Verifiable
What you can open yourself, and what stays under NDA
The invoicing pipeline
Outbound and inbound invoices for an online job marketplace run in production between SAP Business ByDesign and the Peppol network. Inbound arrives over two parallel routes, a webhook and a mailbox, and both end in the same layer.
EN 16931 · Peppol BIS 3.0
client under NDA
The agent on this page
It answers questions about this CV. On a subject-matter question it does not guess: it consults a second agent over the open A2A standard on its own initiative, and marks that answer as coming from elsewhere.
open-bridge, the open-source layer
The generic scaffolding behind this way of working is public under MIT: operating manual, skills, rules, agent runtime. Mandatory checks run before every merge, one of them a scan for leaked content.
The translation gateway
A stateless translator exposes the same agents to MCP clients. Three tools, no model of its own, no logic of its own, and no state carried between two calls.
MCP to A2A
open to MCP clients, anonymous gets lookups only; not a page you can click
Positions
Engagements and employment, most recent first
AI Test Automation Engineer · Building the AI Test Automation Process
AI-driven test automation for one of the group's customer portals: building the complete process, from deriving the test cases to a green CI pipeline.
Key Responsibilities
- Test orchestrator: a chain of AI building blocks with a fixed log schema, its own model tier per block and usage tracking, packaged as a reusable command for the team
- Architecture rules for the test code base: derived from a multi-stage analysis with several AI agents, independently cross-checked and documented
- Architecture check for generated test code: detects violations of the team's style guide and fixes the minor ones on its own
Key Responsibilities · Tools & Technologies
Key Responsibilities
- Calibrated comparison runs: AI-generated E2E tests compared on cost, usage and conformance to the standard, across several model tiers
- Stable pipeline: found and fixed the cause of hanging tests (a third-party element was still missing while the page loaded)
- Coverage: four test areas of a portal module end to end, from deriving the test cases to a green pipeline
Tools & Technologies
- Testing: Playwright, TypeScript, Angular code base
- AI: Claude Code (several model tiers), GitHub Copilot CLI
- CI/CD & tooling: GitHub Actions, Sonar, Jira with Xray, Confluence, SAFe
LLM Infrastructure Architect & Automation Engineer
Development of LLM-orchestrated Enterprise Development Ecosystem: Fully integrated system for knowledge management, project automation, and development workflows with Claude, Gemini, and OpenAI GPT.
Key Responsibilities
- Open-Source Agent Infrastructure: open-bridge under the MIT licence, public at github.com/bks-lab/open-bridge, with a live demo site. The generic CORE layer (agent runtime, MCP gateway, skill tree, promote flow with a content-leak gate in CI) grows out of my own instance and is published upward by scope, with its own test suite and continuous releases since June 2026.
- Harness engineering: what an agent achieves is decided mostly outside the model: context, tool selection, permissions, state across sessions, verification. That layer is measured here rather than estimated. What a session loads before it answers the first word carries a declared ceiling that a CI step checks in bytes; rules that rarely bite load on their trigger word instead of at start-up; the project registries sit in context as a card and are fetched one entry at a time; a further check reports what exists in the tree but is no longer reachable from any file a session loads, and attacks itself to prove it still catches things. The tools behind this are public and run in public CI
- Data separation as architecture, not as agreement: separate instances per client, a rule forbidding access between instances, and a fail-closed contract for materialising shared configuration (the sync aborts rather than writing on doubt). Protection against data leakage at three points: pre-commit hook, pre-push hook and three validators in CI. Plus an adversarial simulation that attacks the protection itself on a schedule, as its own CI job in a sealed sandbox
Key Responsibilities · Tools & Technologies
Key Responsibilities
- A2A Agent Network: an a2a-sdk server with a local claude backend, running on a runtime adopted from open-bridge. Three agents (person, company, OSS project) consult each other on read-only edges, fronted by a stateless MCP-to-A2A gateway so MCP-only clients can reach them. Agent Cards at protocol version 1.0, JSON-RPC 2.0. Around 4,600 lines of Python with 98 automated test cases, built as a team effort (four further contributors)
- OpenTelemetry-based telemetry: logs, metrics and traces over OTLP into a managed sink, with a fixed field convention and naming scheme, a capped ingest key and read rights separated per client (measured as an access cut, not documented as an intention). Honest maturity: the log path is in operation, metrics and traces are wired and not yet accepted
- Human gate on four autonomy layers: what an agent may change about itself is split into four layers (context, skill files and rules, user profile, model weights), each with an explicit human gate. Proposals go through a dedicated folder with a schema and a review path instead of taking effect silently. The EU AI Act is therefore not just workshop content here but my own operating practice
