You walk in, make your first coffee of the morning, and there it is: a pull request, ready for review. While you slept, your agentic software factory detected a performance regression from production traces, figured out what caused it, and shipped a fix. Bug report, tests, release candidate: all done. All that's left is to hit approve.

This is where agentic software development is heading. Parts of it are already here. But most teams aren't anywhere close. They're still copy-pasting ChatGPT output into their IDE and babysitting agents through tasks that should be trivial. And when the hallucinated code passes review and breaks in production, they're the ones debugging it.

The models are good enough. The problem is everything around them.

We'll start where most teams stumble and build toward a fully integrated agentic software factory. At each step, we add one capability and take one more thing off your plate. Context engineering so agents stop forgetting what matters mid-task. LSP so they understand code structure instead of pattern-matching against text. MCP so they connect to your observability stack, issue tracker, and deployment pipeline. Skills and hooks so one-off prompts become repeatable, auditable workflows. And spec-driven development so intent maps to verifiable output.

We'll cover the patterns that work and the ones that waste your sprint. And we'll glimpse what comes after: agents that collaborate, review, and ship on their own. They still need your sign-off, but they stop needing your attention every five minutes.

Monday morning, you'll open your laptop with a plan: which layer to add first, what to stop doing by hand, and how close your team actually is to that morning coffee PR.

Who should attend: Developers and engineering leads who are done treating AI as fancy autocomplete and want to build agentic workflows that keep running after they close their laptop.