Build autonomous AI workflows with agents, tools, memory, & feedback loops Why Loop Engineering? AI agents are easy to demo. They are much harder to make reliable.

The interesting work starts when you stop thinking about a single prompt & start designing the loop around it: what the agent sees, what tools it can use, what it remembers, how it checks itself, when it asks for help, & how it improves over time.

This is a small meetup for software developers exploring that layer.

What to Expect

It won't be a traditional talk, & it won't be a fully structured workshop. Think of it as a practical walkthrough followed by an open engineering jam.

We'll start with a hands-on walkthrough of how I use loop engineering to build autonomous AI workflows using agents, tools, memory, & feedback loops.

We'll look at real workflows, the patterns behind them, & the trade-offs that show up when you try to make these systems actually work.

Bring your laptop if you want to follow along. We'll build a few simple loop-driven workflows during the session.

Open Engineering Jam

In the second half, we'll open it up.

Anyone experimenting with agents, long-running workflows, evals, memory, tool use, or autonomous systems is welcome to share what they're building, compare architectures, ask questions, & trade notes with others working through similar problems.

Who Should Come? Come if you're building with Claude, Codex, LangGraph, OpenAI, MCPs, custom agents, or your own messy stack.

Come if you've moved past chatbot & are trying to make AI systems that can plan, act, observe, recover, & keep going.

The Format

Small group. Practical demos. Real workflows. No polished conference talks.

Bring a laptop, a workflow you're curious about, or just a few good questions.

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