Name: NDC AI 2026
Start: 2026-06-08
End: 2026-06-10
Location: NDC AI

But how does agentic AI work under the hood?
How are models able to understand when to use a tool and how to use it?

In this demo intensive session Alan will explain the concepts of agentic AI in detail. Starting with the basics of function calling in the Open AI models, he will cover the techniques used to provide tools to models, and how the models are able to understand and use the tools. The use of prompting to guide models and improve tool call behavior will be covered, along with guidelines for adding tools to your solution. Alan will also cover the protocols used by Open AI models as well as how the model context protocol is used to provide compatibility between services and LLM solutions.

Join this session if you want to understand what goes on under the hood of function calling, MCP and agentic AI.


Talk (60 min)

AI Agents In-Depth – Function Calling, MCP and Tool Use Under the Hood

AI Tools and Data

AI Agents

AI Fundamentals

We will demonstrate how vulnerabilities can be chained together to steal and exfiltrate sensitive data through indirect prompt injections, malicious rendering techniques, and abusive tool calls. Finally, we will break down the reality of AI risk and show exactly how to build the guardrails needed to stop these attacks before they succeed.-

Breaking the AI Cage: The Art of Manipulation and the Reality of Risk

Security

In this session, we’ll cut through the hype and focus on practical, developer-tested strategies for getting the most out of AI in your workflow.

You’ll learn how to master prompting and context engineering, make the most of long context windows, streamline debugging and testing, and integrate AI into your daily development practices without sacrificing code quality or security. We’ll also explore how emerging standards like Model Context Protocol (MCP) unlock new workflows by connecting your AI assistant directly to tools such as GitHub, Slack, Playwright or Figma — turning it from a code generator into a true development teammate.

Whether you’re new to AI-assisted coding or already experimenting with it daily, you’ll leave this talk with concrete ideas and techniques you can apply immediately to level up your development process.

10 tips to level up your ai-assisted coding

AI-Assisted Development

By now most of you have set up your own coding agent, maybe with sub-agents, custom instructions, and skills. But how do you go from a useful assistant to a system that runs autonomously, overnight, unsupervised, in production?

I'll walk through how we built a fully autonomous development workflow at Nordic Corporate Bank where an AI agent picks up a task, implements the solution, runs tests, creates a pull request, and reviews its own code, all before a human ever gets involved.

When developers open their laptops in the morning, finished pull requests are waiting for review. Build failures and production exceptions are automatically routed to the agent, which fixes them right away. Developers spend their time on architecture, design, and the problems that actually require a human, plus building the system that builds the system.
This is not a proof of concept or a keynote demo. This is code deployed to production every day. In a bank.

How We Built an Autonomous Development Workflow at Nordic Corporate Bank

In this talk, Joachim Jacobsen will present Telenor AI Factory’s service offerings - including GPU-as-a-Service (GPUaaS) and Model-as-a-Service (MaaS) - all delivered within the framework of sovereign data processing.

Talk (30 min)

Unlocking Sovereign AI Infrastructure for Nordic companies

At Tet Digital, we ran a six-week Claude Code pilot across 6 teams and 30 developers, then rolled it out to 180. 90% reported higher productivity. But productivity isn't the whole picture: AI makes mistakes, so team practices for catching and correcting them matter more, not less; there's reduced learning, so skill development needs continued focus; the developer role is shifting toward orchestration and quality control; and like any tool, this one needs maturation, not just access.

In this talk, Stein Inge Morisbak (CTO) shares the concrete findings from the pilot, why Tet chose a deliberate three-step rollout with mandatory training and guardrails instead of an open tap, and why AI is best understood as an amplifier — one that makes deep technical understanding more valuable, not less. When anyone can ship, someone has to know what we're actually shipping.

For God's sake, keep the nerds!

In this talk, I’ll share practical agentic AI workflows, relevant research on why this way of working matters, and what happens when you take it further with agent teams working in parallel.

How do we preserve the mental model when AI generates thousands of lines of code in seconds?

Expect concrete examples throughout, set in a retro pixel-art cyberpunk world spanning ocean floors and desert landscapes.

Polymorphic Mindset

This talk examines what can go wrong when AI models are secured using assumptions and controls that do not hold up in real deployments, creating gaps between perceived safety and actual behavior. Rather than cataloging attacks, the discussion focuses on why common AI security approaches fall short, including brittle safeguards and limited visibility once systems are in use. As AI systems become more agentic, small failures or exploitations can have outsized impact, allowing models to take actions, influence other systems, or compound mistakes at scale. 

The talk closes by outlining how security teams can reason more clearly about AI risk today and what needs to change as these systems continue to evolve.

Talk (40 min)

Keynote: Securing AI Systems. What Can Go Wrong, Why It Matters, and What Comes Next

This talk will cover designing secure agents, how the various failure points are exposed in the real world, and how these failure points can be remediated. We’ll look into common misconceptions about security systems, and how key elements of secure agent design that are often overlooked. We’ll use the perspective of an AI attacker to understand where agentic systems are vulnerable, how to minimze the impact of these attacks, and how to make sure these impacts don’t make your agent utterly useless to its users.

