Anil Khanna on Cracking the Complexity of Modern AI-Driven Product Engineering

The future of product engineering is hands down AI-powered, but humans still call the shots.

Anil Khanna, VP Technology at Nitor Infotech, takes us inside the new playbook for building high-impact products. He talks about blending agile, spec-driven, AI-enhanced workflows with indispensable human expertise and judgment to turn complex challenges into scalable customer-first solutions.

Drawing from your overall experience, which technologies and practices have most influenced your approach to software product engineering at Nitor Infotech?

At Nitor Infotech, an Ascendion company, product engineering is one of our core strengths and offerings. This space has evolved meaningfully over the years for us. We’ve gradually transitioned from a traditional code-first approach (the legacy approach) to a more thoughtful, spec-driven development model.

This shift has been driven by artificial intelligence (AI) as it continually reshapes business processes, development workflows, and coding practices. Even though AI is a crucial tool for today's survival, the fundamental principles of programming and development will remain essential.

Enterprise software often comes with complexity and bottlenecks. How has Nitor Infotech cracked these challenges to deliver solutions that scale seamlessly?

Well, yes, every engagement steps up with its own set of complexities and bottlenecks. These often span technological challenges, business process limitations, budget constraints, and most importantly, market fluctuations that influence outcomes.

To address these roadblocks, keeping ROI at the center has always helped us steer our customer engagements in the right direction. That is, instead of sequentially moving through implementation stages, we go beyond. We choose to position ourselves as strategic partners for our customers to navigate throughout their product journey.

This allows us to articulate the decisions we make to address complex issues clearly. After all, an informed decision tends to deliver far more value than momentary tactical brilliance.

Nitor Infotech embeds AI/ML into its service offerings. How do you blend AI-driven automation with human expertise to truly optimize development?

We were among the early adopters of integrating AI into product engineering, spanning both Engineering^AI and Business^AI. As AI is inherently probabilistic, we recognized early on that human involvement would continue to play a crucial role.

There are several points in the workflow where AI generates intermediate outputs. These outputs are reviewed or validated by humans or our expert teams, as they are the final decision makers. For routine or repetitive tasks, this involvement may be minimal. However, as the complexity of the task increases, the need for human judgment and domain expertise becomes significantly more pronounced.

This approach is what enables us to leverage AI effectively without compromising on quality or intent.

From your vantage point, which approaches have proven most effective in driving technological excellence at Nitor Infotech?

Over the years, we’ve realized that tech excellence isn’t a single sprint – it's an ongoing marathon or journey. Our growth has largely been driven by two parallel efforts:

a) continuously improving and deepening what we already know

b) proactively investing in emerging technologies to understand nuances before they become the norm

To be honest, our customers often rely on us to help them navigate through their product development process, and we make it a priority to support them as capable, informed, and trusted partners on the technology front. This kind of empowerment is one of the key reasons why our customers have continued their association with us for more than five years.

What’s your approach to shaping Nitor Infotech’s GenAI solutions so they create distinctive value for customers while strengthening your market position?

From what I’ve observed, there is no single templatized way of doing things. That is, every customer’s Gen AI trajectory looks a little different. Some are already quite mature and are exploring ways to build or fine-tune their LLMs, while others want to be sure their investment will deliver tangible results and returns that they expect.

Even as we keep our teams updated on the latest generative AI developments, we also understand that customers need to be convinced by the real value it offers.

So, during most of our engagements, we begin with a “Proof of Value” phase before heading into a full, business-wide rollout. Given the mixed results from past cloud migration efforts, some customers are understandably cautious. This influences their perspective on embarking on new initiatives with us.

How do you weave customer feedback into product development to ensure your solutions address client pain points with precision?

We partner with our customers rather than simply acting as “bodies” suppliers. This allows us to understand their product journey and technological stacks. We make sure this understanding is clearly reflected in the solutions we tailor and deliver.

Since modern-day businesses are constantly evolving, any kind of feedback we receive – whether it’s driven by market evolution or implementation details – is carefully evaluated, and any required iterations are made in full alignment with the customer.

It’s no one-shot wonder and no surprise that one of our core offerings, “Research as a Service (RaaS)”, stands tall among the top 3 search results on Google. This proves that our customers and the market consistently value us for our ability to think critically and tailor solutions that perfectly fit the desired requirements.

Do you have a moonshot vision for Nitor Infotech? How does it translate into tangible value for customers?

Our moonshot vision is clear – to position Nitor Infotech as one of the world’s most trusted and forward-thinking product development partners. After our integration with Ascendion in 2023, this vision is not just an aspiration but rather a reality that combines the strengths of both organizations.

With deep capabilities across UX research, product management, and engineering, we’re among the few players who invested early in building a truly end-to-end product development ecosystem.

For our customers, this translates into tangible value. If you ask how, well, they get a partner who can support them across the entire product development lifecycle. I’m talking straight from discovery and design to engineering, modernization, and scaling.

As Gen AI continues to mature at lightspeed, businesses are actively seeking partners who can not only understand tech but also apply it meaningfully and strategically to their product goals. And that’s where we excel and wish to continuously create greater impacts.

So, whether it’s a large-scale business transforming an existing product or a startup taking a breakthrough idea to market, our aim is simple: to be the partner they trust to turn their vision into reality.