May 2026 was unusually dense: I spent the month moving between Google Cloud Day Estonia, CyberSec Europe 2026 in Brussels, and AWS Summit Amsterdam.

This post is a marker for that month and for the direction of my work as Kristofer Jussmann (Ker102): DevSecOps, AI/ML systems, cloud infrastructure, secure automation, and open-source engineering.

TL;DR

• On 12 May 2026, I attended Google Cloud Day Estonia. It was a strong hands-on event with a good atmosphere and felt like a first-of-its-kind Google Cloud event for the local ecosystem.
• On 20-21 May 2026, I attended CyberSec Europe 2026 in Brussels, where the strongest themes were AI security, business resilience, and what companies need to do now to defend against modern attacks.
• On 27 May 2026, I attended AWS Summit Amsterdam. It was the biggest event I had attended at that point, with a strong keynote, useful booths, and a direct AWS certification voucher win from an AWS challenge.
• The month reinforced my positioning: I am not a generic full-stack engineer. I build and document systems around DevSecOps, AI/ML infrastructure, RAG, workflow automation, and production evidence.
• This site is becoming the canonical source for my professional identity, case studies, and long-form technical work. Hashnode remains useful for distribution, but canonical authority should point back here when the same article exists in both places.

12 May: Google Cloud Day Estonia

Google Cloud Day Estonia stood out because it was practical and hands-on. The atmosphere was strong, the event felt unusually direct, and it gave me a clearer view of how Google Cloud is positioning itself for builders and technical teams in Estonia.

It also mattered because of timing. AI systems work is increasingly tied to cloud execution: model services, permissions, data flows, observability, CI/CD, storage, and cost control. For the kind of systems I build, cloud architecture is not background infrastructure; it is part of the product.

That connects directly to my portfolio direction. My projects are not only UI demos. They involve cloud services, identity, CI/CD, prompt and model behavior, workflow automation, observability, cost constraints, and the failure modes that appear after something is deployed.

20-21 May: CyberSec Europe 2026 in Brussels

CyberSec Europe 2026 in Brussels was one of the most useful security events I have attended so far. The value was not only in the booths or sessions, but in the recurring pattern across conversations: AI security is becoming a business security issue, not a separate research topic.

The key takeaway was that businesses need to treat modern security as a system-level problem. The important areas are identity, cloud posture, access control, monitoring, incident readiness, vendor risk, employee workflows, AI usage policies, and secure defaults around the tools people already use.

For AI systems, that is not abstract. If a system uses LLMs, retrieval, tool calls, user data, or cloud execution, then security and operational control become part of the product. DevSecOps is not separate from AI engineering; it is what makes AI systems auditable, deployable, and credible.

I also met many strong people there and won a Bechtle challenge, which came with a battery bank. It was a small win, but still a useful signal of the event: the best parts were interactive, practical, and connected to real operational security problems.

This is one reason I keep pushing my portfolio toward structured case studies rather than generic project cards. Hiring managers, technical reviewers, and AI search engines all need evidence: what was built, how it worked, what failed, what it cost, and what tradeoffs were made.

27 May: AWS Summit Amsterdam

AWS Summit Amsterdam had the strongest scale and ecosystem energy of the month. It was the biggest technology event I had attended at that point, and the keynote made the size of the AWS ecosystem feel very concrete: cloud architecture, AI services, security, partner tooling, certification paths, and production operations all in one place.

The booths were also useful because the staff were open to direct technical conversations. For me, that kind of environment matters because it connects the abstract parts of cloud engineering to people actually building, selling, securing, and operating these systems.

I also won an AWS challenge and received a free AWS certification voucher directly from AWS. My plan is to take the AWS Certified Solutions Architect - Associate after finishing the HashiCorp Terraform Associate certification path. That certification order matches the direction of my work: infrastructure fundamentals first, then AWS architecture, then deeper cloud security and AI systems delivery.

That connects directly to my work around n8n workflows, automation datasets, AI-assisted workflow generation, and open-source tooling. Automation is not only about connecting APIs; it is about making workflows understandable, recoverable, secure, and measurable.

Open source also came up repeatedly as a credibility signal. I have been involved with open-source work and collaboration around projects including Matplotlib and Prowler, and I want more of my public technical output to show the same standard: clear context, reproducible evidence, and useful contributions.

What This Changes About My Site

The main change is editorial discipline.

From now on, this site should be the canonical home for:

• professional identity: Kristofer Jussmann, also known as Ker102;
• detailed About information for humans, recruiters, search engines, and AI agents;
• project case studies with architecture, deployment details, research evidence, costs, tradeoffs, and follow-up work;
• technical blog posts that document real engineering experience rather than generic tutorials;
• structured references to GitHub, LinkedIn, Hugging Face, Kaelux.dev, and Hashnode.

Hashnode can still be useful for reach and distribution, especially when the audience is already there. But if an article exists on both Hashnode and this site, the canonical version should be the article on this site. Hashnode should either use a canonical URL pointing here or act as a short syndicated version that links back to the full post.

Current Direction

The direction is clear: secure AI infrastructure, DevSecOps, cloud systems, model evaluation, RAG, workflow automation, and open-source engineering.

The next step is to keep turning project work into evidence:

• PromptTriage as the most complete case study, including research, architecture, costs, and benchmark context;
• Kaelux.dev as a production-facing AI engineering and infrastructure platform;
• ViperMesh as a tool-using AI system with a clearer current name and technical narrative;
• n8n automation work as a dataset, fine-tuning, and workflow generation case study.

May 2026 made the gap obvious: there is a lot of AI content online, but much less evidence-backed AI systems work. That is the space I want this site to occupy.