- Specification and verification design: before building, a fixed sequence runs through requirement, design and verification plan. Every acceptance criterion is mapped to the strongest available check, in this order: deterministic test before external signal before model judgement, together with the gate strength. This is where quality engineering and AI development are the same discipline
- Git Wiki Transformation: Migration of Confluence knowledge base to structured Git-based wiki with hierarchical organization and multi-repository architecture (submodules for customer projects)
- MCP servers and protocol choice: Built two Model Context Protocol servers in Python, one for the wiki hierarchy (navigation, content discovery, SharePoint integration), one for the company website content. Delivered MCP training. In my own work, MCP is used only where it beats skills, REST or A2A, since most MCP servers are not effective in everyday use
- Google ADK (earlier stage): the first version of the agent network ran on the Google Agent Development Kit with LiteLLM. Replaced in July 2026 by the a2a-sdk server on our own runtime; the ADK and tool-integration experience from that stage stays
- GitHub Project Automation: LLM-driven issue management with 7-mandatory-field system, automatic categorization, smart repository mapping, and review queue management
- Development Workflow Automation: GitHub Actions workflows for fully automatic issue-to-PR transformation (assignment → feature branch → implementation → code review → PR)
- Self-Documenting System: LLM automatically writes project status, meeting protocols, and issue updates back to Git wiki; closed loop of wiki reading → work execution → results documentation → Git commit with structured logging
- Work-time capture: commit-based work time analysis with automatic project assignment. The first stage ran against Clockify; since July 2026 it is being rebuilt as a private registry of semantic conventions on OpenTelemetry Weaver, with three layers (raw observation, derived block, billable time), canonical JSON serialisation per RFC 8785 and an integrity profile per OCSF
- Claude Code Plugin Ecosystem: 120 skills in the productive instance, discovered alike by Claude Code, Codex, Copilot CLI and Cursor through committed symlinks: log analysis, deployment verification, incident handling, email management, meeting transcription (104 filed meetings), PDF/certificate generation, SharePoint integration. Every skill carries one of four scope tiers (core, org, personal, user) checked by a CI validator; what may be published outward depends on it
- Context Orchestrator: central multi-repo control system with a three-way split registry (instance base, shared org fragment, personal fragment), so company data and personal data can be distributed separately. It carries repos, customers, infrastructure and skills, plus automatic cross-repo navigation and structured work tracking with archiving
- Hook-based Permission System: Smart Guard with project-specific security rules for Git operations: branch protection, secret detection and deployment gates
- Production Operations E-Invoicing: ongoing management of an e-invoicing platform for a leading online job platform (under NDA): automated incident management, log analysis, weekly reporting and go-live tracking
- Peppol expansion of the same platform (from 06/2025): separate services for outgoing and incoming invoices (Azure Functions) next to the existing processing, connected to a certified Peppol access point; the SAP ByDesign interface built over SOAP instead of REST after a technical deep dive with the SAP partner; an extra inbound channel by mailbox for suppliers without Peppol (PDF, ZUGFeRD, XRechnung); operated through managed identity and Key Vault in separate pre-production and production environments
- Self-Operated Infrastructure: 50 launchd services on the central host, 18 devices in the registry, reachable over Tailscale rather than open ports. Backups follow 3-2-1 as a declared topology: 10 sources, 5 targets, 16 pipelines (restic/rclone to NAS), with actual state reconciled against intent.
Tools & Technologies
- LLM Orchestration: Claude (primary), Google Gemini, OpenAI GPT, Model Context Protocol (MCP), Google Agent Development Kit (ADK)
- AI Development Platform: Claude Code, Plugin Architecture (Skills, Hooks, Commands, Agents), YAML/Markdown Configuration; Cursor before that
- Multi-Agent: A2A Protocol 1.0, a2a-sdk, Agent Cards, MCP-to-A2A gateway, JSON-RPC 2.0, SSE Streaming
- Backend: Python 3.13, FastAPI, uvx Distribution, Git Submodules
- Automation: GitHub Actions, GitHub GraphQL API, gh CLI
- Integration: SharePoint API, Microsoft Graph, Exchange Online, Elasticsearch, Kibana, OpenTelemetry/OTLP
- Operations: Cloudflare (Workers, Pages, R2, DNS), Tailscale, launchd, restic/rclone
- Cloud: AWS, Google Cloud (alongside Azure)
- Development: Bash Scripting, jq, Docker, Multi-Agent Systems; orchestrated repos span Python, TypeScript, Rust and Go
Senior Quality Engineer · Test Automation and Monitoring
Quality Engineering for an enterprise platform for AI-powered document processing in medical device certification (MDR/IVDR) with AI chat integration and data pipeline automation.
