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Ideas from the work

Writing

I use writing to make the work inspectable: the decisions behind a data platform, what failed in an automation, how an agent stack behaves in production, and how those lessons are converging into Company OS.

English is the default so technical work can travel across teams and markets. Swedish pieces remain in Swedish when their original context benefits from it, and are labelled clearly.

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Five pieces that explain the trajectory.

Together they connect analytics, engineering, operational ownership, and the current Company OS thesis.

01The throughlineFrom BI Reporting to Data-Driven Automation: A 10-Year Evolution of Data StrategyA decade from dashboards and BI to data-driven automation.02The platformFrom Raw Data to Revenue Decisions: Building an End-to-End Analytics PlatformHow ingestion, models, dashboards, and AI became one decision system.03The disciplineWhat is Agentic Engineering? A Practitioner's DefinitionA practitioner definition grounded in production infrastructure.04The organisationAgentic Data Organisation: How I Set Up an AI-Driven Data Organisation with ClaudeAgents coordinating analytics, platform, governance, and data quality.05The operating stackYour AI Agent Stack Is Your Competitive Edge — If You Treat It as InfrastructureWhat created leverage in a continuously running agent stack.

Latest

Notes, cases, and tested patterns.

Company OS: The Architecture, Vision, and Plan

field note ·
Company OS is my working thesis for connecting human intent, shared context, autonomous execution, and accountable outcomes. This is the architectural view—not a finished product announcement.

Beyond the Spin: Building a Creative Loading Bar in Streamlit for Better UX

case study ·
When Databricks queries take 5–20 seconds, a static orange banner feels like an error. Swap in a branded Automower animation with the same Streamlit context-manager API.

LINHAC 2026 — Conference Report

field note ·
LINHAC 2026 confirmed a clear shift: hockey analytics is becoming core infrastructure, not a side project. This report summarizes the strongest research signals, practical club examples, and what organizations should prioritize next.

n8n Switch node vs. chained IF nodes: how branching logic affects execution at scale

tutorial · · Updated
If your workflow routes items into more than three paths using chained IF nodes, the Switch node does the same with one evaluation per item instead of N. Here is the mechanical difference, when each wins, and the practical rule for choosing between them.

22 Articles in 26 Days: Session Data, Keywords, and What the Automation Actually Produces

case study · · Updated
Four weeks of build in public: 22 n8n tutorials published, 951 sessions, 38 ranked keywords, and 2 top-10 rankings — without a single external backlink. Here are the numbers, without spin.

n8n IF Node: Adding Conditional Logic to Your Workflows

tutorial · · Updated
The IF node is how you branch in n8n. It evaluates a condition against each incoming item and routes it down one of two paths — true or false. Here is how to use it correctly across simple and complex scenarios.

n8n HTTP Request Node: Calling External APIs from Your Workflows

tutorial · · Updated
The HTTP Request node is the workhorse of n8n — it connects your workflows to any API that accepts HTTP calls. Here is how to configure it correctly, handle authentication, and deal with real-world API quirks.

n8n Webhook Node: Receive Data from External Services and Trigger Workflows

tutorial · · Updated
The Webhook node turns n8n into a receiver — any external service that can send an HTTP request can now trigger your workflows instantly. Here is how to set it up, secure it, and use it in production.