Do you want to increase the software development process at your company and the quality of your output? Take a look at generative AI…
Does this sound like an infomercial from the 1980s?
Developers may boost and speed up their productivity by using generative AI without disclosing all of your company’s trade secrets, passwords, certificates, and IP addresses (more on that later).
Here are 10 quick use cases for AI throughout your company’s software development lifecycle (SDLC)—and these are probably just the very minimum!
Baseline Coding Guidelines
You can utilize generative AI to establish and document the coding standards that developers in your company should follow. These standards can be written in multiple languages, ensuring compliance with best practices and industry standards.
AI-Powered Coding Support
By the standards and best practices established by your organization, generative tools like CodePilot may now assist with activities like code creation, completion, code reviews, bug fixes, code refactoring, and code style checking (see point 1).
Generating Synthetic Data
Removing personally identifying information from test data might take time and effort. Still, engineers can utilize generative AI to produce synthetic data for your development and testing environments. Creating training data for your machine learning models is another extension of this.
UI and UX Design
You can rapidly create front-end application designs for your organization using tools like Midjourney, instead of spending weeks on the process.
Design Playbooks & Documentation
You can employ generative approaches to develop Wikis, How-To Guides (both in text and video formats), and knowledge base content. These resources can serve as valuable references for your technical teams during service interruptions. Or even while trying to quickly upskill new team members in the application landscape of your company.
Knowledge Sharing
You can record your Stand-Ups and meeting minutes using programs like Whisper (or even Microsoft Teams). Then, you can communicate them as part of your Scrum of Scrums or, more generally, as part of x-team delivery updates to gain insights into roadblocks and delays affecting product delivery schedules. When engineering teams seek strategies to prevent scheduling meeting paralysis, these updates may be provided in Teams or Slack channels!
Creation of User Stories
It might take a lot of time and effort to write user stories. However, an AI software development company in NYC may quickly develop a set of baseline criteria for epics, user stories, and tasks for engineers to follow using generative AI. While this will only satisfy some of your demands, particularly for common infrastructure parts, it will help create around 70% of the essential requirements.
Survey and feedback questions for the research
Generative artificial intelligence (AI) can generate research questions and feedback surveys regarding your products and customer demands. By tailoring them to specific demographics and audience requirements, you can ensure personalized insights that align with your analytical needs.
Developing Test Cases
The time and effort needed for human test case generation may be reduced by using generative AI to produce test cases automatically. Generic artificial intelligence (AI) can provide several test cases that span a range of situations and edge cases by analyzing code and comprehending its operation. Doing so can ensure full testing and possible problems may be found before release.
Engineered Robots
A: “Speak to Michelle; she is very knowledgeable about the Core Banking Platform.”
B: “Michelle retired 8 years ago!”
We’ve all been here. Institutional knowledge has left the company, and no one has kept the comments in your software up to date or updated the “How to” guides. Building Bots specifically trained on your organization’s data to provide natural language insights across your repositories, version control systems, knowledge management systems, and other data sets is now possible due to generative AI and, more specifically, Large Language Models.
It might not be easy to know where to go for documentation or who to contact regarding certain products and applications, particularly when beginning a new career. Therefore, organizations may employ generative AI bots to advise experienced and new engineers about whom and where to contact about certain coding difficulties and production performance concerns, for instance.
A few weeks ago, OpenAI presented a napkin sketch to its GPT-4 model and surprise!
We transformed the pen-based design into a functional, albeit basic, website. The potential of these models will continue to grow, and we can expect the emergence of AI-generated apps that are highly intricate, stateful, and distributed in the near future.
However, there was some controversy only last week when Samsung disclosed what seemed to be a data breach due to employing ChatGPT across their software engineering teams. Ironically, a prior restriction on utilizing ChatGPT had been removed only a few weeks before to stop similar data breaches. According to reports, staff used OpenAI’s simple access solution to exchange confidential source code for testing semiconductor equipment.
In the frequently asked questions (FAQ) section of the company’s website, OpenAI specifically instructs users not to reveal “any sensitive information in your conversations.” The AI powering the chatbot is trained using data that users directly supply. But workers everywhere seem blissfully oblivious to this; honestly, it has to stop.
Implementing generative AI throughout the SDLC can lead to intriguing productivity improvements. However, it is crucial to ensure the implementation follows best practices in order to safeguard your organization’s information security posture. Control and caution are essential.
Author Bio:
This is Aryan, I am a professional SEO Expert & Write for us technology blog and submit a guest post on different platforms- Technoohub provides a good opportunity for content writers to submit guest posts on our website. We frequently highlight and tend to showcase guests.