Key Responsibilities
- BDD API Test Framework: Development of comprehensive test framework with Python/Behave, self-healing authentication, HTML report generator with embedded API responses
- E2E Test Automation: Playwright E2E test suite for complete user journey (Setup -> Upload -> Transformation -> Download) with 500 error handling and route mocking
- Performance & Monitoring: Development of Azure Monitor Workbooks (QA Live Testing Companion, Error Investigation Assistant) with KQL for end-to-end monitoring
Key Responsibilities · Tools & Technologies
Key Responsibilities
- Bug Analysis & Quality Intelligence: Implementation of comprehensive bug tracking system with WIQL queries, automated dashboards, and executive PDF reporting
- Pipeline Integration: Test automation in Azure DevOps CI/CD pipelines with HTML report upload to Azure Test Results
- AI-Powered Automation: Development of automation skills for workflow optimization, bug analysis, and incident response with measurable time savings
- AI-Driven Test Processes: Integration, E2E and API testing set up as end-to-end processes with AI agents, plus AI-assisted incident analysis
Tools & Technologies
- Testing: Behave, Playwright, TypeScript, Python, pytest, Page Object Model, Fixtures
- Monitoring: Azure Monitor Workbooks, KQL, Application Insights, Log Analytics
- Backend: FastAPI, Python, Pydantic, SQLModel, Azure Functions, Azure Service Bus
- Frontend: React, TypeScript, Vite, TanStack Router
- AI Integration: Azure OpenAI (GPT-4o), LangChain, Azure AI Search, Embeddings
- DevOps: Azure DevOps Pipelines, Git, Docker, Azure Blob Storage, Poetry
- Agentic Coding: GitHub Copilot CLI
AI-driven QA Environment for Energy Infrastructure
QA Leadership for EU-wide Battery Swap Infrastructure: AI-driven simulation tool for battery swap station network with energy infrastructure integration
Key Responsibilities
- QA concept, design and implementation for AI-driven simulation of EU-wide infrastructure
- QA framework development for inhouse AI server infrastructure
- Proof-of-concept for automated testing of AI-driven simulations
Key Achievements
- Established QA methodology for AI-driven infrastructure simulation
- Created testing framework for energy sector critical systems
- Validated proof-of-concept with measurable reliability improvements
Energy Sector Connection · Technical Stack
Energy Sector Connection
- 50 Hertz Participation: 50 Hertz (Elia Group subsidiary) participated in research project eHaul, the predecessor of AkkuSwap
- Direct energy sector experience with critical infrastructure quality requirements
- Context of critical energy infrastructure (transmission-grid environment)
Technical Stack
- Infrastructure: Linux, Docker, Azure OpenAI
- Automation: pytest, AI code generation integration patterns
- Monitoring: Grafana, Azure Monitoring
- Energy Systems: Battery swap infrastructure, grid integration simulation
Technical Lead & AI Automation Architect
Technical lead & development: Design and implementation of a scalable automation solution for processing e-invoices and PDF invoices fetched from a mailbox of a leading online job platform (under NDA). Full responsibility from requirements analysis through implementation to production go-live.
Focus areas
- Workflow automation: Extraction, analysis and classification of incoming invoices using Python and Azure Functions.
- E-invoice classification & data extraction: Full processing in accordance with EU standard EN 16931 (ZUGFeRD, XRechnung, Factur-X), including structural and content parsing.
- Peppol Network Integration: Connection to European e-invoicing network through a certified Peppol Access Point for automated invoice receipt and dispatch with UBL/CII formats.
Focus areas · Tools & technologies
Focus areas
- SAP ByDesign Integration: Automatic transfer of validated invoice data to SAP ByDesign for seamless ERP integration.
- Hexagonal Architecture: Domain-driven design with Ports & Adapters for maximum testability and interchangeability of infrastructure components.
- Salesforce integration: Forwarding prepared invoice data via email to the downstream system for Salesforce import.
- Auditing & logging: Comprehensive documentation of all processing steps plus storage of original email content in the processing log.
- Outlook management & SharePoint archiving: Automatic moving and categorising of emails into predefined Outlook folders; archiving of original and generated invoice documents via Microsoft Graph API.
- Monitoring & logging: End-to-end real-time monitoring with Kibana, including alerting and dashboard creation.
- Team coordination: Managing the developer team incl. code reviews.
- AI Workflow Automation: Development of AI skills for automating task tracking, issue management, and project documentation
- Intelligent Documentation System: Automated wiki synchronization with git commit analysis and natural language documentation generation
- Automated Status Reporting: AI-driven email updates with automatic project progress analysis
- MCP & A2A Protocol Implementation: Next-generation AI protocols for tool integration and multi-agent communication
Tools & technologies
- Azure Functions: Serverless orchestration of automation workflows.
- Python: Core logic for data extraction, classification and integration with automated CI/CD processes, packaging, and comprehensive unit and integration tests for quality assurance.
- E-Invoicing: Peppol Network, Access-Point-API, ZUGFeRD/Factur-X, XRechnung, UBL 2.1, CII
- ERP Integration: SAP ByDesign, Salesforce
- Microsoft Graph API: Access to Outlook mailboxes and SharePoint libraries.
- GitHub: Version control, CI/CD pipelines and collaborative development.
- Kibana: Monitoring, log analysis and performance dashboards.
- Streamlit: For developing an interactive web application for visualization.
- AI Automation: Claude AI, Custom Skills Development, Git Analysis, Natural Language Processing
- Protocols: Model Context Protocol (MCP), Agent-to-Agent (A2A), JSON-RPC 2.0
AI Engineering Lead & ML Solutions Architect
Project management & technical lead: Development and deployment of an AI-driven email bot to automate customer communication, AI-assisted processing of incoming emails and triggering of follow-up activities in existing SAP systems. Responsible for end-to-end project coordination and team management from idea to implementation.
Focus areas
- Development of ML models: Design and training of specialized models for effective email classification, implemented via Azure Functions.
