Human-in-the-Loop Experts in Germany

• Claude Code subagents, MCP, Pydantic V2, pytest, bandit

• Designed and shipped 3 specialized agents that hand work down a line: a research agent writes a cited implementation spec, a coding agent builds the modular code and its tests, a review agent ranks findings by severity and applies the fixes. Each handoff is a structured document, so no stage depends on another agent's context window.

• Connected the research agent to an academic-research MCP server (Semantic Scholar, ArXiv, Hugging Face Hub, citation snowballing) so every reference traces to a tool result rather than the model. Gated commits behind ruff, mypy, pytest and bandit, required human sign-off before installs and commits, and persisted session state on disk so long runs survive a context reset.

• Redesign of legal operations: standardised workflows reducing routine effort by up to 80%, with source citation, hallucination check as quality gate, role model, logging and audit trail.
• Compliance-by-design operating model (EU AI Act readiness, GDPR, eIDAS) with documented, releasable process steps.
• Roadmap, sprint planning and release management for an agentic RAG platform with counsel-in-the-loop approval, audit trail and German hosting.
• EU AI Act readiness, GDPR and eIDAS requirements managed as first-class project deliverables; go-to-market for two customer verticals.

• Advisor on AI readiness and evaluation structures for enterprise-level adoption in finance and technology contexts
• Developed rubric-based evaluation frameworks assessing reasoning quality, factual reliability, and compliance alignment of AI models
• Embedded human-in-the-loop oversight and reporting standards

CRM and revenue platform managing billing and subscription workflows.

• Scaled payments infrastructure across data products, direct debit expansion and automated abuse prevention, generating $416K in annualized operational savings ($8K/week) by eliminating redundant gateway calls.
• Owned backlog and sprint execution for autonomous checkout abuse detection pipelines, designing real-time risk guardrails and velocity heuristics that blocked card testing attacks.
• Architected enterprise billing migrator user stories and data reconciliation mechanisms, achieving zero-downtime subscription state transitions and cutting $60K in infrastructure overhead.
• Expanded European direct debit (SEPA) payment capabilities, managing cross-squad API dependencies and automated webhook error-handling to eliminate checkout friction.

Workflow-automation SaaS for operations teams (Berlin, 120 people); full-time freelance engagement reporting to the CEO: an initial 12-month interim mandate, extended twice through the AI build-out; owned product for one squad and coached the other product managers on process.

• Led generative AI (LLM) integration into the core product: from LLM-powered steps to natural-language workflow authoring and step-level automation suggestions, plus AI-managed dynamic workflows, shipped behind eval gates with human-in-the-loop fallbacks: AI-drafted workflows grew to 31% of all new workflows, and median time-to-first-workflow fell from 3 days to 4 hours.
• Packaged the AI capabilities as a usage-based add-on priced on executed automation steps, working with sales and marketing on positioning: ~€800K added ARR in the first year, and adopting accounts churned 1.8 pp less.
• Owned the roadmap end to end: replaced feature-request-driven quarterly planning with an outcome-based rolling roadmap built on quarterly bets and explicit kill criteria, presented monthly to the executive team and quarterly to the board.
• Rebuilt the product-management operating system: weekly customer-discovery cadence incl. workshop facilitation, RFC/decision-doc reviews and a single quarterly metrics narrative; coached four product managers, one promoted to senior during the engagement.
• Closed the engagement as scoped: hired and onboarded the permanent VP Product, handed over the process playbook and roadmap, and exited on schedule in June 2026.

• Team leadership: Prioritization and coordination of four cross-functional teams.
• Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
• Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
• Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
• Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
• Organizational development: Improving communication and decision-making structures across all organizational levels.
• Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
• Quality assurance: Ensuring high quality standards in processes, services, and deliverables.

Seitenkumpel — agents build websites for trade businesses, unattended. Own product, live.

