Sessions

Agents get a lot more useful when they can finish the job without you sitting in the middle of every step. The missing piece is usually the loop: act, observe, verify, and only stop when the work is actually done.

In this talk, I’ll show how to close that agentic loop. We’ll look at how agents can verify their own work, how good system design shows up in the diffs they produce, and which primitives you can compose so they operate with real autonomy. I’ll also share how Kody MCP fits into this picture: searchable capabilities, sandboxed execution, memory, and the surfaces agents need to check their work before they hand it back to you.

You’ll leave with a practical model for widening the loop—trading a bit of compute for a lot less babysitting—so your agents ship work you’re willing to trust.

Most people working in AI feel behind. It seems like every day they open their email and find yet another model release or tool to learn, feel stressed from constant change and chaos, and often fear for the future of their jobs.

This talk is about staying current without making yourself miserable in the process.

We’ll start with the practical side: what’s worth learning vs. what can be safely skipped, and how to develop a consistent learning plan that helps you keep your skills sharp without becoming overwhelmed.

Then we turn to the mindset side, which might matter even more. We’ll discuss how to handle common blockers like imposter syndrome, procrastination, and guilt, to keep you advancing your career over the long term from a place of curiosity and enjoyment instead of fear and stress.

Marina Wyss has coached more than 200 career changers into AI roles, and has seen first hand that the people who build durable careers are the ones who found a relationship with this field they can actually sustain.

Attendees will leave with a concrete weekly learning system and a healthier way to measure progress that doesn’t depend on keeping up with everything.

AI coding agents are changing what it feels like to be a software engineer. For a lot of us, that’s challenging our sense of craftsmanship. If agents are writing the code, do we lose the joy of building?

I don’t think so. The building moves up a layer.

In this talk, I’ll share how I found that familiar engineering flow state again. Not by writing every line myself, but by designing agentic systems that still require the engineering principles we value: systems thinking, decomposition, separation of concerns, state management, etc.

The tools are different now, but the engineering discipline is still there. We’ll walk through how to apply the engineering muscles you already have to a new set of building blocks.

If you’ve been wondering where your value goes in an AI native world, this talk will help you see that it hasn’t disappeared. It’s now at the system level.