Vasilis Skourtis is an engineer that applies reverse engineering constantly in order to have a look at the source code of the world. Currently, he provides his services as an Information Security Officer for the Hellenic Electricity Distribution Network Operator (HEDNO), after accepting the challenge to protect human rights and national assets against an invisible enemy in an undeclared CyberWar. For more than a decade, he was developing web applications in various industries, like betting, hospitality, insurance, and projects for the European Union.
Academically, he graduated from the Department of Electronic & Computer Engineering of the Technical University of Crete(TUC), while he holds 2 postgraduate diplomas in Engineering Management (TUC) and in Information Systems (UOA).
He thinks that a driver that drives in the same way for 30 years remains stagnant, repeating the same mistakes without being aware of them, while a driver that races learns from the competition and evolves. Therefore, he joins competitions occasionally to improve himself. During that romantic journey, he found himself lucky enough to be part of the winning team of the Threat Modeling Connect Spring 2023 Hackathon, member of the runners-up team (2nd) of the Startup Weekend 2012 (Athens Microsoft Facilities), as well as being 1st in Web Applications Design and Development and Top50 overall during a written exams competition ran by the Supreme Council for Personnel Selection of Greece(>15000applicants, 2022).
Vasilis Skourtis is an engineer that applies reverse engineering constantly in order to have a look at the source code of the world. Currently, he provides his services as an Information Security Officer for the Hellenic Electricity Distribution Network Operator (HEDNO), after accepting the challenge to protect human rights and national assets against an invisible enemy in an undeclared CyberWar. For more than a decade, he was developing web applications in various industries, like betting, hospitality, insurance, and projects for the European Union.
Academically, he graduated from the Department of Electronic & Computer Engineering of the Technical University of Crete(TUC), while he holds 2 postgraduate diplomas in Engineering Management (TUC) and in Information Systems (UOA).
He thinks that a driver that drives in the same way for 30 years remains stagnant, repeating the same mistakes without being aware of them, while a driver that races learns from the competition and evolves. Therefore, he joins competitions occasionally to improve himself. During that romantic journey, he found himself lucky enough to be part of the winning team of the Threat Modeling Connect Spring 2023 Hackathon, member of the runners-up team (2nd) of the Startup Weekend 2012 (Athens Microsoft Facilities), as well as being 1st in Web Applications Design and Development and Top50 overall during a written exams competition ran by the Supreme Council for Personnel Selection of Greece(>15000applicants, 2022).
What is logging, in one word? Cost. Undeniably.
Development cost. Performance cost. Operational cost. Maintenance cost.
But is logging truly costly, or merely expensive?
As with education, the answer depends on outcomes, and those outcomes only become visible over time.
By approaching logging the way we approach learning, we can transform a controversial expense into an operational necessity.
We employ a discreet but continuous source of insight across business, development, architecture and design, security, and incident response.
When designed intentionally, logs tell stories about both system and human behaviors.
They reveal how our services actually run and where assumptions quietly fail.
In that sense, observability through logging is not a sunk cost, but a high-return investment in understanding and decision-making, potentially offering a multi-aspect business intelligence solution.
In this talk, we explore how to extract real value from logging by mapping it to three universal dimensions of learning:
-Things we know that we know
-Things we know that we do not know
-Things we do not know that we do not know
What is logging, in one word? Cost. Undeniably.
Development cost. Performance cost. Operational cost. Maintenance cost.
But is logging truly costly, or merely expensive?
As with education, the answer depends on outcomes, and those outcomes only become visible over time.
By approaching logging the way we approach learning, we can transform a controversial expense into an operational necessity.
We employ a discreet but continuous source of insight across business, development, architecture and design, security, and incident response.
When designed intentionally, logs tell stories about both system and human behaviors.
They reveal how our services actually run and where assumptions quietly fail.
In that sense, observability through logging is not a sunk cost, but a high-return investment in understanding and decision-making, potentially offering a multi-aspect business intelligence solution.
