A few years ago, building a software feature took weeks. Today, a team can ask an AI tool to write the requirement, produce the code and prepare the test cases in a single afternoon. The work moves faster than ever. But one question has become harder to answer. If AI built it, who checked it?
Aakash Yadav has built his career around that question. The 29-year-old from Mumbai works with Testriq QA Lab and Cinute Infomedia, where he contributes across quality engineering, business growth, technology strategy, client partnerships and digital initiatives.
He began in software quality, working close to applications, requirements, test scenarios, development teams and the people who actually used the products. It was there that he learned a lesson he still works by. Quality is not only about finding defects. It is about asking the right questions before anyone else does. What could go wrong? Are we solving the right problem? What are we assuming? Will this work for the real user?
Those questions travelled with him as his responsibilities grew. He moved into QA leadership, and then into client communication, technology discussions, pre-sales, partnerships and solution planning. Sitting across the table from many different businesses taught him that a good digital product is never the work of one department. Development, quality, business strategy, customer experience and growth have to move together.
Today he works on both sides of that table. On the quality side, he leads and contributes to product validation, testing strategy, release readiness, automation, performance, security, accessibility and software reliability. On the business side, he works with founders, companies, agencies and technology partners to understand their goals and shape practical solutions around their real challenges.
This gives him two ways of looking at every project. The quality professional in him asks whether it will work reliably and what can break. The business professional asks whether it solves a genuine problem, whether users will value it and whether it supports the client’s growth.
It is this double view that shapes his thinking on AI. Aakash sees AI as a real opportunity for software teams to work faster, be more productive and try new ideas. But he also sees a gap that speed has opened. “If AI writes the requirement, generates the code, and also generates the tests, who is challenging the assumptions?” he asks.
For him, this is not only a technical worry. It is a question of trust. When AI shapes every stage of the work, the same blind spots can pass through every stage unnoticed. That is why he believes independent thinking and validation matter more now, not less.
He also points out that products built with AI need to be tested differently. Traditional software is checked to see whether each feature works as expected. An AI-powered product can give a confident answer that is simply wrong. It can invent information. It can be misled by a cleverly written prompt, put private data at risk, or respond differently to the same question at different times. Checking that the features work is no longer enough. Teams also have to ask whether the product is accurate, secure, consistent and still under sensible human oversight.
But Aakash is quick to add that even a product that passes every test can still fall short. A technically working product is not necessarily a successful one. It has to solve the right business problem, give users something they genuinely value and earn their trust over time. This is where his work in quality and his work in business strategy meet.
He carries the same belief into his partnerships. Through Testriq QA Lab and Cinute Infomedia, he regularly speaks with founders, businesses, agencies and technology teams about software quality, development, AI solutions and digital growth. He believes the best technology relationships do not begin with a sales pitch. They begin with understanding the problem. Only then does he bring the right technology and quality solution around it.
None of this makes him wary of AI. He sees it as a tool that should support people, not replace their thinking. AI can draft, suggest and speed things up, he says, but responsible use still depends on human judgement, independent validation and someone willing to ask the difficult question.
His long-term goal is to keep building expertise where quality engineering, AI, technology, business growth and partnerships meet, and to help businesses build products that are not just faster to develop, but also reliable, scalable and useful.
For Aakash, the work has never been only about finding bugs. It is about knowing whether technology works, whether people can trust it and whether it truly helps the business it was built for.