- API integrations: Seamless connection to Microsoft Outlook 365 via Microsoft Graph API and to SAP systems for customer data checks.
- Process automation: Automatic moving of emails based on classification and specific business rules, including complaint handling.
Focus areas · Tools & technologies
Focus areas
- DevOps and monitoring: Implementation of CI/CD pipelines and use of Kibana for monitoring.
- Development of a Streamlit-based user interface: Improved testability and visualization of process results.
- Team coaching: Technical guidance for developers with regular code reviews and problem-solving sessions.
Tools & technologies
- Azure Functions: For serverless application architectures and ML model execution.
- Python: Main programming language for the email bot and ML models.
- Microsoft Graph API: For accessing and processing emails in Microsoft Outlook 365.
- SAP API: For querying customer data and communicating with SAP systems.
- GitHub: For version control, CI/CD pipelines and collaborative development.
- Kibana: For real-time monitoring and system performance analysis.
- Streamlit: For developing an interactive web application for system monitoring.
Platform Quality Architect (CI/CD, Monitoring, Automation)
Test management & coordination, as well as introduction of CI/CD with quality-gate setup. Acting as cross-team Quality Lead: onboarding, guidance, consulting and training for the introduction of quality metrics and test automation within the pipeline across teams.
Result: Real-time sprint-quality transparency via Grafana dashboards, quality-gated releases in the teams' CI/CD pipelines: data-driven release decisions replacing manual data gathering.
Key responsibilities
- Design and implementation of functional and technical dashboards with Grafana for real-time quality measurement
- Documentation of quality metrics covering the measurable sprint progress
- Design and setup of CI/CD pipelines for multiple development teams (backend + frontend)
Key responsibilities · Tools
Key responsibilities
- Introduction of quality gates to safeguard quality within the CI/CD pipeline
- Adoption of Gauge (BDD)
- Roll-out of Playwright and integration into the existing CI/CD pipeline
- Functional and technical incident analysis
- Consultancy, design and implementation of solutions for quality-related issues
Tools
- IntelliJ / Visual Studio Code
- Java / Kotlin / JavaScript / TypeScript
- Playwright / Gauge / Karate
- Python for processing and analysis of test and reporting data
- CI/CD / GitHub (reusable workflows)
- Helm / Containers
- JIRA / Confluence
- Grafana
- Behaviour Driven Development
- Consumer-Driven Contracts (Pact.io)
Founder: Boiman.Solutions and QualityCluster
Set up his own consultancy Boiman.Solutions and the quality engineering community QualityCluster, a group of quality engineers working towards more quality through a higher degree of automation.
DevOps Quality Lead & Dashboard Architect
Test management, test coordination, test automation, agile (Kanban, Scrum, SAFe): Coordination as PO of a cross-team QA team including cross-team onboarding, support, consulting, training
Key responsibilities
- Built the production load test for a bahn.de feature: load scenarios, test setup, execution and analysis
- Load and performance tests within CI/CD with Gatling / JMeter, bottleneck analysis using Kibana, Graylog, Grafana and Instana
- Agile quality assurance through the design of quality gates in the CI/CD pipeline
Key responsibilities · Tools
Key responsibilities
- Design and implementation of functional and technical dashboards with Kibana, Graylog, Grafana, Instana & Elastic Search
- Introduction of domain-specific logging for microservices to transparently track calculations and service interactions
- Documentation of quality metrics on the progress of measurable sprint quality
- Design and setup of CI/CD pipelines for data tests
- Functional and technical problem analysis
- Consulting, design and implementation of solutions for quality-related issues
- Setup of Junit, unit tests and integration tests, among others with Java Cucumber
- Development of a hybrid app for presenting (reviewing) results on a web or mobile platform
- Coordination of integration tests between the involved teams
Tools
- IntelliJ
- Java
- Cucumber / Cypress
- JMeter / Gatling
- CI/CD / GitLab CI / Jenkins
- Helm / Docker
- JIRA / Confluence
- Kibana / Grafana / Instana / Graylog
- AWS
- Behaviour Driven Development
- Consumer Driven Contracts (Spring Cloud Contract)
- Ionic (hybrid app)
- Selenium
Performance Engineering Lead & Test Architect
Load and performance tests and analysis (test manager, test designer, analyst): Development, execution and analysis of load and performance tests
Key responsibilities
- Setup and execution of load and performance tests over HTTP, WS, REST, MQ and JMS
- Analysis of results & performance logs
- Documentation in the form of test concepts, analyses, management reporting and wiki documentation
Key responsibilities · Tools
Key responsibilities
- Status reports
- Customer consulting
- Requirements management
Tools
- Visual Studio
- Eclipse
- JMeter
- SoapUI
- Git
- JIRA / Confluence
- Excel & Access VBS
- Interfaces: HTTP, WS, REST, MQ, JMS
Senior iOS Developer & Mobile Architect
Senior iOS Developer: Further development of the rebuilt version of Deutsche Telekom's Customer Center App, extension with new features for IFA.
