Innumerable AI agents can overwhelm. Can Walmart’s ‘super agents’ come to the rescue?

For the last few months, Walmart has been parading out an army of new agents for its workers, according to global chief technology and development officer Suresh Kumar. AI systems can now help with tasks like pricing items, stocking shelves, or requesting time off.

But the whole ensemble may have gotten to be a bit much.

“If you build individual agents for every use case, it very quickly becomes overwhelming for the end user,” Kumar told us.

Now, a team of “super agents” is here to save the day. The retail giant is reorganizing its many agents under four of these souped-up personas, which can route queries to any of the dozens of sub-agents under their scope.

The four super agents will be geared toward shoppers, store associates, suppliers and advertisers, and developers. Already live is “Sparky,” a shopping assistant that can help plan around an occasion, summarize reviews, or set up recurring household orders. “Marty” will help merchants craft ad campaigns and list items. The two internal super agents, for employees and developers, remain nameless.

“The agent knows that you are a merchant. The agent knows that you are a store manager. The agent knows that you work in people services. And it also knows all our sub-agents that are there. It can coordinate,” Kumar said. “We will have tons and tons of sub-agents underneath as we start automating more capabilities, as we start addressing more use cases.”

Networked: Ever since talk of agents reached a dull roar in the tech industry, experts have been telling us this tech is all about teamwork. Initial agentic experiments will eventually level up into orchestrated networks of task-specific entities, these pros said.

“The dominant discourse in modern LLM-based agents is still leaning heavily toward building large single agents as one-stop shops, and I don’t think that scales,” Babak Hodjat, CTO of AI at Cognizant, told us in a previous interview in February. “Multi-agent systems hold the key to leveraging AI in ways that can balance and analyze often conflicting needs to deliver higher value impact.”

Trust issues: But most companies are far from that point. A recent EY survey found that only 14% of companies have fully implemented agents. The biggest barriers are all trust-related, EY found—cybersecurity and data privacy concerns chief among them.

Walmart has a framework to govern who has access to what when it comes to security and compliance, Kumar said. In most cases, there’s still a human in the loop to evaluate response quality and fine-tune the model based on where it might be “misaligned,” Kumar said.

“[We] realize that this is a journey, just like all of these other businesses,” Kumar said. “So it’s not like we are going to start on day one giving full access and full delegate authority and full capabilities to any single agent, even the super agent.”

Walmart is building its agents to coordinate with data sources through Anthropic’s Model Context Protocol (MCP), an open-source framework that standardizes how agents connect with outside systems. Kumar said the plan is to make the system fully interoperable so that, for example, Sparky might continue a shopping journey that started on another site, or the associates’ super agent might communicate with an Aetna AI agent about health insurance benefits.

As the shopping giant continues to build out these agentic systems, Kumar envisions the shopping experience eventually encompassing different modes of media, from TikTok videos to snapped photos of home decor.

“If I’ve already decided on a particular decor for my living room, what is the particular painting that I want to hang on the wall? This is not something that you can…do through search keywords,” he said. “No, you actually take a picture and you let the agent go, ‘Ah, now I understand what it is that you are trying to do: Here, let me suggest a bunch of stuff.’ So I think that is the future.”