Meet the winners of Automation Anywhere's Agentic Bounty Challenge

In this episode, hosts Micah Smith and Kate Ressler spotlight winners from Automation Anywhere’s Agentic Bounty Challenge, created to help the Pathfinder community move beyond simple task automation and build goal-based AI agents for real business problems.
 
They interview three winners: Jenna Saunders, who built an agent that performs sentiment analysis on product reviews, outputs a CSV with sentiment scores, and generates actionable insights, using Python for precise data sorting and formatting; Omkar Mahajan, whose transit-focused agent uses maintenance and disaster management manuals to recommend next actions, create Salesforce tasks, work orders, and purchase orders with guardrails like order-history checks and approved product lists; and Ganesh Bhat, who built a “Sprint to Jira” agent that turns unstructured sprint planning inputs (screenshots, emails, transcripts) into Jira epics, stories, and tasks with human-in-the-loop and data protection guardrails.