Head of Application Development , Synechron
Artificial Intelligence (AI) is changing the way we build user interfaces.
It’s improving the user experience by creating more personalized solutions, and making codebase faster, safer and more accessible. AI can find and fix errors, ensure accessibility standards, and streamline performance. This leads to faster applications with fewer errors – enabling developers to spend more time building features that solve real problems. And, with AI handling the initial coding and scanning for errors, humans can spend vital time on the oversight essential for the development of a fully functional product.
Now, as the next step in AI, generative AI (GenAI) is about to deliver even better user interfaces.
There are a number of terms we should all know if we’re planning to use GenAI tools:
In terms of tools, there are a few that can assist developers with GenAI right now (it's important to mention that more tools may become available as the industry develops):
Now that we know the technologies and tools teams can utilize, we can start talking about what is practically possible with Generative AI.
GenAI can create a more engaging and relevant user experience by suggesting pertinent content or product recommendations, based on user and company data. Tools like GPT can analyze text inputs and user data, remember conversation and generate predictions, based on previous actions or preference. For instance, companies can use an AI travel assistant that will remember past trips, places, restaurants – and even transport preferences like preferring taxis to Ubers. Now, with these technologies, teams can build more engaging applications with direct access to the power of AI.
Rapid prototyping enables faster development cycles – and one area where new AI models will accelerate development is during prototyping. These AI models can help with the heavy lifting of starting a new project or using a new programming language or library. With advanced AI models, such OpenAI's GPT-3 and Codeium, teams can quickly build prototypes by describing the models that they would like to create, which programmers can then review and edit – for example, building forms, a responsive CSS grid layout, or translating Angular code into React. The newest development of GTP, in terms of Vision recognition (aka GPT-4Vision), will even allow the generation of lines of code by uploading a sketch of a UI.
Another area where Generative AI is improving applications is in helping teams ship cleaner and safer code. Tools like Copilot can already suggest code or generate unit tests for your code. However, more powerful tools like DiffBlue can analyze the code base (currently only supporting Java) and write tests autonomously. Other tools like Copilot and Amazon CodeWhisperer can also assist in generating tests or code improvements.
These AI models will also assist with complex areas such as accessibility and security, by scanning code, suggesting changes, and writing a better version of a piece of code. These tools can leverage all the good accessibility best practices covered by WCAG principles or security vulnerabilities outlined by the Open Web Application Security Project (OWASP).
There are a couple of areas where AI can assist developers, and one of them is in improving the overall Developer Experience (DX), which can ultimately impact how quickly a team can deliver code. One such area is documentation. AI can automatically generate documentation, summarizing the UI components, JS functions, CSS classes, data schemas and APIs used, in a fraction of the time it would take for a team of people to do it manually. This allows teams to spend less time writing documentation and more time building features.
Another indirect benefit of GenAI on how we build front-end applications is around learning. All these new technologies and tools help developers improve their coding skills. Now you can learn faster by creating your own learning assistant, using tools like ChatGPT or Bard and clever prompting, for instance: “You are a learning assistant. Based on the pareto principle, explain Kubernetes.” Learning platforms can build customized learning paths, project-based learning, interactive examples and automated quizzing, based on the topic the developer is learning. AI-power learning is going to be more engaging, effective and help developers stay up to date with all the latest trends.
Generative AI is changing the way we develop front end apps, empowering developers with enhanced productivity, creativity and problem-solving abilities. It will continue to give dev teams the power to build whatever they envision. Previously only accessible to large tech companies, these AI tools are now available to any team, enabling startups and enterprises alike. GenAI can uplift developers by automating repetitive tasks so they can focus on more complex challenges.
At Synechron, we're already helping teams to leverage the power of generative AI. This includes GenAI model validation that compares multiple AI models, and a GenAI tool that uses a database to source solutions and responses for report generation – both of which save significant time and resources.
Contact us to find out more about how we can help your business.