Low-Code/No-Code + LLMs: How AI is Changing Software Development

No-code/low-code platforms have been around for a long time. They help democratize software development and give people without development experience a chance to try their luck in the tech world. And they have become increasingly popular lately. For example, Appian says that 84% of companies are already turning to low-code solutions to make their IT departments' jobs easier.

However, the evolution of software development did not end there. Large language models (LLMs) came into play. They simplified the processes even more: Now developers can generate code much faster and with less chance of human error.

It would seem that with such tools, software development should become incredibly fast and high-quality. But did it really happen? In this article, we will help you understand how AI-powered LCNC platforms influence the software development industry and where exactly these tools bring the most benefit.

Understanding Low-Code/No-Code Development

Low-code/no-code (LCNC) development is a type of software development that uses special platforms with drag-and-drop interfaces, pre-built templates, and ready-made layouts. With this approach, the use of manual coding is either reduced to a minimum (low-code) or disappears altogether (no-code). This allows even people without programming experience to create and release applications for various purposes.

Such an approach has plenty of benefits. With LCNC platforms, you can speed up the development and shorten your time to market. It’s especially useful if you want to create an MVP and/or a prototype. Also, LCNC platforms are cheaper than traditional development since they minimize the need for big development teams. And, as we already mentioned, these solutions enable business analysts, marketers, and other non-developers to build and modify apps if necessary.

The Role of LLMs in Software Development

A Large Language Model (LLM) is an AI solution that is designed to learn and understand human languages and generate human-like text. However, the possibilities of modern LLM aren’t limited by text only: They can generate images, videos, audio, and… Right, code. That’s why LLMs have become a popular tool among plenty of developers.

How can LLMs assist developers? Here are the key areas:

• Code generation: LLMs can generate code lines, snippets, or even full-scale scripts based on the context developers provide in prompts. It significantly reduces the coding time and provides faster time-to-market for businesses.

• Debugging: An LLM can check the manually written code for any mistakes, typos, and bugs and help developers fix them in time. 

• Code optimization: With the help of such models, developers can rewrite legacy code in more efficient and optimized ways.

• Automated documentation: A good model can generate comments and summaries to help developers write documentation faster.

• Skill enhancement: If a developer stumbles upon an unfamiliar piece of code or a new concept, they can ask an LLM for a quick and concise answer. They can also use an LLM as a sort of tutor to learn new programming languages and frameworks.

• Testing: LLMs can create unit tests and edge cases to facilitate the work of QA specialists.

How LLMs Enhance Low-Code/No-Code Platforms

Now let's get to the fun part: How LLM and LCNC solutions can work together to make the biggest contribution to software development.

• Natural language to code conversion: An LLM can convert plain English into functional code. Just like LCNC solutions, this feature reduces the barrier for non-developers and allows them to create applications without previous software development background.

• Automated workflow generation: LLMs can generate whole applications, features, and processes based on just text inputs. They can also suggest what blocks and components of your chosen low-code/no-code solution to use to get the most high-performing results.

• Smart debugging: LLMs will detect any issues in the workflow logic and suggest the best way to fix them.

• AI-powered recommendations: When you work with a low-code/no-code platform, AI can recommend suitable templates, layouts, and integration so you can create an app that meets all your business needs.

• Advanced customization: With the help of LLMs and their custom-generated formulas and queries, your team can bridge the gap between LCNC and traditional development and take the best from both approaches.

Key Use Cases of Low-Code/No-Code + LLMs

The combination of low-code/no-code platforms and large language models can unlock plenty of powerful use cases across industries. Here are some key applications:

Chatbots and virtual assistants

You can build LLM-based customer service chatbots and personal assistants that understand natural languages and provide fast, well-structured, and coherent responses. And LCNC platforms will help you do that with minimal coding.

Automated document processing

Since LLMs can read and understand huge volumes of data in no time, you can use them in your LCNC application to extract data from reports, invoices, contracts, emails, chats, and other sources to automate data entry.

Web and mobile development

LLM-powered tools like Bubble, Retool, and Webflow simplify UX/UI creation. Also, this approach will be suitable for prototyping and MVP building.

Data analytics and visualization

AI-driven no-code solutions enable data modeling and business intelligence. For example, you can use the LLM features to analyze customer feedback and then use the insights to improve your LCNC solution.

Personalized user engagement

You can generate personalized email campaigns, chat responses, and product recommendations for your no-code/low-code solution based on user data.

Workflow automation

Tasks like content generation or invoice processing can be automated with the help of LLMs, and then you can bring this automation to the no-code/low-code workflows.

Low-сode AI model deployment

This combination of tools can help you fine-tune and deploy AI models without deep ML expertise and integrate predictive models into business apps via no-code platforms.

Intelligent HR and recruitment

Apps built with LCNC platforms and powered by LLMs can provide automated resume screening, candidate matching, and interview scheduling.

Popular Tools and Platforms Combining LLMs and LCNC

The combination of these technologies is already on the market and is popular among developers and non-technical specialists. The most proven and reliable at the moment are:

Bubble

Bubble is a no-code platform founded in 2012 that helps users create web applications through an easy-to-use visual interface. Now this platform has an artificial intelligence integration that allows users to connect to OpenAI's APIs (ChatGPT, GPT-3, DALL·E 2, Whisper). With the help of these APIs, users can now build AI-powered applications that can come in handy for tasks like natural language understanding, automation, and image generation. 

Zapier AI

Zapier is an automation platform that connects various applications to streamline workflows. It was founded in 2011 and since then proved itself to be a valuable and efficient automation tool. With the introduction of AI features, Zapier’s users can now extract, summarize, and transform data via AI models from, for example, OpenAI and Anthropic. They allow for more intelligent automation so tasks like lead management and marketing campaigns can be monitored and handled more efficiently.

Retool and OutSystems

Retool and OutSystems are both low-code platforms designed to speed up software development.

Retool leverages AI models to help users with tasks like text generation, analysis, and classification. Also, the platform's "Ask AI" feature assists in writing, editing, and debugging queries. 

OutSystems’s artificial intelligence capabilities assist in generating functional software solutions quickly. The platform provides tools like AI suggestions and AI agents to facilitate natural language understanding within apps.

GitHub Copilot

GitHub Copilot, powered by OpenAI's Codex, is an AI-driven code completion tool that can autocomplete code and give function suggestions. Initially based on GPT-3, Copilot has evolved to support multiple models, including those from Anthropic and Google. This multi-model approach provides developers with better efficiency and accuracy. 

Microsoft Power Apps

Microsoft Power Apps is a low-code platform where users can build custom applications for their tasks. The integration of a next-generation AI copilot allows users to describe features they want to build in plain text, which the AI then translates into working applications. Such an approach makes software development more accessible for people with no tech background and simplifies the development process in general.

Conclusion

Both no-code/low-code solutions and LLMs play kind of the same role in software development—they democratize it and make it faster, more accessible, and more efficient. And the right combination of these tools doubles the benefits. With the help of large language models, LCNC platforms reach new heights and allow users to create software with even fewer doubts and concerns. Even though these tools can’t always provide the same customization and level of control as traditional development, LCNC platforms and LLMs still have their own place in the market.

If you want to build a top-tier software solution that your audience will adore, contact us! Yellow is ready to help you explore AI-powered LCNC platforms and experiment with AI-driven app development.