AI is everywhere in development right now. Coding assistants. Autonomous agents. Background workflows. AI-generated PRs. But most teams are stuck in the same place:

• Experiments work, production doesn’t.
• AI writes code faster, but workflows break.
• Agents generate output, but teams can’t trust or scale it.
• And governance gets added too late, slowing everything down.

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.

You’ll walk away with:
- A clear understanding of why most AI workflows break when moving to production
- Insight into how AI changes the software development lifecycle, not just coding
- A practical model for structuring AI workflows across planning, building, and operations
- Examples of how teams are introducing control and consistency without slowing developers down
- A mental model for scaling AI usage across teams, not just individual developers

Tech Talk: Agentic Workflows & Reliability: Building Agents That Own Outcomes
Speaker: Chidi Udeze (Reddit)
Abstract: Coding agents are getting good at completing tasks, but completing steps isn’t the same as owning an outcome. I built AgentFlow to explore how we can delegate meaningful, long-running work without micromanaging every step. This talk covers the core patterns behind it: defining clear intent, giving agents outcome-oriented responsibilities, verifying work with evidence, and supervising recovery when things go wrong. The goal is simple: build agent systems we can actually trust with real work.

Tech Talk: Deploying AI at Scale: Infrastructure, Security & Platform Engineering for Production
Speaker: Jullian Pepito (Coder)
Abstract: AI experimentation is easy. Running AI-powered applications and agents reliably in production is an infrastructure problem.
In this hands-on workshop, Jullian Pepito, Solutions Architect at Coder, will break down the infrastructure and platform engineering patterns teams need to move from AI prototypes to scalable, production-ready workflows. Attendees will explore how traditional scalability principles apply to AI consumption, including resource isolation, workload orchestration, security controls, policy as code, observability, and infrastructure governance.
The session will focus on the practical challenges that emerge when AI agents move from individual developer environments into enterprise-scale infrastructure, and how engineering teams can build an architecture that supports AI adoption without sacrificing security, reliability, or developer velocity.

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

Venue:
Improving, 11675 Rainwater Dr #100, Alpharetta, GA 30009

Sponsors:
We are actively seeking sponsors to support AI developers community.  Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 8,000 AI developers in Atlanta and 500K+ worldwide.

Local and Global AI Community on Discord
Join us on discord for local and global AI tech community:
- Events chat: chat and connect with speakers and global and local attendees;
- Learning AI: events, learning materials, study groups;
- Startups: innovation, projects collaborations, founders/co-founders;
- Jobs and Careers: job openings, post resumes, hiring managers;