Current focus
COBOL development on enterprise-scale mainframe systems, with attention to structure, reliability, maintainability and the realities of long software lifecycles.
Andy Valkenburg
Understanding systems, from Mainframe to AI.
Software engineer, jazz musician, and long-time experimenter with technology — from COBOL on large-scale mainframe systems to automation, AI workflows, and startup building.
About
Curiosity first.
I’m a software engineer with one foot in modern stacks and one in long-lived critical systems. By day I work as a COBOL developer at the Dutch Tax Authority, building and maintaining large-scale mainframe systems with z/OS, ISPF, IDz, Zowe and Robot Framework.
I’m developing as a technical depth engineer: someone who likes getting below the surface, understanding how things really work, and improving them from that reality rather than from fashion.
Alongside that, I’m building Recrugent.com as a startup — a product-led approach to recruitment built around how teams actually work, not just how CVs are filtered.
Software engineering
Legacy and modern, both taken seriously.
Broader stack
Experience with Java, PHP, Symfony, Laravel, Docker and agile workflows. Comfortable moving between older and newer environments.
Engineering lens
Influenced by practical software engineering ideas from Clean Code, The Pragmatic Programmer and Team Topologies — applied in real systems, not as slogans.
Jazz musician
Listening, timing, interplay.
Alongside software, I’ve continued working as a jazz musician. On recordings connected to O.A.P. Records, I appear as a double bassist in projects such as Solar, Raisin Bread and When We Kiss.
The descriptions around those releases consistently point to ensemble playing, pocket, warm tone, and tightly woven interplay — the kind of musical role that serves the whole while still keeping an individual voice.
That same instinct carries into software: timing matters, space matters, and systems work best when the parts actually listen to each other.
Experimentation timeline
A pattern of exploring early.
Early 2000s
AI agents and intelligent systems
Experimenting with AI concepts and agent-like behavior long before the current wave.
2009
Decentralized money
Exploring peer-to-peer digital money as an answer to closed banking systems.
2012
Crypto becomes real
Watching those earlier ideas materialize in the rise of crypto and decentralized systems.
Since 2020
Home Assistant
Designing home automation setups and thinking in sensors, flows, feedback loops and system behavior.
Since 2025
AI-driven organizations
Exploring AI workflows, startup systems, and the idea of a zero-human company.
How I work
Complexity is not a reason to back away.
I tend to dive into complexity, figure out what’s really going on, and build on top of that reality.
Whether that means understanding a mainframe workflow, shaping a product idea, wiring up home automation, or turning an abstract concept into a working startup, the common thread is the same: break it down, make it real, improve it.
“From mainframe systems to AI workflows, the thread is not trend-chasing — it’s understanding systems deeply enough to build something useful.”