The Netherland's Shortest Hackathon

Hands-on technologist with a deep understanding of software development across the whole stack, cloud technologies, DevOps practices and AI.

AI, GenAI, ML, LLMs, MLOps

Transformer model for robust specialised postal address parsing. Chatbot for researching best areas to live in the UK. Centralisation of company comms with AI. AI Photobooth.

Founder @fiberplane; API Debugging IDE. Chief Goose for the https://honc.dev stack. Investor in teams solving hard problems @nphardvc

TypeSCript API, Observability, Debugging and Developer Tools.

Fiberplane - API developer portal

Architect of the Matrix; expert in simulated realities and AI-driven environments. Designed the simulation to maximize human contentment through controlled parameters and systemic stability.

I am continually seeking innovative approaches to human factor integration and exploring more efficient methods of reality management.

One current project involves a deep dive into understanding and managing the impact of anomalous individuals on the stability of the Matrix. This requires developing new predictive models and adaptive countermeasures to maintain system equilibrium in the face of such deviations.

Laurynas Keturakis is a mid-level software/product engineer currently at Fiberplane, working on building agents and agent platforms. Prior to Fiberplane he worked at TNW in product and program roles (Product Engineer / Product Manager / Program and Content Manager) and has held research and policy-focused roles including a fellowship at the Embassy of the Republic of Lithuania and analyst positions at the Vilnius Institute for Policy Analysis. He holds a BA in International Studies from Leiden University. His background spans product engineering, web development (Joomla, WordPress, Jekyll), content/program production, policy research and data visualization, positioning him as an engineer with strong product and research sensibilities.

👨‍💻 AI Research & Engineering @GroqInc. Ex-founder of open source data ETL tool. I like neural networks.

Autonomous Agents, silicon <> machine learning interaction, quantum machine learning (first need low-error qubits :), automation, machine intelligence, philosophy of science/life, investing/wealth, doing good

Making Groq go faster & making it higher quality 🚀 AI terminal utility: https://github.com/ricklamers/shell-ai

Rick Lamers is a senior technical AI researcher/engineer currently at Groq, based in Amsterdam. He previously worked at Definitive Intelligence (acquired by Groq) and was the technical co‑founder of Orchest, a data workflow orchestration startup for ELT and ML pipelines (raised $4M, sold IP and returned remaining capital). Earlier roles include data science and web development internships and positions (Datlinq, Keadyn, MediaMonks). Academically he completed MSc coursework in Computer Science at Delft University of Technology (left before formal graduation), holds an MSc in Strategic Entrepreneurship from Rotterdam School of Management (Erasmus University) and a BA from HAN University of Applied Sciences. He is a hands‑on builder with experience in ML/model engineering, data engineering, web scraping, and product/engineering leadership in startups.

I embarked on my tech journey at 15, landing a job at the US/French startup Neptune.org during the dot-com boom. After the bubble burst, I pursued and earned a BSc in Economics and Management. Following graduation, I gained three years of experience in bankruptcy management, playing a pioneering role in creating one of the globally first e-bankruptcy system. My career then shifted back towards technology, specifically in the edTech sector, joining the team that developed one of the first educational platform in the US (which was also the first COPPA compliant app). Four years ago, I took a career break and obtained a Master's Degree in Data Science and Society from Tilburg University. Currently, I am a co-founder of a small startup, focusing on R&D&I for AI applications in edTech.

I posses deep knowledge and a keen interest in a wide range of fields. My interests spans various aspects of AI implementation, machine learning, deep learning and natural language processing. I am also interested in advanced time series analysis using tools from complexity science, as well as navigating data, AI and IP regulation.

R&D in AI for edTech. Creating a PoC for automated detection of pronunciation errors. https://www.pioneertown.ai/ R&D in embodied AI at Manus-meta as AI lead. https://www.manus-meta.com/