You've got the platform and executive buy-in, but do you have the people to deliver on agentic AI?

In this episode, Micah Smith and Kate Ressler talk with Mike Reynolds, Business and Technology Executive at KeyBank, about what it actually takes to build, retool, and upskill automation teams for the shift from task-based RPA to goal-driven agentic AI.

Mike shares how he invests in his team to build automations, how those citizen developer skills are evolving for the agentic era, why ideas that were rejected years ago are now greenlit, and the leadership mindset required to invest in people when the pressure is on short-term results.

Whether you lead an automation team, build solutions, or are figuring out what skills to invest in next, this one's for you.

Every week brings a new AI technique, a new protocol, a new framework claiming to change everything. So how do you actually decide what to build, what to wait on, and what to ignore entirely?

In this episode, Adi Kuruganti, Chief AI and Development Officer at Automation Anywhere joins Micah Smith & Kate Ressler, to share how he thinks about separating signal from noise, what it really takes to move agentic AI from POC to production, and the two contrarian bets his team is making right now on data architecture and conversational UX. Grounded, direct, and worth your time.

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.