[Austin] Coder Agentic AI Meetup

This meetup is for developers and platform teams who want to understand what it actually takes to move from AI experimentation to production-ready workflows. We’ll focus on how teams are redesigning their development workflows to work with AI, not just adding tools on top. That includes how to structure workflows, manage agents, and introduce the right level of control without killing developer velocity. No hype. No tool comparisons. Just a clear look at why most AI workflows fail and what actually works at scale. Who this is for:- Beginner → intermediate software developers- Platform engineers and DevOps folks supporting dev teams- Anyone using (or wanting to use) AI tools beyond simple autocomplete Agenda:* 5:30pm~6:00pm: Checkin, Food and Networking* 6:00pm~6:15pm: Welcome/community update* 6:15pm~8:00pm: Tech talks and Q&A* 8:00pm~8:30pm: Open discussion & Mixer Tech Talk: Scaling AI Coding Agents Across the EnterpriseSpeaker: Stephen Kirby, Solutions Engineer @ Coder  Abstract: Everyone wants AI coding agents, but putting them on developer laptops creates a new set of problems. Tool sprawl becomes impossible to govern, security and data egress are difficult to audit, and access to agents stays limited to the developers who know how to use them.​As organizations look to scale AI, platform teams are left with the challenge of figuring out where these agents should actually run. Kirby will walk through how remote, organization-owned infrastructure can solve these problems by giving platform teams centralized control over execution, context, tooling, and security. We’ll look at what it takes to move from scattered agent setups to a standardized, auditable foundation that can scale beyond engineering and make AI agents an organizational capability. Tech Talk: Your Agent Needs an AlibiSpeaker: Logan Bell, Founder @ Avanor Abstract: Company workspaces finally give coding agents a place to run that you control. Location, sprawl, and egress get a lot easier from there. The next question is the action itself. What did it try, what rule judged it, and can you show that later without depending on a vendor dashboard? An alibi here is not a story that gets the agent off the hook. It is a record of what the agent tried, what it could reach, and who allowed it, held outside the system that acted. This talk follows one denied tool call from the moment it fires to a hash you can check offline, and shows how that check can sit on the live path without making the official setup worse than a laptop.