US Retailer Embeds Agentic AI Across Software Development
Get the Tech newsletter
Daily tech — startups, AI labs, chips, the launches that shape the next decade. Free.
- Prasad Banala, director of software engineering at a large US-based retail organization, joined the Infosys Knowledge Institute Podcast to discuss operationalizing agentic AI across the software development lifecycle.
- Dylan Cosper hosted the "Enterprise AI hub" episode, pressing Banala on how his team applies AI to validate requirements, generate and analyze test cases, and accelerate issue resolution.
- The retailer maintains strict governance, human-in-the-loop review, and measurable quality outcomes even as it embeds agentic AI deeper into development workflows.
- Banala framed the AI deployment as spanning the full SDLC — not isolated tooling — positioning agentic AI as infrastructure for requirements, testing, and bug triage.
- The episode frames measurable quality outcomes as a non-negotiable check on AI-generated work, tying agentic adoption to engineering metrics rather than raw speed.
Why it matters: A director-level practitioner is publicly walking through a production-scale deployment of agentic AI inside one of the largest US retailers — naming the governance and human-in-the-loop controls he's keeping in place. For enterprise engineering leaders weighing where to insert agentic AI, Banala's breakdown sketches a concrete pattern: embed it across the SDLC, but anchor every output to reviewable quality metrics.
