Generative AI (GenAI) is rapidly changing the landscape of software development. And we at Ascendion are at the forefront of this revolution, by using GenAI to upskill Ascenders and deliver superior results for clients. The journey so far has been exciting with new learning every day. As I look at our first year of working with a GenAI trained force, here are my key takeaways:
Learning from the ground up
Creating a GenAI skilled workforce requires understanding of their personas. Firstly, we discovered GenAI usage varies depending on the role. For instance, we developed “experimental pods,” with folks with varying levels of expertise. This led to the development of persona-based use cases became primal, where GenAI tools are tailored to specific developer needs.
Secondly, the importance of high-quality data became evident. “Garbage in, Garbage out” applies to GenAI as well – clean data is essential for accurate and reliable results. Finally, it is crucial to understand the need for a cultural shift. GenAI isn’t just a new tool; it represents a whole new way of approaching software development. We had to help people understand that to work with GenAI, we must rewire the way in which we operate.
When working with clients, we take a similar approach: Rewire your software ecosystem (people, skills, and systems); clean data and choosing the right use cases aligned to the persona.
Digital Ascender, our GenAI tool was developed keeping these in mind. By empowering how our engineers work with GenAI, we also were able to develop a tool that makes sense for our clients.
What’s Working: Boosting efficiency and quality
Ascendion’s GenAI implementation has yielded impressive results. The Ascendion engineering experts working on A.AVA+ platform team saw a significant boost in efficiency with the introduction of GenAI-powered unit test case generation (UTCG). For ex, engineers who code using Python and had to test a UTC with J-unit or C-sharp, saved as much as 45% in time and improved code quality and reduced defect leakage. GenAI further helps engineers generate better use cases leading to better problem solving.
Ascendion’s Digital Ascender (DA), a GenAI-powered tool for generating code solutions, proved invaluable for developers by providing multiple options and clear logic explanations. With DA and A.AVA+, we have accelerated development processes while maintaining high-quality outputs.
After months of honing our GenAI platform, we are now delivering solutions with GenAI-powered codebase.
GenAI centric solutions are driven by GenAI, making the entire work complementary work ecosystem. This in turn impacts speed to market, tremendously improves product quality, and most importantly, reduces technical debt!
Impact on Ascenders and clients: A transformation in the making
We are at the cusp of complete transformation on how we deliver engineering solutions. The impact of GenAI extends beyond internal efficiency gains. It’s transforming the entire software development ecosystem, from initial client requests to final delivery. Clients are becoming increasingly aware of GenAI’s potential and are starting to integrate it into their projects. For ex, from a simple proposal to actual implementation, GenAI plays a part in every step of entire life cycle chain.
This necessitates a significant upskilling effort for both Ascenders and our clients. Ascendion is heavily invested in equipping our employees with the necessary skills, particularly in “prompt engineering” – the art of crafting optimal prompts to maximize GenAI output quality. This is where we are focused and heavily investing.
Our training includes a new course developed in collaboration with Cognixia, an Ascendion company, specializes in digital training and organizational DNA development. This is a customized program based on skill levels.
For clients, Digital Ascender & AVA+ are not restrictive platforms – they are architected with high modularity that makes plug and play possible at every level. Be it explorative phase, or experimental in the current or futuristic models, DA and A.AVA+ models are equipped to fit right in.
DA is architected in such a way that it’s persona oriented. That’s our specialty. DA will complement any existing product or platform and complement it. For ex, DA’s Michealangelo studio can create usable coded wireframes from simple drawings on a paper or Figma stencils.
Challenges to address
Ensuring that engineers unlearn, rewire, and get accustomed to the new ways of working is our priority. It’s a task to ensure that we are consciously looking at GenAI adoption at every phase in SDLC, be it for innovation or BAU execution.
Client considerations: Data, selection, and ethics
Clients need to understand three main aspects while embracing GenAI:
- Data readiness – data that is clean and of high-quality determines success
- Choose the right use cases that are best solved using GenAI
- Hype cycle will be around for a few years – understanding where they need to improve is essential, rather than one-size fits all approach
For ex, some problems can be solved through automation, some through Machine Learning algorithms, some through simple platform modernization. Clients need to understand that not everything requires a GenAI solution.
Ascendion works closely with clients to identify the optimal applications of GenAI, ensuring they leverage its capabilities effectively.
Security and ethics are also critical considerations. Understanding which data to use with specific generative AI models (is it proprietary, is it safe to feed data etc.), and language that is fed is vital. Ascendion has robust policies and practices in place to ensure ethical and compliant GenAI usage.
We train Ascenders to be cognizant of these ethical aspects both within our framework of operations and the client’s.
The art of possibilities: Exploring a new frontier
Ascendion’s GenAI journey is just getting started. We are constantly exploring new possibilities and applications. The focus is not on the specific models themselves, but on the art of prompt engineering and invoking any models as the situation demands. This empowers developers to unlock GenAI’s full potential. Challenges remain, but the potential benefits are undeniable. “We are currently in – well versed with art of possibilities – and exploring newer, farther frontiers.”
