Masterclass AI Systems Architecture

AI demos look impressive because nobody has to rely on them yet. Production is a different matter. People need to understand the results, teams need to measure quality, and the product needs clear rules for when AI may act and when it has to stop.

The difference between a demo and production is rarely a better prompt. What matters is the architecture around the feature, and just as much the interface on top of it. Once agents do the work and people review it, the interface is no longer a place to get tasks done. It becomes the control surface for quality, trust, and accountability.

In this masterclass we will look at AI Systems Architecture from the product side and map out what actually makes an AI feature production-ready:

– Contract first, not prompt first: which structured outputs does the product really need, and what does the user need to see, decide, or override? – Evaluation as a quality gate: classic pass/fail tests aren’t enough. So where do the signals come from that tell you whether quality holds? – Agent-first design: when people move from doing the work to reviewing it, the interface becomes a review surface. That means supervision that scales with risk, decisions that double as learning signals for evaluation, and friction that is used on purpose. – Control and handoffs: what can an agent do on its own, and where does a human step in, without drowning people in confirmations?

You will leave with a working model for mapping an AI feature as a production system, covering required outputs, evaluation signals, review responsibilities, risk levels, and handoff points. You will also come away with a sharper sense of what UX becomes when your users supervise agents.

Datum

18.11.2026

Uhrzeit

TBA

Konferenz / Veranstaltung

Digitale Leute Summit 2026

Ort

Palladium, Köln