Key responsibilities
- Swift
- iOS 8
- Requests & responses to backend
Key responsibilities · Tools
Key responsibilities
- Error handling
- iPad / iPhone
- Scrum
Tools
- Xcode
- Git
- JIRA
Quality Assurance Lead & Test Automation Architect
QA, test management, test automation, requirements engineering: A total of 5 projects were supported as QA & test manager and successfully implemented
Projects
- SOM (05/2009-07/2010): management and overview of OrgUnits; test management and requirements management
- SIPCA (07/2010-09/2010 and 07/2014-03/2015): management system for employee annual targets and bonus calculation; change request management
- STM (09/2010-03/2012 and 05/2014-07/2014): application and travel expense recording (Frontend: Web / Backend: SAP); test management and requirements management
Projects · Key responsibilities · Tools
Projects
- PATAC (07/2012-08/2012): test automation
- GPM2 (09/2012-05/2014): share bonus program for employees (Frontend: Web / Backend: JBoss); test automation
Key responsibilities
- Creation of technical test concepts and test plans
- Defect tracking
- Management of CRs, communication between customers and developers
- Creation, maintenance and scheduling of test automation
- User acceptance tests
- Training of new testers and test automation engineers
- Support as test manager after project completion, in steady-state operation
- Setup of acceptance tests
- Transfer of functional specification and detailed specification to Quality Center
- Monitoring of implemented requirements against the detailed design spec
Tools
- HP ALM
- HP UFT
- HP QC
- Quick Test Pro
Performance Test Engineer & Load Testing Specialist
Load and performance tester: The goal of the project is the design and development of LoadRunner scripts for load testing a bundle of approx. 20 J2EE applications in a banking portal
Key responsibilities
- Creation of test scripts in LoadRunner with the http protocol
- Execution of load tests and analysis of results
- Monitoring and reporting
Tools
Tools
- HP LoadRunner 8.1 and 9.5
Performance Test Engineer & Quality Consultant
Load and performance tester / tester: Various projects, predominantly load & performance tests
Key responsibilities
- Creation of test scripts in LoadRunner with the http protocol
- Execution of load tests and analysis of results
- Monitoring and reporting
Clients and systems
- British Telecom (Munich): number porting system, load tests over HTTP and SOAP
- Mobiliar (Bern): insurance system with Java applet and terminal front ends
- DB Systel (Frankfurt): delay notification for rail passengers, load tests with simulated XML data
- Sparkassen Informatik: banking portal of more than 30 J2EE applications on WebSphere (AIX and Sun)
- Loyalty Partner (Munich): Siebel call centre application
- Telekom (Darmstadt): document management system and a media system for a mobile operator
- Itelium and Deutsche Post: load on point-of-sale systems
- Postbank: transfer archive and client integration software
Tools
Tools
- LoadRunner
Projects
Own work and solutions built for clients
E-Invoicing Automation Platform
Production E-Invoicing Pipeline (Peppol/EN 16931)
Core Features:
- Peppol Network Integration: connection to the European e-invoicing network through a certified Access Point
- Multi-Format Support: ZUGFeRD, Factur-X, XRechnung, UBL 2.1, CII (EN 16931 compliant)
- ERP Integration: Automatic transfer to SAP ByDesign with validation and error handling
- Hexagonal Architecture: Domain-driven design with Ports & Adapters, seven repositories
- More test code than production code: around 46,700 lines of application code against 81,600 lines of tests, roughly 2,900 automated test cases. Every one of the seven repositories enforces a minimum test coverage in CI, 75 percent in the core service
- Format coverage: ZUGFeRD and Factur-X from 2.0.1, XRechnung in UBL and CII syntax, UBL 2.1, PDF/A-3 with embedded XML, plus a format detector that tells the variants apart by namespace
- Dual-Channel Inbound: access-point webhook (push) + email inbox (pull) for redundant processing
Impact: Production system: Peppol connectivity per EN 16931, automated inbound and outbound invoice processing through to the ERP. The outbound route runs 13 processing steps from the SAP document to Peppol delivery, each independently testable.
Python · Azure Functions · Peppol · Peppol Access Point · SAP ByDesign · ZUGFeRD · Factur-X · UBL · Hexagonal Architecture
24/7 Automated Legacy Migration Validator: Dual-Run Quality Engineering
Enterprise Legacy Transformation with End-to-End Quality Assurance
The Challenge: Complex mainframe price calculation with millions of combination possibilities needed secure migration, without quality loss or data errors.
The Solution: 24/7 Dual-Run Validation System with intelligent deviation analysis
- Continuous Testing: Randomly generated tests across all variations around the clock
- Real-time Monitoring: Live dashboard with deviation detection on every deployment
- Complete Traceability: Every deviation uniquely logged with technical and business context
- Automated Root Cause Analysis: Direct access to calculation paths and error sources
- Quality Intelligence: Kibana dashboards for end-to-end quality overview
Result: Secure migration without data loss, 24/7 validation across all combinations and full transparency over migration status
Java · Cucumber · Kibana · Graylog · Elasticsearch · Container · CI/CD · Mainframe · Dashboard Engineering · Test Automation
Agent mesh and MCP-to-A2A gateway
Three agents, one translator, one open protocol. The agent on this page is one of them.
