Bengaluru: AI tools have increased developer productivity by 30% on daily tasks. Many tech companies are actively investigating ways to use Genai tools to further improve developer efficiency.Stack Overflow CEO Prashant Chandrasekar believes AI is releasing developers for more meaningful work. “From our perspective, AI agents are not going to replace developers. They focus on and unlock higher-order tasks (creative, strategic or architectural work). The best agent AI tools help developers learn new technologies and make a greater impact,” he said.According to independent engineers, researchers and hackers, TheJesh GN, AI agents have led programmers to get business concepts and to more efficient code writing. “It helps to identify the logic behind your code. It helps to identify the business case for the line of code and adjust accordingly,” he said.Generation AI is popular among developers as a comprehensive solution. “To explain the problem, unlike Google searches, which require you to dig into information, you get the best results possible. You can ask your agent to code for a specific feature,” said Sujit Sharma, senior director of software engineering management at ServiceNow.These tools are quickly gaining popularity among developers and offer a more comprehensive solution. Sharma said his team is increasingly dependent on AI agents, rather than understanding business processes. These agents generate code overviews and streamline the development process further.Beyond coding, AI tools also take over routine and operational tasks. Bebi Negi, a senior lead data scientist at Happest Minds, uses the generated AI to generate reports each week and manage permissions. “Currently, these tools handle 10% to 20% of tasks and free up similar parts of my time by eliminating repetitive tasks,” she points out. For developers, AI automates traditional manual tasks, such as creating test cases.AI has proven to be particularly useful for senior developers overseeing junior teams. “genai is very beginner friendly. Most fresh people struggle with writing the right code, but AI can generate functional code to get the job done,” says Thejesh. However, he warns that beginners may not fully understand the reasons behind AI-generated code. He says that a deeper understanding of programming logic still requires practical experience. AI has also emerged as a quality assurance and management tool. Arindam Ray, vice-chairman of Maveric Systems, which leads the company's North American engagement, emphasizes that most AI agents are still in the pilot phase. “They haven't taken over technology jobs yet. Now it's primarily about increasing internal productivity,” he says.Chhavi Sharma, a product manager and anitab.org India community member, uses Genai for large-scale data analysis. According to her, success in AI depends on creating accurate prompts. The evolution of agent workflows leads to smarter orchestration throughout the development lifecycle. Jitendra Dulhani, manager and developer at Deloitte India, explains how agents can understand their role within currently complex tasks and adjust their own adjustments. “For example, in a migration, one agent can identify the source and target language, create a detailed migration plan, and delegate tasks to other agents. They handle the actual migration and validate another agent. The entire orchestration is becoming more dynamic and intelligent.”