• Agents research public company data and build complete websites from it, with nobody watching
• A validation layer makes sure extraction errors fail loudly instead of passing quietly
• Acquisition runs through a postcard funnel with a screenshot and a QR code, subscription model from 79 euros a month
• Result: several hundred websites built, running unattended
• Honest limit: there are no paying subscriptions yet — the funnel is built, the revenue is not there

Stack: agent workflows built directly without a framework, Claude and OpenAI APIs, TypeScript, Node.js, PostgreSQL, Cloudflare Workers, web scraping, data enrichment

• Own the 12–18 month roadmap and key outcomes for Elli's enterprise customer platform, covering onboarding, pricing, billing, analytics and broader platform modernization; redesigned the Fleet onboarding funnel to double conversion, supporting a projected €20.7M revenue uplift by 2028.
• Lead the broader Energy Intelligence product and directly own its AI/ML, asset and portfolio-optimization capabilities, including MLOps and safe strategy deployment, strategy lifecycle management and backtesting; delegated data and V2G integration roadmap ownership to a new PO as the platform scope expanded.
• Built a Human-in-the-loop GenAI/RAG support workflow, increasing L1 resolution by 24%, routing accuracy to 91%, and reducing L2 workload by 30%.
• Introduced standardized data contracts and a self-service Python toolkit for traders and Data Scientists, increasing platform adoption by 15% and reducing support effort by 50%.
• Built and scaled a real-time orchestration product from 32 to 3,000+ endpoints across four markets, growing recurring revenue from €1.4k to €56.3k MRR.
• Developed product and AI capability across the organization, training 20 PMs on RAG, agents and prototyping; mentoring a junior PM and coaching an Enterprise Platform Tech Lead toward Product Management ownership.

Designing AI-native digital products by combining product strategy, UX research, interaction design, software engineering, and modern AI workflows. Leading projects from discovery to implementation while integrating AI throughout the entire product development lifecycle.

Key responsibilities

• → Product discovery, stakeholder workshops, Jobs-to-be-Done and user research
• → User journey mapping, information architecture and interaction design
• → Wireframes, high-fidelity UI, prototypes and scalable design systems in Figma and Penpot
• → AI-assisted interface generation and rapid concept exploration using Figma AI, Figma Make and generative design workflows
• → Design-to-code workflows with AI-supported frontend generation and engineering collaboration
• → Building accessible interfaces following WCAG 2.2 and enterprise design standards
• → Usability testing, iterative validation and KPI-driven product optimization
• → Development of AI knowledge systems, MCP-powered design workflows and human-in-the-loop review processes
• → Close collaboration with engineering teams to ensure production-ready implementation

• Root cause analysis of complex business, technical, and data-related errors in PowerCloud across process, booking, and system boundaries.
• Data-driven management of payments and receivables; contributed to reducing historical receivables from over 100 Mio. EUR to under 25 Mio. EUR.
• Identification of automation and straight-through processing potential at the interface between business departments, IT, and external service providers.

• Project-based work in marketing automation, process optimization, and content.
• On-site operational assignments in fully English-speaking teams.
• Focus on self-organized work, changing locations, quick onboarding, and a high level of personal responsibility.
• Remote projects for Spartan Race Australia & DMC Europe, among others.

Independent engineering practice focused on custom AI systems, production delivery, and fractional technical leadership.

Selected client engagement: Scalutions

• Role: Serve as fractional CTO and hands-on technical lead, responsible for the architecture and agentic infrastructure behind its managed B2B outbound operation.

• Product: Designed and built OutboundLoop, an agentic SDR operating system for research, qualification, personalized outreach, campaign management, human approvals, measurement, and continuous improvement.

• Scope: Own the full system lifecycle—from business processes and agent behavior to context design, model routing, integrations, evaluation, telemetry, reliability, cost control, and production operations.

Following the Vaillant engagement, established independent practice focused on senior SAP advisory and building ASTRA — a methodology, not a tool. ASTRA is independent and unbiased: the same four pillars serve CIO / Business Leadership, SI / SAP Practice, and Programme Director / Principal with equal weight. No audience is primary.

