BOSTON — Meet Bob, the 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, the global tax and consulting firm, affectionately referring to the well-known 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.”
You could say that Bob, released about a week before the start of IBM’s Think 2026 user conference, was the star of the show, popping up in panels and presentations and even the opening keynote by Arvind Krishna, the long-established tech vendor’s chairman and CEO.
In a way, Bob is IBM’s answer to Claude Code, the widely used coding agent from IBM partner/competitor Anthropic, and Codex from OpenAI, another generative AI leader.
Related:Enterprises Contain AI Agents to Balance Risk, Reward
Except that Claude is one of the AI models at the heart of Bob, which routes coding tasks to Claude, open source models from France-based AI vendor Mistral, and Granite, IBM’s own family of lightweight models, depending on the nature of the job.
Venkatesan and her team, who are building out an extensive global tax platform for EY, had been using Bob in private beta for a few months before IBM made it generally available late last month and introduced it to the wider world at the conference.
“I would call it an agent,” Venkatesan said in an interview on Tuesday, the official start of the conference. “It helps you during every phrase. It’s like you’re working with it.”
In the coding community, pair programming is 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.
Bob, who has his own mascot, was certainly not the only new IBM AI creation on display this week.
Krishna positioned AI at the core of the 115-year-old company’s go-forward strategy, saying in his keynote that IBM itself has applied AI and automation across all of 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?”
Among other new developments was the release of 150 prebuilt agents in Watsonx Orchestrate for hybrid cloud and mainframe environments and a major expansion of the Concert AIOps platform. IBM also touted a new generation of the Watsonx Orchestrate agent management system and an integration of Watsonx and Confluent’s streaming data platform, after IBM’s $11 billion acquisition of Confluent.
Related:SoundHound Launches Self-Learning AI Agent Platform
For many observers, IBM is wise to strategically extend its generative AI offerings — led by the Granite and Watsonx lines of models — to hybrid cloud and mainframes, while retaining many cloud AI products and services and maintaining a multi-model, multi-cloud approach.
IBM has a long tenure with many of the world’s biggest and oldest financial institutions and other companies in highly regulated industries that value the data privacy and security of mainframe computers. It’s a trusted brand with loyal customers that are moving forward with both on-premises IT operations and more modern cloud and AI technologies.
Remarkably for IBM, which still builds and sells mainframe hardware and software, mainframes are still a profit center, said Sanjeev Mohan, founder and analyst at the SanjMo advisory firm, in an interview at the conference.
“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.”
Related:Mistral’s Model Lets You Vibe Long-Running Code in the Cloud
Likewise, IBM’s decision not to engage competitively with the biggest generative AI vendors and instead focus on smaller and lighter-weight models was correct, Mohan said.
“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.
Meanwhile, the IT department of another IBM customer, Pennsylvania-based SEI, a large financial services company, is not going the mainframe route in favor of a fleet of AI agents it plans to build with IBM Consulting, the professional services wing of IBM. The company’s accounting section, however, still runs on IBM mainframes.
IBM Consulting recently won a competitive request for proposals at SEI to design agents for cloud-based operations for a multitude of business processes, including replacing dated optical character recognition document systems.
“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. “Those agents would be deployed on our framework and may require tech that we don’t have. In the future, operations goes from banging away on applications to orchestrating agents.”
That tech could include Watsonx models and agents, Claude or OpenAI models, Womack said.
“We definitely are multi-model in our approach,” he said. “All that will be part of the harness we are continuing to build out.”
As for ROI, that remains to be seen, as are the metrics SEI will use to determine it.
“It’s still early days. The question of ROI is a good one,” Womack continued. “I think people are still evaluating the promise that’s there.”
One IBM customer is retired tennis superstar Andre Agassi and his sports entertainment company.
Agassi appeared on the main stage Tuesday to talk about his Watsonx-powered racket sports digital coaching mobile app, set to be released later this year.
Agassi said that when he played, preparation was key to overcoming his physical limitations as neither the biggest nor fastest player on the pro tennis tour.
He said he had to count on his coaches and trainers to help him perform at a high level.
“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.