- Problem: An agent that only holds its own knowledge guesses at everything outside it. Loading it up with someone else's knowledge does not make it smarter, only more expensive and harder to check.
- Solution: Three agents, each with its own subject, a person, a company and an open-source project, consult each other over the open A2A protocol, read-only. In front of them sits a stateless gateway that offers the same agents to MCP clients as three tools, with no model and no logic of its own.
- Result: A subject question gets passed on instead of guessed, and the borrowed answer is marked as borrowed. The agent card is publicly retrievable, and the generic framework behind it is open under MIT.
Python · a2a-sdk · A2A Protocol 1.0 · Agent Cards · JSON-RPC 2.0 · SSE Streaming · MCP · FastAPI
Quality Dashboard · Real-time Overview
End-to-end solution for real-time quality monitoring: the test tools of several teams and environments under one surface, plus multi-source integration (Pipeline, LeanIX, Jira, Confluence) for automated PDF reports with open issues, bugs, and technical debt.
Grafana · Elasticsearch · Python · CI/CD · Playwright · Jira API · Confluence API · LeanIX · PDF Generation
AI-driven Test Automation
Guideline-based AI agent in the IDE that generates tests directly from Jira stories.
- Problem: Deriving test cases from a story is manual work, and it comes back with every story. A language model without constraints invents steps and selectors the application does not have.
- Solution: The agent reads the story over the Jira API and writes the test from it. The project's own conventions, page objects, naming rules and permitted selectors, sit beside it as a rule file and bound what it may produce.
- Result: The test comes out in the style of the existing Playwright project. Typing an empty file turns into reviewing a draft.
Python · OpenAI GPT-4 · Playwright · IDE Integration · Jira API
AI Context Orchestrator: Multi-Repo Development Platform
Central Control System for Enterprise AI Development
Core Features:
- Context Orchestrator: a three-way split registry (instance base, shared org fragment, personal fragment) for repos, customers, infrastructure and skills, so company data and personal data can be distributed separately
- One skill tree for every tool: discovered alike by Claude Code, Codex, Copilot CLI and Cursor through committed symlinks. Log analysis, deployment verification, incident handling, email management, meeting transcription, PDF/certificate generation, SharePoint integration
- Hook-based Permission System: Smart Guard with project-specific security rules (branch protection, secret detection, deployment gates)
- Structured Work Tracking: Automatic documentation with daily/weekly archiving and cross-project Kanban board
- Cross-Repo Automation: Seamless navigation and operations across customer, partner and internal repositories
- Open-source layer: three-tier architecture. The generic CORE layer is public as bks-lab/open-bridge (MIT, with a live demo site) and is fed from this seed instance, with a BKS overlay in between.
Impact: In daily use: 120 skills, 5 sub-agents, 15 standing orders, 104 automatically filed meetings. Six mutually isolated instances share the same open-source core without data flowing between them.
Python · YAML · Claude Code Plugins · Hooks API · GitHub Actions · Elasticsearch · Azure Functions · Microsoft Graph API
Developer Workshop: AI-Agent Development & Integration
Target Audience: Developers, Technical Leads, DevOps Engineers
Workshop Content:
- Hands-on AI Agent Development: Live coding with Claude, Gemini, GPT-4o
- Next-Gen Protocols: MCP & A2A implementation for enterprise integration
- Browser Automation: Playwright-MCP for automated test generation
- IDE Integration: AI assistance workflows with Claude Code as primary stack, GitHub Copilot & VS Code as tool comparison
- Multi-Agent Orchestration: JSON-RPC, secure agent communication
- Practical Demos: Jira integration, Elasticsearch queries, GitHub workflows
Deliverables: Complete source code, slides, hands-on exercises, production-ready templates
Anthropic Claude · Google Gemini · OpenAI GPT-4o · MCP · A2A · Playwright · JSON-RPC · IDE Integration · CI/CD
Enterprise AI Consulting: From Strategy to Implementation
Target Audience: C-Level, Management, Product Owners, Business Analysts
Consulting Services:
- Strategy Development: From AI vision to measurable implementation roadmap
- Process Analysis: Identification of automation potential, quality-first assessment
- ROI Assessment: Business cases, cost savings, amortization calculations
- Executive Workshops: Hands-on strategy sessions with live-demo business cases
- Change Management: Team adoption, training concepts, resistance management
- Implementation Support: From concept to productive AI solution
Deliverables: AI strategy template, ROI calculator, implementation roadmap, executive workshop, implementation support
AI Strategy · Process Analysis · ROI Assessment · Implementation Planning · Change Management · Executive Workshops · Quality Engineering
Medical Transcription System
GDPR-Compliant Transcription of Doctor-Patient Conversations
Core Features:
- Fully local: No cloud uploads, all processing on local machine (Privacy-by-Design)
- Speaker Diarization: Automatic doctor/patient distinction with Pyannote 3.1
- SOAP Protocol Generation: Automatic creation of structured medical protocols
- Open Source AI: Ollama with Llama 3.2 for intelligent summaries without API costs
- Apple Silicon Optimized: Native performance on M1/M2/M3 Macs
Impact: Privacy by design, with fully local processing (no cloud upload), automatic speaker separation and structured SOAP protocols.
