensure you harness the full power of this synergy, driving innovation and creating software solutions that meet the demands of tomorrow.
