This presentation was recorded at GOTO Copenhagen 2025. #GOTOcon #GOTOcph
https://gotocph.com

Henrik Kniberg - AI Whisperer & Chief Scientist & Co-Founder of Abundly.AI @henrikkniberg 

RESOURCES
https://twitter.com/henrikkniberg
https://www.linkedin.com/in/hkniberg
https://blog.crisp.se/author/henrikkniberg

ABSTRACT
What is an AI agent?
How do you make agents that actually work and do useful stuff?
And what are some things to keep in mind when doing so?
–Tips, techniques, pitfalls.d

In this talk Henrik shares experiences from real-life agent development. [...]

TIMECODES
00:00 Intro
00:21 The future of work
01:02 What is an AI agent?
02:32 Demo: How to build an AI agent
11:40 Code vs Agent vs Human
13:12 Architecture of an agent platform
14:47 Where to use agents
19:13 Content is king
22:30 Demo: Data documents & apps
24:13 Content is king continued
27:11 Agent design tips
33:20 Cool thing: Agents making their own tools
36:45 Wrap-up
39:35 Outro

Download slides and read the full abstract here:
https://gotocph.com/2025/sessions/3766

RECOMMENDED BOOKS
Alex Castrounis • AI for People and Business • https://amzn.to/3NYKKTo
Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ
Holden Karau, Trevor Grant, Boris Lublinsky, Richard Liu & Ilan Filonenko • Kubeflow for Machine Learning • https://amzn.to/3JVngcx
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) • https://amzn.to/3AQmIRg
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • https://amzn.to/2ZD7t0x
Lakshmanan, Görner & Gillard • Practical Machine Learning for Computer Vision • https://amzn.to/3m9HNjP

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GOTO's resource offers insights, tutorials, and resources for software developers, architects, and technology leaders. Readers can learn about emerging technologies, industry trends, and best practices for software development. With articles, talks, and workshops, GOTO provides  guidance and expertise for staying ahead in the ever-evolving world of technology.

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Henrik Kniberg shares two and a half years of hands-on experience building AI agents at GOTO 2025. He defines agents as autonomous digital entities using LLMs as their brain, with tools and a mission beyond simple chat. A live demo shows an agent connecting to GitHub and Slack, making phone calls, and scheduling recurring tasks autonomously. Key lessons include: identifying tasks that are time-consuming, low-value, and moderately complex as ideal agent candidates; using structured data formats (JSON with CRUD tools) instead of dumping raw CSVs into LLMs for scalability; having agents write their own code and scripts to avoid token waste; treating agents like interns (useful metaphor for debugging and design); keeping humans in the loop for safety; iterating heavily on prompts; and managing risk by scoping agent jobs narrowly and adding guardrails as complexity grows. A real-world case study of a scheduling agent for a Swedish TV channel illustrates both the potential and the challenges. The talk also previews agents building their own tools via HTTP requests.

AI Agents in Practice • Henrik Kniberg • GOTO 2025