Enter Bob, IBM’s Friendly AI Coding Assistant

BOSTON — Meet Bob, a supportive and collaborative AI coding helper that automates much of the software development process while leaving the human in charge.

“It’s Bob the Builder,” said Venkat Venkatesan, senior manager in the tax technology and transformation practice at EY, referring to the animated British TV show featuring a builder and his helpful talking machines. “When I first started using Bob, I knew it was not a simple coding assistant.”

Released about a week before the start of IBM’s Think 2026 user conference, Bob quickly became a centerpiece of the event, appearing in panels, presentations and the opening keynote by IBM chairman and CEO Arvind Krishna.

An Agentic Approach to Coding

Bob is positioned as IBM’s answer to leading coding agents such as Claude Code from Anthropic and Codex from OpenAI. Notably, Claude is also one of the AI models that powers Bob.

Bob routes coding tasks to different models depending on the job, including Claude, open source models from France-based AI vendor Mistral, and Granite, IBM’s own family of lightweight models.

Venkatesan and her team at EY, who are building an extensive global tax platform, used Bob in private beta for several months before IBM made it generally available late last month and introduced it more broadly at Think 2026.

“I would call it an agent,” Venkatesan said. “It helps you during every phrase. It’s like you’re working with it.”

She compared the experience to pair programming, a traditional practice in which two developers share a single workstation to collaboratively write code.

“Bob is like that. It’s like a digital worker. You both work together,” Venkatesan said.

AI at the Core of IBM’s Strategy

Bob was one of several AI announcements at the conference. Krishna emphasized that AI sits at the core of IBM’s strategy, noting that the 115-year-old company has applied AI and automation across its operations and realized $4 billion in productivity gains.

“As you talk to different clients, as you talk to different geographies and industry sectors, this is the big change,” Krishna said. “It’s no longer about how much your budget is. The question comes down to, how deeply is AI embedded in your business processes?”

IBM also announced the release of 150 prebuilt agents in Watsonx Orchestrate for hybrid cloud and mainframe environments, a major expansion of the Concert AIOps platform, and a new generation of the Watsonx Orchestrate agent management system. The company highlighted an integration between Watsonx and Confluent’s streaming data platform following its $11 billion acquisition of Confluent.

Industry observers say IBM’s strategy of extending its generative AI offerings — led by Granite and Watsonx models — into hybrid cloud and mainframes, while maintaining a multi-model, multi-cloud approach, aligns with the needs of its enterprise customer base.

IBM has longstanding relationships with large financial institutions and other highly regulated organizations that prioritize data privacy and security, particularly on mainframes.

Sanjeev Mohan, founder and analyst at SanjMo, noted that mainframes remain a profit center for IBM.

“If you’re a financial services company or an agricultural company, and for 70% of global transactions, everything still flows through mainframes,” Mohan said. “Mainframes are a growing business, not a dying business.”

Mohan added that IBM’s decision not to compete head-on with the largest generative AI vendors, but instead to focus on smaller, lighter-weight models for niche enterprise needs, is a sound strategy.

“What IBM is saying is that, with so much competition, ‘If we focus on very niche areas where their clients are, then we can cut a swath based on where the need is rather than create a generic model,’” he said.

Enterprise Adoption and Multi-Model Strategies

IBM customer SEI, a Pennsylvania-based financial services company, is working with IBM Consulting to design AI agents for cloud-based operations across multiple business processes, including replacing legacy optical character recognition document systems. SEI’s accounting division continues to run on IBM mainframes.

“They’re coming in to really help us reexamine our workflows bottom-up and reengineer those workflows and apply AI where applicable and potentially build out those agents,” said Zachary Womack, CTO at SEI. “In the future, operations goes from banging away on applications to orchestrating agents.”

The technology stack could include Watsonx models and agents, as well as Claude or OpenAI models.

“We definitely are multi-model in our approach,” Womack said. “All that will be part of the harness we are continuing to build out.”

Return on investment remains an open question.

“It’s still early days. The question of ROI is a good one,” Womack said. “I think people are still evaluating the promise that’s there.”

AI Beyond the Enterprise

Retired tennis champion Andre Agassi also appeared at the conference to discuss his Watsonx-powered racket sports digital coaching mobile app, set for release later this year.

Agassi said that during his playing career, preparation helped him overcome physical limitations. Now, he sees AI as a way to enhance performance in new ways.

“And now, all of a sudden, when you start seeing the capability of an AI, my partnership with IBM, you start to realize … we have multiple ways to use this to enhance this game in a beautiful way, and take it deep in the future,” he said.