Posts
When Frictions Matter: From Models to Decision Systems
Nothing looked wrong in the model. And yet, the system behaved differently. A SoccerSim Lab case on friction, admissibility, and decision confidence under real constraints.
The Augmented Actuary: A System View on Actuarial Work
Actuarial work already spans reasoning, modeling, and workflows. The shift is not a new profession, but a new operating model: hybrid reasoning, computer-aided modeling, and agent-organized workflows that make work persistent, scalable, and accountable.
Direction, Trust, and Stability: What a Small Stress Study Taught Me About Decision-Grade Models
A small time-series review: why directional effects are valuable, why trust can break when assumptions fail, and how stability signals point to better predictions—and better insurance decisions—under stress.
Risk Capacity, Exposure, and Order: Why Insurance Portfolios Fail — or Hold — as Systems
Why insurance portfolios fail not because of too much risk, but because risk is taken in the wrong order — how survivability, risk capacity, and exposure allocation must be sequenced.
Vibe Coding vs. Agentic Development
Why feeling productive is not the same as building systems that compound — and when AI work actually starts to stick.
Why I Only Talk About Agents That Run in Public
A personal standard for building AI agents — visibility, restraint, and accountability over demos and hype.
ALM as a System: How Modern Insurers Create (or Destroy) Value
A system-level perspective on ALM: why outcomes differ, where value leaks, and how an integrated ALM engine unlocks clarity, capacity and sustainable growth.
Building a Palantir-Level Operating System With Open Source
How modern Python/LLM ecosystems now rival enterprise platforms — from someone who has worked deeply in both worlds.
A Structured, Quantitative Approach to Sports Betting: Value, Portfolios and Risk
How a quantitative bettor evaluates Matchday 12: value signals, portfolio construction and risk profiling — clear, transparent and data-driven.
How a Sporting Director Uses Predictive Intelligence
A concise, first-person view on how predictive models clarify squad strength, trajectories and scenario risks.
Building a Reliable AI Reporting Engine: Lessons From a Personal Mission to the Moon
Privacy-first AI reporting engine for clinical documentation. How structured workflows, validation and local models enable reliable, transparent GenAI.
Season Update: Control, Consequence – and Mental Strength
Resilience and astounding similarities to the vice championship campaign 23/24
Season Update: Control vs. Consequence — A Setback with Lessons
Sebastian HoeneĂź sees team on right track, but identifies items to improve. What could he mean?
Season Update: VfB Stuttgart – Rotation, Maturity, and Tactical Control
Sebastian HoeneĂź applies tactical foresight successfully
Understanding Artificial Intelligence — From Reasoning to Generation
What is artificial intelligence? Why the hype? How is it used?
Season Update: VfB Stuttgart – On Course for Europe
VfB Stuttgart – Three Points on Command, Firmly on Course for Europe
The Living System of Leadership: Purpose, Collaboration, Innovation
Most organisations were designed for a time when the world was stable — when direction came from the top, execution from below, and change moved slowly enough to plan. How have market leaders adapted already?
From Prompt to Pipeline — Reflections on Building with Generative AI (Part 1)
How I select my language models…
Season Update: VfB Stuttgart on track
VfB Stuttgart – Season Outlook and Model Update ⚪️🔴
Why Sport Modeling Is Full of Opportunity
The sport industry is a rapidly changing environment:
Parallel Worlds: How Reinsurance and Sports Modeling Speak the Same Language
Gary Lineker: “Football is a simple game. Twenty-two men chase a ball for 90 minutes, and at the end, the Germans always win.”
The Search for Value Bets: Next Steps in Modeling
Betting Basics — From Fair to Value Bets, and beyond