Python · Whisper · Pyannote · Ollama · Llama 3.2 · Apple Silicon · SOAP Protocol
AI Learning Platform
EU AI Act Compliant Learning Platform for AI Workshops
Core Features:
- Article 4 Compliance: EU AI Act compliant certifications with audit trail
- Learning Card Types: Interactive quizzes, exercises, adaptive tests with scoring system
- Visual Themes: Learning, AI-Team, Star Trek, Nerd, Helldivers, Wednesday
- Progress Tracking: localStorage-based tracking with HR export functionality
- Automated Tests: learning paths and certification logic are covered by regression tests
Impact: Around 18,400 lines of application code and 16,100 lines of course material across 524 versioned files, written single-handedly (116 of 117 commits, the remaining one from a bot).
Astro · React 19 · TypeScript · Supabase · EU AI Act
Django SLA Dashboard · Enterprise Service Monitoring
Enterprise SLA Monitoring Dashboard for Service Level Agreements
Development of a comprehensive SLA monitoring system as part of a BKS evaluation project (2023-2025) for monitoring Service Level Agreements with real-time metrics and automated alerting.
Core Features:
- Service Registry: monitored services, each with its own SLA target and check interval
- Response Time Capture: periodic measurement per service, stored as a time series
- SLA Evaluation: availability against the configured target, rolling over selectable windows
- Incident Management: capture and prioritisation of open incidents
- Performance Analytics: response time distribution as a histogram over configurable buckets
- Availability Timeline: history over a selectable window at a chosen resolution, with trend display
- Alert System: rule-based alerting on SLA violations and performance degradation
Technical Highlights:
- Django 4.2 with async views for high-performance data processing
- PostgreSQL with TimescaleDB extension for time-series data
- Django Background Tasks for asynchronous processing
- WebSocket integration for live dashboard updates
- RESTful API for service integration and CSV export
- Docker-based deployment with Kubernetes-ready architecture
Context: Internal evaluation and demonstration dashboard fed by simulated SLA data, an architecture reference for time-series monitoring (not a production system).
Django · Python · PostgreSQL · Chart.js · WebSockets · Docker · REST API
QualityCluster
QualityCluster is an alliance of quality engineers jointly developing better solutions in software quality assurance.
Our goal is to implement more quality through a higher degree of automation.
Hugo · JavaScript · GitHub Actions · CI/CD
Streamlit demos: NLP text analysis
Interactive Streamlit demonstrations for NLP text analysis and AI-driven document processing.
Streamlit · Python · NLP · spaCy · NLTK · PyPDF2 · Named Entity Recognition · Sentiment Analysis · OpenAI
wecation
wecation is a collaborative solution for organising shared experiences: plan, search, coordinate with friends or colleagues and enjoy the activity together! Built with Flutter and Google Cloud.
Flutter · Google Cloud · Firebase · Dart
AI-Driven Chatbot for Trade-Fair Interaction
Development of an interactive chatbot using RAG (Retrieval-Augmented Generation), OpenAI GPT-4, Vector Embeddings, Python FastAPI, and Streamlit frontend to optimize user interaction on trade-fair websites.
Python · OpenAI GPT-4 · Streamlit · FastAPI · Vector Embeddings
Appointment enquiry over WhatsApp and phone
Two channels on one domain core: a WhatsApp assistant and a phone assistant that read free slots live from the booking portal instead of inventing them.
- Problem: Calls were lost during working hours, and a language model must never invent an appointment.
- Solution: The model runs the conversation, the free slots come live from the portal API. It pencils an appointment in but never books it, and consent comes before the first substantive sentence.
- Result: The WhatsApp channel has been in production since August 2026 on the client's own business account, with data residency in Germany and real end users. The voice channel is built and verified and is deliberately idle at present.
Python · FastAPI · WhatsApp Business Cloud API · Speech-to-Text · Text-to-Speech · LLM · Telephony gateway · Booking portal API
Email Classification and Processing Workflow
Complete automation solution with Microsoft Graph API, SAP RFC, Azure Functions (Python), OpenAI GPT-3.5-Turbo, Elasticsearch 8.x, Kibana Dashboards, Docker containers, and GitHub Actions CI/CD.
Python · Azure Functions · OpenAI GPT-3.5 · Microsoft Graph API · Elasticsearch · Kibana · Docker
Competencies
Grouped by field
Quality Engineering
Quality Engineering · Specification & Verification Design · Playwright · Behave / pytest (BDD) · Cucumber/Gauge · JMeter · Gatling
AI & Agents
Claude Code (Skills, Hooks, MCP) · Agent Harness Engineering · LLMs (Claude, Gemini, GPT) · Agent Orchestration (MCP & A2A) · a2a-sdk & Agent Cards · Google ADK · LangChain
Delivery & Automation
Python · TypeScript · FastAPI · JSON-RPC 2.0 & SSE · CI/CD · Docker · REST APIs · Agile (Scrum/Kanban)
Platform & Monitoring
Peppol/E-Invoicing (EN 16931) · Azure Functions · Azure DevOps · Azure Monitor & KQL · Cloudflare (Workers, Pages, R2) · Microsoft 365 / Exchange Online · Grafana · Elasticsearch · Kibana · OpenTelemetry / OTLP
More
AWS · Google Cloud
Talks
Workshops and talks where I pass the knowledge on
Guest Lecture: AI-Assisted Software Development in Practice
Guest lecture in a block lab course for Bachelor's students in Computer Science (Dept. 20). Shared how agentic coding and AI prototyping work in real projects. The talk connects directly to the students' subsequent team work on their own startup ideas.
