AI is dominating the conversation like never before – and often with inflated expectations. The market is full of promises that sound too good to be true. At Huld, instead of chasing AI hype, the focus is on practical application. AI has become a day-to-day tool in the tech company’s operations.
AI-assisted testing has become a core method at Huld for improving the quality and efficiency of software development. In well-defined problem areas, AI can support testing and validation, saving both time and money. Often it produces results that are more precise than what a human alone could achieve.
“With AI, we can analyze test coverage or generate harmonized documentation in seconds – tasks that would take hours for a human. But AI doesn’t understand context, empathy, or accountability. That’s why humans lead, and AI assists,” says Niko Rantalainen, Quality Specialist at Huld.
In Huld’s teams, AI already functions as a digital member of the development team. It analyzes test coverage, reviews code, suggests improvements, and initiates discussions. AI-assisted reviews are part of everyday life for developers, but when it comes to code review feedback, the human touch is still valued. Encouragement and collaborative problem-solving are especially important for the new generation of software developers entering the field.
“What matters isn’t what AI can do, but how wisely we can use it. AI’s greatest strength is speed and repeatability – and the greatest risk is overestimating its capabilities,” Rantalainen notes.
AI-powered coding and prompting open up new ways to build solutions quickly. However, a high-quality outcome still requires a human who understands the bigger picture. This isn’t about developers disappearing, but about the nature of their work evolving.
Rantalainen encourages companies to approach AI from a practical standpoint. Instead of chasing grand visions, it’s more effective to focus on small, concrete steps: one testing phase, one code review, and one documentation process.
“There’s no point in building AI solutions just for the sake of using AI. The best way to begin is by gaining hands-on experience: see what works, how well, and how reliable the outcome is.”