In this talk, we explore how to extract real value from logging by mapping it to three universal dimensions of learning:
-Things we know that we know
-Things we know that we do not know
-Things we do not know that we do not know
What if your engineering team could move at the speed of AI – without sacrificing quality, security, or control? Enter the Agentile Team: a lean, AI-powered, and platform-enabled evolution of Agile, designed to amplify human creativity.
In this session, we’ll explore how Agentile teams codify architectural tradeoffs (security, capacity, cost) into specs, templates, and guardrails, enabling rapid experimentation and smarter decision-making from day one. Drawing on real-world experiments and platform engineering principles, Suzanne will share practical strategies for developers and platform engineers to thrive in this new era of agentic, high-velocity software delivery.
Most developers use AI coding tools like a search engine: type a question, hope for a good answer. But the teams getting real results are engineering the context: configuring system prompts, structuring project knowledge, and managing the AI’s working memory like a first-class architectural concern.
This workshop is built around a real coding project. Participants will receive a small application to build – and throughout the session, they’ll apply each technique as they learn it, experiencing firsthand how context engineering transforms their AI’s output quality.
We’ll cover:
– **The context window** – what tokens are, what counts as context, and why your AI gets worse mid-conversation (context rot)
– **Basic prompting techniques** – prompt engineering is no longer as important, but can still improve your results
– **System prompts as project configuration** – set up instruction files (CLAUDE.md, copilot-instructions.md) that make every AI interaction project-aware
– **Grounding techniques** – anchor AI output in real data instead of letting it guess, using file uploads, documentation references, and structured retrieval
Each concept is immediately put into practice on the project – so by the end, participants will have both a working application and a repeatable playbook for getting better results from any AI coding tool.
Targeted to software engineers, bring a laptop with an AI coding assistant installed.
Nobody’s talking about this: MCP isn’t just another way to build chatbots. It’s the bridge we’ve been missing between AI reasoning and real-time data systems.
Teams build AI applications that work great in demos but fall apart with production data. Your agents analyze historical reports but can’t tell what’s happening in your Kafka streams. They’re blind to schema changes and disconnected from events that matter to your business.
Instead of treating streaming platforms like black boxes, you expose them directly to your agents via MCP protocol. Suddenly, your AI doesn’t just read about data—it lives inside your data flows.
Learn what becomes possible when you stop thinking about AI as an external service and start treating it as part of your streaming architecture. We’ll build systems where agents subscribe to real-time events, reason about evolving schemas, and make decisions that ripple through your data platform.
Architectural Katas were created by Ted Neward to solve a problem: architects rarely practice their craft. Most people design systems only a handful of times in their careers, so they never develop the judgment that comes from repetition.
The kata format creates those practice opportunities. Teams work on realistic architectural problems, make design decisions, and defend those decisions when challenged. The learning happens when you see other teams solve the same problem differently and understand the assumptions behind each approach.
We run these sessions at Epignosis because our engineers need that practice too. It’s one of the few ways to develop architectural judgment outside of production systems.
This workshop is for anyone who wants that practice. You might be a developer learning to think architecturally, a tech lead seeking feedback on your decisions, or an architect wanting more repetitions. The format works because it forces clear articulation and exposes you to alternatives.
Most features arrive late, break things, and hide complexity until it hurts. Branch deployments are a rigged game: merge early and you break things, merge late and integration becomes a nightmare. Whatever you do, you lose. The only way to win is to stop playing.
Enter Elephant Carpaccio, a software development exercise that teaches vertical slicing, incremental delivery, and how to keep software deployable at all times. Instead of delivering the whole elephant at once, you learn to carve it into the thinnest possible slices: each one small, end-to-end, deployable, and providing visible progress. The goal isn’t to finish the feature. It’s to learn how to evolve software safely.
In this hands-on workshop, you’ll practice exactly that. You’ll feel the difference between fat slices and thin ones, and walk away with a technique you can apply the very next day.
If you’ve got PTSD from releases, this one’s for you.
Disclaimer: No actual elephants will be harmed during this workshop
