Ahead of its flagship retail-tech event Converge, Walmart in August, 2025 unveiled WIBEY, a super agent platform under the retailer’s newly introduced agentic framework.
WIBEY enables developers to specify what they want (viz, a new microservice, a UI component, or a fix for an accessibility bug) and plans the workflow using Walmart’s internal APIs via the Model Context Protocol (MCP), and delivers working, testable code.
“WIBEY is more than just vibe coding. It has starter kits, access to enterprise APIs, and context-awareness that makes the output scalable and maintainable,” Sravana Kumar Karnati, EVP, global tech platforms, Walmart told AIM.
WIBEY acts as a single, intuitive entry point for anyone building, deploying, or operating technology at Walmart, functioning not as a dashboard or portal, but as an invocation layer that interprets developer intent and orchestrates execution across Walmart’s agentic ecosystem.
Representing a fundamental shift in software development and operations, WIBEY is fast, context-aware, and meets users where they work whether in CLI, Slack, or Visual Studio augmenting workflows without forcing teams to change their existing processes.
Supporting WIBEY, Element, Walmart’s machine learning platform has introduced new capabilities such as agent-aware pipelines, stateful architecture, and standardised communication protocols.
What is Walmart Solving?
For developers inside Walmart, legacy code is often the biggest pain point as Karnati mentioned. He further added that much of the mainframe stack is built on COBOL—hard to maintain, harder to modernise. With WIBEY, developers don’t need to slog through every line manually.
Instead, WIBEY can analyse legacy code, map it to modern APIs, and even suggest equivalent implementations in languages like Java, Go, or Rust. Developers remain in the loop, reviewing pull requests and test cases that WIBEY generates automatically.
This means faster modernisation, without burning developer energy on syntax-heavy rewrites.
Another area where WIBEY has proven game-changing is accessibility compliance as Karnati explained. Ensuring apps meet WCAG (Web Content Accessibility Guidelines) is critical, but finding and fixing accessibility gaps is often repetitive and time-consuming.
With WIBEY, developers can spin up agents that scan code for accessibility gaps, fix them, write test cases, and even run automated browser tests. Doing this, Walmart has seen as Karnati reveals, an 8–10x improvement in velocity for resolving accessibility issues.
“Developers don’t want to spend their time fixing repetitive bugs. WIBEY lets them supervise the process instead of grinding through it,” Karnati said.
Unlike some generative coding tools, WIBEY doesn’t push changes directly into production. Instead, it creates pull requests (PRs) that developers review. This keeps engineers firmly in the driver’s seat, while letting WIBEY handle the repetitive, automatable steps.
What Developers Get?
For developers, this means fewer late nights debugging minor issues, and more time tackling system design, distributed algorithms, and scaling challenges.
WIBEY essentially marks a shift for developers from simple prompt engineering to contextual engineering.
Instead of just writing clever prompts, developers can now feed WIBEY with knowledge bases like HR policies or system rules, APIs and MCP tools such as sourcing, inventory, or merchandising services, as well as constraints and meta-rules like “keep code under X lines” or “always add test cases.”
This richer context enables WIBEY to generate output that is not only syntactically correct but also domain-aware and scalable. For students and early-career developers, this signals that syntax alone isn’t enough.
Karnati stressed on computer science fundamentals such as algorithms, caching, distributed systems over memorisation of languages. He said that “You can learn Golang or Rust on the job, but you can’t quickly learn the fundamentals of distributed systems at Walmart’s scale. That’s what we test for.”
In other words, developers who combine strong CS fundamentals with adaptability in agentic workflows will thrive in this new era.
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