AI coding tools speed the sprint from idea to working demo

Developers across the industry are increasingly using generative AI tools to accelerate early coding tasks that once required hours of reading documentation or assembling boilerplate code. About 84% of developers say they already use or plan to use AI tools in their development workflow, according to a developer survey compiled by Panto. The tools range from standalone chat systems to assistants embedded directly inside development environments.

IBM Bob is an AI software development partner designed to work within a developer’s coding environment, scanning documentation, reviewing code, flagging potential issues and helping generate or refine software based on a developer’s intent, project repository and security requirements. At Think 2026, IBM Chairman and CEO Arvind Krishna illustrated the offering, now generally available, plainly. “Bob is not just a coding assistant,” he said. “When we say software development, we mean architecture, planning, code generation, testing, security.”

Ash Minhas, a Technical Content Manager and AI Advocate at IBM, said Bob has recently become part of his daily workflow because it helps him assemble technical demonstrations and prototype applications more quickly.

AI coding tools can write software faster, but enterprise development still gets bogged down by sprawling systems, legacy code and security headaches. IBM says its AI coding agent, Bob, is meant to tackle that mess directly, helping developers coordinate changes across everything from Java apps to aging COBOL systems. Inside IBM, one developer described Bob as less of a chatbot and more like an extra engineer sitting beside the team, helping modernize and secure code across the entire software pipeline.

“I am using it to help me make demo applications and technical prototypes,” he told IBM Think in an interview.

Prototyping and experimentation rank among the most common uses for AI coding tools, according to developer surveys reported by DevOps.com. GitHub has reported that about 46% of the code in files with Copilot enabled is generated by the tool’s suggestions.

Minhas said the assistant allows him to skip much of the traditional preliminary research that once slowed early development work. “Rather than me spending a lot of upfront time doing research or analysis, I can get it to scan documentation and specifications and let me just get going quickly so I can get to prototype quicker,” he said.

Minhas said the shift changes how he approaches new ideas. Rather than investing significant time upfront determining whether an idea is worth building, he can begin testing concepts sooner and refine them as he works.

Even so, Minhas stressed that as projects move toward completion, human expertise still matters.

“I think that getting from 0–30 is super easy,” he said, adding that progress becomes more iterative as the code becomes more complex. “30–80 [takes] a little more back and forth with prompting.” But the final stage of development still requires careful human oversight, Minhas said.

“The last 20% requires me to look at code and either specify more accurate prompts, with the risk of some of the 80% being undone by mistake, or hand-code myself,” he said. For Minhas, Bob is not meant to replace the role of a software engineer but instead serve as a helpful partner to take on more menial, tedious tasks. “It’s a time saver,” he added.