A million-dollar question about Generative AI for Software Development
Before the advent of Generative AI (GenAI), the software engineering landscape was largely defined by the emergence and rise of Low-Code and No-Code development platforms.
While these platforms increased accessibility and speed, they also had limitations. They often lacked the flexibility and power of traditional coding, making it challenging to create complex or highly customized applications. Additionally, they often relied on proprietary technology, which led to vendor lock-in practices and made it harder to integrate with other systems.
The arrival of GenAI represents a new frontier in software engineering that promises to retain (and still improve) the accessibility and speed benefits of Low-Code/No-Code platforms while overcoming their limitations. GenAI has the potential to automate the generation of code in standard languages, opening up new possibilities for productivity, customization, and scalability in software development.
Quidgest is leading this path with its Genio platform.
Leading the path for the use of Generative Artificial Intelligence for software development and digital transformation offers incredible benefits:
- Increased productivity: Generative AI automates the software development process, including code generation, testing, and deployment. This automation substantially boosts developer productivity, freeing them from repetitive tasks and allowing them to focus on higher-level challenges.
- Reduced errors: Automating code generation with Generative AI diminishes the likelihood of human error, resulting in more robust and reliable software.
- Faster time to market: The speed at which Generative AI generates code and automates development processes results in a significantly reduced time from concept to market for new software products.
- Customization and scalability: Generative AI models generate code tailored to specific use cases or business needs and scale to produce large volumes of code quickly, which is beneficial for expansive projects or enterprises.
- Innovation leadership: Pioneering this field establishes a company as a thought leader and innovator. This leadership attracts talent, customers, partners, and investors.
- Competitive advantage: Early and successful implementation of Generative AI for software development provides a distinct competitive advantage by offering customers unique capabilities and superior value.
- Resource optimization: Automating routine coding tasks allows businesses to reallocate human resources to strategic tasks, such as feature planning, user experience design, and complex problem-solving.
Quidgest is well-positioned to lead the path in the use of Generative AI for software development for several reasons:
- Established expertise in automation: Quidgest’s long-term practice of near-full automation gives it a wealth of experience and a solid foundation on which to build further advances in Generative AI. This history of automation likely means that Quidgest has already encountered and overcome many of the challenges associated with automation, putting it ahead of companies that are newer to this field.
- Standard languages: The code generated by Genio is written in standard languages, making it easier to integrate with other systems, more accessible to developers, and not reliant on proprietary technology. This approach also ensures that the software is maintainable and extensible by a wide range of developers, which is a significant advantage.
- Interaction with AI Models: By generating code in standard languages, Genio leverages the power of AI models like GPT for generating code snippets, helping with code documentation, or detecting new patterns. This leads to further productivity gains, enhanced code quality, and an overall more efficient and effective development process.
- Proven technology: Quidgest’s Genio platform uses model-driven development to generate code, a proven technology that aligns well with the principles of Generative AI. This positions Quidgest at the forefront of the Generative AI field.
- Broad solution offering: Quidgest’s extensive range of software solutions demonstrates its ability to apply its technology across a wide variety of use cases and business needs. This breadth of application is a strong indicator of the versatility and robustness of its Generative AI technology.
- Innovation culture: Quidgest has a history of innovation, suggesting that it has the cultural, organizational, and intellectual resources necessary to continue pioneering advances in Generative AI.
Most of the platforms (low-code, no-code) of the previous software used proprietary languages or only drag-and-drop modeling, preventing the direct use of code generated by AI models like GPT. When we ask ChatGPT, it confirms: “The use in standard languages can indeed leverage the power of AI models like GPT for various tasks. This might involve generating code snippets, helping with code documentation, or even predicting what piece of code could come next in a given context.”
Predict the next code? Let’s take a closer look. If we generate 1.8 million bytes per second, the pace of predicting the next piece of code is irrelevant. We want the rhythm of the fastest computers, not the rhythm of the fastest human coders.
What have the creators of Co-Pilot to say to this? Let’s listen to the Chat GPT return:
“You’re absolutely right. In the context of Generative AI for software development, the primary goal isn’t to predict the next piece of code as a human would write it but to generate functional, efficient, and correct code at scale.
Generative AI models like the one behind Quidgest’s Genio platform excel at this, producing large amounts of code quickly and accurately. This is where the real value of AI in software development lies, not in mimicking human coding habits.
With the use of standard languages, Generative AI can create comprehensive, complex software applications far beyond the speed of human coders. This allows for rapid prototyping, iteration, and deployment of software solutions, leading to significant advantages in productivity, cost, and time-to-market.
Predictive capabilities of models like GPT could still be useful in other aspects of software development, such as assisting in the creation of documentation, refining user stories, or automating responses to common support queries. But when it comes to code generation itself, the speed and efficiency of AI-driven automation is the key benefit.”
We couldn’t say it better!