Topics
- From prompt to prototype: AI toolchains that get an MVP done in hours, not weeks
- Agentic coding in practice: where it scales, where the friction sits, where tools break down
- Live demos from my own skill ecosystem, on demand in response to the group's questions
- Lessons from production AI projects rather than slide theory
Format: moderated impulse talk with interactive live demonstrations. Audience: ~25 students with mixed prior knowledge.
Workshop: Development with Generative Language Models
Developer Workshop: Comprehensive workshop on modern AI agent development with practical demos and live coding
Workshop Content
- Development with LLMs (Claude, Gemini, GPT-4o) and token optimization, used across projects
- Model Context Protocol (MCP) & Agent-to-Agent (A2A) protocol implementation
- Google Agent Development Kit (ADK) for multi-agent systems and tool integration
Workshop Content · Technologies & Tools
Workshop Content
- Agent orchestration with JSON-RPC and multi-agent systems
- Browser automation with Playwright-MCP for automated test generation
- Live demos: Jira integration, Elasticsearch queries, GitHub workflows
- Prompt engineering & rule-based agent control (CLAUDE.md, instructions)
- TDD workflows with AI assistance and automated PR creation
- Task Master AI agent for project management and code scaffolding
Technologies & Tools
- Anthropic Claude, Google Gemini, OpenAI GPT-4o
- Google Agent Development Kit (ADK), Model Context Protocol (MCP), Agent-to-Agent Protocol (A2A)
- Claude Code as primary stack; GitHub Copilot & VS Code AI extensions covered as tool comparison
- Playwright, browser automation, web scraping
- JSON-RPC, REST APIs, multi-agent communication
Complete workshop with slides, live demos, and practical exercises for modern AI-assisted development workflows.
Presentation: Efficient Documentation through Automation
Enterprise Presentation: Demonstration of modern automation approaches for centralized, current documentation and sustainable project success
Key Focus Areas
- Single Source of Truth: Central truth in Confluence, avoiding redundant versions
- Shift-Left Documentation: Code and documentation developed in parallel, so both stay up to date
- Automation First: Bots and CI/CD jobs for recurring tasks, automatic updates
Key Focus Areas · Technical Solutions · Tools & Integration
Key Focus Areas
- OpenAPI Documentation: Automatic generation on code merge, Consumer-Driven Contracts
- Documentation Debt Management: Dashboard-based visibility, Tech-Debt labels
- Automated Quality Assurance: Unit tests, integration, end-to-end reports
Technical Solutions
- Template-based standardization with mandatory and optional fields
- Label system instead of traffic lights for multi-dimensional filtering (status:draft, domain:payments)
- Semantic Release for automatic release notes
- Code changes aligned with documentation
- KPI/OKR dashboards for measurable progress
Tools & Integration
- Confluence, GitHub, Jira, MkDocs, OpenAPI
- CI/CD pipeline integration for documentation automation
- Monitoring and dashboard creation for Documentation Debt
Applications of AI in Business Context
AI workshop: Comprehensive presentation and live demonstration of innovative AI applications for business with a focus on practical implementation, theory and code examples.
Presentation content
- Comprehensive overview of AI fields and patterns (supervised/unsupervised/semi-supervised learning)
- Deep dives into machine learning, deep learning and natural language processing
- Detailed look at GPT models and how they work (next token prediction)
Presentation content · Practical workshop part · Technologies used
Presentation content
- Practical prompt engineering with examples for various use cases
- Introduction to tools such as Hugging Face, Stable Diffusion, Midjourney and Auto-GPT
Practical workshop part
- Development of an intelligent Q&A bot with OpenAI GPT-3.5-Turbo
- Live development of a web scraper for data acquisition
- Extraction and vectorization of text embeddings with OpenAI models
- Implementation of similarity search for context-based answers
- Similarity analysis and visualization of results
- Creation of an interactive Streamlit user interface for the Q&A bot
Technologies used
- OpenAI API (GPT-3.5-Turbo, Embedding-Ada-002)
- Python with Pandas, NumPy and Streamlit
- Vector embeddings and cosine similarity for semantic search
- Web scraping with BeautifulSoup and Requests
- Prompt engineering and AI integration into business processes
- Integration via RESTful APIs
The full presentation is available at Pitch.com. The complete source code of the developed Q&A bot is documented in my GitHub repository.
Education
Degrees, certificates and languages
Diploma in Computer Science (UAS)
ISTQB Certified Tester
Certified Dynatrace Diagnostics Basic Training
Languages
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