ASTRA serves three audiences with equal weight — CIO / Business Leadership · SI / SAP Practice · Programme Director / Principal. ASTRA is independent and unbiased — it does not sit inside any SI practice and does not serve any single audience as primary customer. Each audience receives a role-calibrated output from the same analysis.

One methodology, two outcomes:

OUTCOME 1 — SAP TRANSFORMATION GOVERNANCE:

Any active SAP programme: ECC→S/4HANA Greenfield, Brownfield, Global Rollout, AMS. The four pillars answer the four questions that determine whether a transformation succeeds — for any of the three audiences.

• Are business requirements clean — or is the SI building what SAP standard already covers? (Functional Auditor → all three audiences)
• Is the custom object inventory healthy — or accumulating debt that blocks upgrades? (RICEFW Auditor → Director and CIO)
• Is the SteerCo reporting accurate — or is leadership seeing a Watermelon? (Truth Engine → CIO and Director)
• Are people ready for the system they are receiving? (Human Signal → CIO and Director)

OUTCOME 2 — AUTONOMOUS ENTERPRISE READINESS:

Any programme deploying Joule, pursuing RISE, or planning an AE migration. The same four pillars answer the questions SAP does not — again, calibrated per audience.

• Which custom objects block the 224 Joule AI agents? (RICEFW Auditor → SI gets remediation paths, Director gets verdicts, CIO gets financial impact)
• Is the Fiori deployment complete enough to activate Joule? (Truth Engine → all three audiences)
• Is the workforce trained for AI-native working? (Human Signal → CIO and Director)

Four pillars (each serves all three audiences):

• Functional Auditor: Clean Core Score 0–100. Section A (CIO): KG fidelity risk in €. Section B (Director): SI challenge questions, man-day saving. Section C (SI): Language Translation Ledger, SAP alternatives.
• RICEFW Auditor: Joule API Pathway Audit, Clean Core Level A–D, Technical Debt Index 1–10. Section A: financial impact of blocked AI agents. Section B: RETIRE/MIGRATE/REDESIGN/KEEP verdicts. Section C: BTP remediation paths.
• Truth Engine: Watermelon Detection, Fiori Deployment check, Programme Truth Score 0–100. Section A: 3 SteerCo questions. Section B: 48-hour action list. Section C: vendor friction map.
• Human Signal: three-stage Fiori adoption model, HITL Policy readiness, Human Signal Score 0–100. Section A: GUI training weight, AE adoption financial risk. Section B: go-live recommendation, stakeholder resistance map.

On-Demand SAP Advisory:

• SAP Programme Management — end-to-end governance, factory management, multi-stream delivery, vendor oversight, SteerCo reporting for Greenfield, Brownfield, Rollout and AMS programmes.
• Delivery Management — RICEFW oversight, Data Migration governance, Release & Cutover management, Hypercare, SLA/KPI management.
• Due Diligence & Landscape Assessment — SAP landscape review, AS-IS/TO-BE roadmap, RFP structuring, SI selection advisory.
• IT Strategy & CIO Advisory — transformation roadmap, Clean Core strategy, Autonomous Enterprise readiness planning.
• Programme Recovery — distressed programme assessment, rapid governance setup, escalation resolution.

Operating through senior professional networks across EMEA.

• Expert-supervised AI systems for scientific reasoning, model evaluation, and research workflows.
• Built the IAS Problem Solver, an orchestrated system for difficult mathematical reasoning; it achieved 84% in one submitted answer set on the Leipzig mathematics benchmark.
• Built a resumable state-machine pipeline for research-grade mathematics benchmark generation: source selection, LLM-agent-based phenomenon discovery, task synthesis, gold-answer and certificate generation and validation, probing, repair, human feedback, and quality gates, targeting tasks that are difficult, natural, verifiable, and cost-effective.
• Current work extends this into budget-aware AI research workflows for real scientific problems with expert review.

Tech stack: Python, OpenAI/OpenRouter-compatible APIs, embeddings, RAG, SQLite.