Mon, Apr 20 · 5:30 PM CEST
We are excited to announce our next Utrecht JUG meetup on April 20, 2026, hosted at the Kamer van Koophandel. Join us for an evening focused on the future of software development, where AI-driven, agentic systems are becoming an integral part of how we build and operate applications.
In the first session, Soham Dasgupta will demonstrate how AI agents can power autonomous DevSecOps pipelines; from detecting vulnerabilities to generating fixes and validating them through CI. This hands-on talk offers a practical look at building self-driving security workflows with tools like GitHub Copilot.
After the break Raphael de Lio explores how memory works in both humans and AI agents. By connecting insights from cognitive science to real-world engineering challenges, this session sheds light on how to design more reliable and context-aware AI systems.
Join us for an evening of practical insight, new ideas, and great conversations.
Please join us and RSVP!
Because of the limited number of seats, please keep your RSVP up-to-date, so we can welcome someone else if you can't make it.
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## Timeschedule
17:00 Doors open
18:00 Food & Drinks
19:00 Agentic DevSecOps: Autonomous Security Pipelines with AI Agents & Agentic Workflows by Soham Dasgupta
20:00 Break
20:15 The Anatomy of Memory in Humans and AI Agents by Raphael de Lio
21:15 Drinks
# Giveaway
1 JetBrains licence
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# Talks
## Agentic DevSecOps: Autonomous Security Pipelines with AI Agents & Agentic Workflows
What if your security pipeline could find vulnerabilities, file issues, write fixes, run CI, and request human approval — all autonomously? In this hands-on session, we start with a polyglot microservices repo that has zero security tooling and progressively build a fully autonomous agentic DevSecOps pipeline using GitHub Copilot.
You'll see how AI agents perform repo-wide security assessments, how custom instructions shape agent behavior across the SDLC, and how agentic workflows chain dependency scanning, SAST, and test coverage checks into a self-driving loop: scan → auto-create issues → Coding Agent fixes → CI validates → AI code review → human approves. We'll also build custom Copilot agents for IaC security scanning and use GitHub's agentic workflow capabilities to generate recurring security reports — no human trigger required. Walk away with a working, repeatable pattern for embedding autonomous AI agents and agentic workflows into every stage of your DevSecOps lifecycle.
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# The Anatomy of Memory in Humans and AI Agents
Artificial intelligence does not need to copy the human brain to advance, yet cognitive science still offers useful guidance. As agentic applications grow, understanding how humans store and retrieve information can help us design agents that act with greater context and reliability.
This talk connects human memory to the practical challenges of building AI agents with memory. We will review the main types of memory in the brain, revisit a landmark case in neuroscience, and relate these ideas to how large language models process information. We will also look at the real difficulties of taking agents to production, where choosing what to store and how to retrieve it becomes the core challenge.
Participants will learn:
- How insights from cognitive science can guide agent design
- The key forms of human memory and their relevance to AI
- What neuroscience reveals about the limits of large language models
- The main obstacles of deploying agents with memory in real systems
- How our work at Redis led to an open-source, production-ready agent memory server
- Practical ways to improve memory in AI agents
This session offers both conceptual clarity and concrete tools for building more capable agentic systems.
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# Speakers
## Soham Dasgupta
Soham is a technology enthusiast working at Microsoft as a Solution Architect, with over 19 years of experience in software programming, designing, and architecture which includes on-prem, cloud-native applications, and web-based conversational application design.
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## Raphael de Lio
Raphael De Lio is an AI and Software Engineer at Redis with over eight years of experience spanning multiple industries and countries. He is passionate about distributed systems and specializes in Java, Kotlin, and building scalable, high-performance software with a growing focus on reliable, distributed agentic systems.
What drives him is bridging the gap between software engineering and AI engineering, bringing the hard-won knowledge of building distributed, scalable systems into the world of AI where those foundations are often missing but matter most.
Originally from Brazil, Raphael spent six years in Portugal before making the Netherlands his home, where he also helps organize the Dutch Kotlin User Group. He loves blending code, community, and creativity to help developers build better systems faster, and with a lot more fun along the way.