Agentic AI in the Wild - Callstack & Qodo Dev Community
AI agents are moving into production, and the hard part isn't getting one to work — it's making it work reliably, day after day, on real codebases. This meetup gathers builders, founders, and practitioners who are past the demo stage and deep in the mess of integrating agents into CI/CD pipelines, developer platforms, and knowledge systems.
We've lined up practitioners who'll share what's actually working (and what isn't) in their own agentic systems, followed by time to talk it through with the people sitting next to you.
Expect talks from different points in the agent workflow: cloud agents running mobile apps on real devices to verify what a pull request actually changed before merge; a Vite-to-Expo migration of a large React app handled by a coding agent re-prompted on a loop, one manageable piece at a time; and turning team standards into machine-readable guardrails so AI-generated code respects your architecture instead of quietly eroding it. Verification, execution, and quality control - the parts nobody demos.
Agenda highlights:
5:45 PM — Doors Open & Pizza & beers
6:10 PM — Intro
6:20 PM — Matt Hargett (Callstack)
6:45 PM — How to Embed Code Quality into SDLC / Nnenna Ndukwe (Qodo)
7:10 — Large Codebase Migration with Loop Engineering / Rafael Mendiola (okthink)
7:35 PM — Networking & Pizza
Talks abstracts:
Large Codebase Migration with Loop Engineering / Rafael Mendiola (okthink)
Moving a large React app from Vite to Expo is not a simple framework upgrade. Hundreds of components, styles, browser APIs, and tests must be converted without breaking the product. Traditionally, we would create a huge project plan, divide it into dozens of tickets, and spend weeks coordinating and reviewing the work. Instead, we created an Agent Loop: a coding agent repeatedly received the same prompt every 30 minutes, found one manageable part of the migration, converted it, ran tests, recorded its progress, and left the code ready for the next run.
This talk explains how that loop turned an overwhelming migration into a series of small, repeatable steps. You’ll learn how to give agents clear rules, help them choose the next task, verify that their changes are correct, and prevent them from repeating work or drifting away from the goal. You’ll also see where the approach failed, why strong tests and feedback loops mattered more than detailed ticket planning, and how your role changes from writing every line yourself to building a system where agents can make safe, steady progress.
How to Embed Code Quality into Your ADLC with Codex/ Nnenna Ndukwe (Qodo)
AI is a force multiplier that turns weak standards into architectural chaos. As code review becomes the ultimate bottleneck, engineering teams must bridge the gap between human intuition and machine output. In this talk, we'll explore how to codify development best practices into machine-readable guardrails. We'll walk through how to leverage context engineering at scale to ensure your AI code tools respect your system’s design, preserving long-term maintainability without sacrificing the speed of the AI era.
You'll learn how to embed code quality into the SDLC from AI-generated output with Codex and multiple AI dev tools. They will leave with a practical methodology for encoding best practices into their workflow, where developers already operate (CLI, IDE, and Git).
Matt Hargett (Callstack)