The Last Mile of Agentic AI: From LLM to Enterprise Outcome

Hack Session

About the session

Agentic AI promises autonomous workflows. The reality is messier. Agents that work in demos break in production because they lack what we call the harness — domain knowledge, process awareness, cultural context, and the ability to handle the exceptions that define real enterprise workflows. This talk shares hard-won lessons from deploying agentic AI at scale: voice agents handling 2.5Cr+ calls a month who need to know what "maafi ho jayegi" means for collections outcomes, document agents that must navigate smudged land records in local languages, and credit decisioning agents that need to match analyst judgment — not just generate text. The argument is simple: LLMs give you intelligence. Harness engineering gives you outcomes. And in enterprise, only outcomes matter.

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