Remote or On-site1 DayZurich, Switzerland

Build Reliable AI Agents — Workshop in Zurich

Bring your team up to speed on AI agent architecture in Zurich. This 1-day workshop covers the core building blocks — tool calling, agent loops, context management, human-in-the-loop patterns — and teaches your engineers how to design agents that actually work in production.

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Why Take This Workshop in Zurich?

Zurich hosts Google's largest engineering office outside the US, along with ETH Zurich, one of the world's top technical universities. The city's fintech and enterprise scene is deeply invested in type-safe development. Our AI agents workshop in Zurich gives your team hands-on experience designing reliable agentic systems — the skill set every engineering team needs in 2026.

Workshop at a Glance

Duration

1 Day

Format

Remote or On-site

Participants

Up to 15 participants

Price

€4,500/team

What Your Team Will Learn

This workshop is for software developers, technical leads, and builders who want to understand how modern AI agents work and how to design them more reliably. It is especially relevant if you are already experimenting with LLMs and want to move toward more advanced, agentic workflows.

Understand the key building blocks of AI agents
Know how tool calling, loops, and context handling fit together
Recognize the main challenges involved in building reliable agents
Learn practical patterns for designing safer, more robust AI workflows
Leave with a clearer mental model for building production-ready AI agents

Workshop Curriculum

We connect theory to practice: how agents use tools, how loops behave in the wild, how to manage context and memory, when to add human approvals, and how to think about evaluation and system design as you move beyond simple LLM calls.

Reliable AI agents — from concepts to production patterns

What AI agents are and how they differ from simple LLM applications
Tool calling and connecting agents to external systems
Agent loops and task execution flows
Context management and memory considerations
Human-in-the-loop patterns for safer systems
Common reliability challenges when building AI agents
Evaluating and improving agent behavior
Practical design patterns for production-minded AI agents

Focus Areas

LLM

LLM APIs

How models are invoked in agent workflows, constraints, and failure modes you need to design for.

API

Tools & integrations

Patterns for calling external APIs, validating outputs, and keeping agents bounded and observable.

Eval

Evaluation & reliability

Practical approaches to measuring behavior, regressions, and when to add human oversight.

Your Instructor

Davy Engone

Founder & Software Mentor @ Hackages

Davy helps teams ship software with confidence — including AI-assisted development and agentic systems. This workshop distills practical patterns for reliability, evaluation, and design that go beyond polished demos.