Systems | Development | Analytics | API | Testing

Chatbots have quickly moved from novelty to necessity. With over 987 million users and platforms like ChatGPT receiving more than 4.6 billion monthly visits, chatbots are now core to how people interact with digital products.

As AI models become commoditized, the conversation is shifting from building smarter models to building data infrastructure that turns models into real business value. Enterprises are accelerating their adoption of agentic AI—systems that don’t just predict but plan, decide, and act autonomously—across their software and operations.

More and more businesses are now starting to realize the importance of having a mobile app developed to boost their business and increase customer engagement. There is a good reason to develop a mobile app and hire a mobile app developer to do this. Why? 2017 was a historic year because for the first time mobile internet use overtook desktop searches. Many studies also show that more and more people are using mobile apps to access the internet rather than their web browser.

AI is no longer a fringe experiment: it’s a mainstream mandate. But with that shift comes a new kind of pressure: to act quickly, to appear modern, to bolt on something “intelligent” before someone else does. For many teams, this leads to reactive choices. Features get prioritized because they sound impressive, not because they solve a real user problem. Familiar interfaces get copied instead of questioned.

The idea of using an AI like GPT-5 or any LLM based tool to generate SQL from natural language sounds like a productivity goldmine. Ask the AI a question, and it automatically writes and executes the perfect query. Insight on demand. No SQL expertise needed. But beneath this automation lies a serious threat. Giving AI systems free rein to generate and run SQL against your production database is not just risky—it could be catastrophic.