HitchHacker's Guide to Building Secure Agents

In this session, I'll share what I've learned from using Claude Code daily and teaching it to developers in workshops. We'll go into the features that change how you work. Things like shaping Claude's behaviour through 

, building your own commands and skills, automating feedback loops, and understanding the small configuration details that most people overlook.

We'll also look at use cases beyond software development. We'll use Claude Code as an actual AI-assistant, not only a code-assistant.

This isn't a getting-started guide. It's a tour of the parts of Claude Code that only become visible once you stop treating it like an autocomplete tool.

If you use Claude Code but feel you're not getting the most out of it, this session will help you see what it can really do.

What Claude Code Can Do That You Haven't Tried

Here's what we've picked up along the way patterns that held up, things we had to rethink, and a few demos of where we are right now.

Agentic Engineering: Notes from Building and Shipping with Agents

Talk (90 min)

NDC AI Afterparty

This talk is our playbook, or the parts any team can steal. How we think about AI safety after real incidents, from sandboxing and git hooks to agent permissions and supply chain protection. How we evaluate new tools honestly (including when the AI lied in our own analysis). How we built a community of practice from scratch with workshops, coaching, peer-led knowledge sharing. And the one principle that kept us honest: “Does this make the community more capable, or does it make us more central?”

You don't need 2,000 developers to use this. You need one person who cares. Maybe that's you.

The playbook we built for 2,000 developers (and the parts any team can steal)

This talk shows a better approach: shift the focus from chasing specific attacks to teaching solid defensive coding principles. We'll build security knowledge directly into the agent — using skills, hooks, and standards — so it looks up the right guidance, plans for it, and reviews its own work. You'll leave knowing how to make your agent produce secure code far more often, by default.

Teaching your coding agent defensive coding

After about 7,500 sessions I notice they're all variations on the same move — using cheap LLM tokens to claw back something AI made suddenly much harder: understanding what's in your code, your sessions, your design space. Addy Osmani calls it "comprehension debt"; Simon Willison, "cognitive debt".

I had a couple of days giving Claude Code to engineers who'd never used it. What they reached for first wasn't the chat — it was the tools. Once a tool exists, you don't need to know how to build it to use it. I'll walk through three of these tools, the prompt → skill → tool pipeline that produced them, and the patterns engineers picked up fastest when handed them — plus one uncomfortable finding from the research: AI walkthroughs measurably improve comprehension and inflate confidence about it. Designing for both is the actual craft.

What Actually Happens When You Give a Dev Team Claude Code for a Day

Although things worked, something felt off. Implementations were technically correct but oddly inconsistent.


I realized that AI didn't make any mistakes, but that I hadn't made the decisions. AI couldn't cross any boundaries, because I never drew them. Speed made it impossible to ignore implicit thinking.

This is not a talk about prompting, frameworks, tooling or models. It's about recognizing where decisions were missing all along. AI makes it uncomfortably fast to see where boundaries are missing.

NDC { AI }

Agenda

09:00 - 09:40 (UTC+02)

Keynote: Securing AI Systems. What Can Go Wrong, Why It Matters, and What Comes Next

Kasimir Schulz

10:00 - 11:00 (UTC+02)

What Claude Code Can Do That You Haven't Tried

Gui Ferreira

Breaking the AI Cage: The Art of Manipulation and the Reality of Risk

Stök .

Joona Hoikkala

Polymorphic Mindset

Marina Santos Haugen

11:20 - 12:20 (UTC+02)

AI Agents In-Depth – Function Calling, MCP and Tool Use Under the Hood

Alan Smith

How We Built an Autonomous Development Workflow at Nordic Corporate Bank

Hallstein Brøtan

What Actually Happens When You Give a Dev Team Claude Code for a Day

Stian Håklev

13:20 - 14:20 (UTC+02)

Agentic Engineering: Notes from Building and Shipping with Agents

Mats Oustad

The playbook we built for 2,000 developers (and the parts any team can steal)

Håkon Eriksson

Øyvind Viken

HitchHacker's Guide to Building Secure Agents

Kenneth Yeung

Kasimir Schulz

14:40 - 15:40 (UTC+02)

10 tips to level up your ai-assisted coding

Aleksander Stensby

Where thinking stops

Yngve Bakken Nilsen

SOTA Agentic Coding with OpenCode, Greek Gods and E2E Validations

Tjalve Aarflot

16:00 - 16:30 (UTC+02)

Teaching your coding agent defensive coding

Erlend Oftedal

For God's sake, keep the nerds!

Stein Inge Morisbak

Unlocking Sovereign AI Infrastructure for Nordic companies

Joachim Jacobsen

16:30 - 18:00 (UTC+02)

NDC AI Afterparty