AI agents boost developer productivity
Stack Overflow CEO Prashant Chandrasekar believes that AI is freeing up developers for more meaningful work. "From our perspective, AI agents don't replace developers. They free them up to focus on higher-order tasks—creative, strategic, or architectural work. The best agentic AI tools give developers back time and energy, helping them learn new technologies and make a greater impact," he said.
According to Thejesh G N, an independent technologist, researcher, and hacker, AI agents are helping programmers grasp business concepts, leading to more efficient code writing.
"It helps identify logic behind code. It helps us identify a business case of a line of code and tweak it accordingly," he said.
Generative AI has become popular amongst developers as a comprehensive solution. "Explain a problem and it fetches the best possible outcome unlike a Google search where we have to dig out information. One can ask the agent to write code for a particular functionality," Sujit Sharma, Senior Director, Software Engineering Management at ServiceNow, said.
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These tools are quickly becoming popular among developers, offering a more comprehensive solution. Sharma said that his team increasingly relies on AI agents instead of product managers to understand business processes. These agents generate code summaries, streamlining the development process further.
Beyond coding, AI tools are also taking over routine and operational tasks. Bebi Negi, Senior Lead Data Scientist at Happiest Minds, uses generative AI for generating weekly reports and managing access permissions.
"Currently, these tools handle 10% to 20% of tasks, freeing up a similar portion of my time by eliminating repetitive work," she notes. For developers, AI is automating traditionally manual tasks such as writing test cases.
AI is proving especially helpful for senior developers overseeing junior teams. "GenAI is extremely beginner-friendly. Most freshers struggle to write proper code, but with AI, they can generate functional code and get the job done," said Thejesh.
However, he cautions that beginners may not fully grasp the reasoning behind AI-generated code. A deeper understanding of programming logic, he says, still requires real-world experience.
AI is also emerging as a quality assurance and management tool. Arindam Ray, vice-president at Maveric Systems, who leads the company's North America engagements, emphasizes that most AI agent deployments are still in the pilot phase.
"They haven't taken over technology-related work yet. Right now, it's mainly about boosting 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 with AI hinges on crafting precise prompts. The evolution of agentic workflows is leading to smarter orchestration across the development lifecycle.
Jitendra Dulhani, a manager and developer at Deloitte India, explains how agents now understand their roles within complex tasks and can coordinate among themselves.
"For instance, in a migration case, one agent could identify the source and target languages, create a detailed migration plan, and delegate tasks to other agents—one handling the actual migration, another validating the output. The entire orchestration is becoming more dynamic and intelligent," he said.
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