DutchRank.ai: Why the Netherlands Needs Its Own AI Arena

DutchRank is an open arena where Dutch speakers blind-test AI models head-to-head, turning gut feel about "which model sounds best in Dutch" into a real leaderboard.

Introducing SiteCraft: Prescriptive Location Intelligence for Multi-Location Businesses

Imagine your best location consultant could evaluate every candidate site simultaneously, explain every recommendation in plain English, and update its thinking the moment your strategy changes. That's SiteCraft. Built by DataChef, SiteCraft is a prescriptive location intelligence platform that tells multi-location businesses not just where they could open

King Kong vs. Godzilla: Code Generator vs. Code Reviewer

There's a particular kind of engineering conversation I genuinely enjoy. Not the kind where someone brings a problem they already have the answer to and just wants you to nod along. I mean the kind where someone says something that makes you stop and reconsider what you thought

How Product Organizations Scale Without Splitting Strategy from Execution

Quick recap from my previous article: In high-performing product organizations, strategy and execution aren't split between different roles. Every product team needs someone who owns both the "why" an

Legacy Migration Starts with Understanding, not Inventory

An alternative to scale and direct legacy migration activities

How we use Claude to write code

Claude is a tool. It helps us think faster and write code faster. But the developer is still in charge. The goal is simple: better code, clear thinking, and full responsibility. This document explains

Introducing DANA: Conversational AI for Legacy System Modernization

Imagine your data expert could answer every team's questions at once, without a single meeting. That's DANA. Built by DataChef, DANA is a conversational AI that learns from your domain experts, unders

The Missing Right Side of Your dbt DAG

If you maintain a dbt project long enough, you end up with a familiar problem: you can see what’s upstream of a model, but it is surprisingly hard to answer what is downstream in the real world. Which

Don't Split Product Strategy from Execution

Mention the Product Owner role to someone from a startup or scale-up background, and you'll likely get a blank stare. They'll probably google it later to figure out what you meant. On the contrary, pe

Spec-Driven Development: Ship Features with AI Guardrails

Something has fundamentally shifted in how we build software. A year ago, if you told us we'd ship a production web application, 8 major features, 11 releases, 17,000 lines of TypeScript across a full

Event Storming and Context Mapping for Data & AI Product Managers

Discovery and requirements gathering are among the most critical phases of data product management. Yet they're also among the most challenging. Too often, data teams fall into the trap of being order-takers, responding to ad-hoc requests rather than...

Product Managers and the Art of Engineering a 'Yes'

If you spend any time reading about product management online, you'll frequently encounter a piece of advice: saying no is the product manager's superpower. There are countless guides on how to say no, why to say no, and frameworks for saying no with...

Generative BI

Copilot VS. Custom LLM: Navigating the Generative BI Landscape

For years, Business Intelligence has followed a familiar, often frustrating pattern. An executive has a question, an analyst hunts for the answer, engineers build data pipelines, and eventually—days or weeks later—a dashboard appears. By the time the...

Data Mesh

Is Your Organization Ready for Data Mesh? A Practical Readiness Check

You are being asked to make a long‑term bet on data architecture. Most conversations frame this as a choice between data lake and data mesh. Vendors, internal teams, and reference architectures encourage you to pick a side. 💡 “Data lake vs data mes...

Beyond Dashboards: An Executive Introduction to Generative BI

For years, leaders have relied on dashboards and BI teams to understand what is happening in their organization. The rhythm has been familiar: you notice something unusual, ask someone to “pull a report,” and wait while the request moves through a ba...

n8n

How We Turned Onboarding Into Something Magical Using n8n

Bringing a new colleague into DataChef has always felt a bit like welcoming someone into our kitchen. You want the place to feel warm and ready, and you want their first steps to feel smooth. For a long time, our onboarding process did not give that ...

team topologies

Fast Flow Conf 2025: Team Topologies and the Language of Flow

Consider this paradox for a second: imagine studying grammar for a language that doesn’t exist. You know all the rules in theory, yet you can’t communicate with anyone. After attending Fast Flow Conference in London earlier this week, that metaphor c...

monitoring

Agent/Non-Agent based monitoring & Distributed tracing

Introduction When monitoring applications and infrastructure, businesses usually choose between agent-based and non-agent based monitoring solutions. Some tools, such as Datadog or Splunk, can use agent-based approaches, while both also support non-a...

llm

Why your LLM needs its own version of Monitoring

TL;DR: LLMs don’t behave like normal services. They’re creative, a bit moody, and change under the hood without warning. Left alone, they surprise you at the worst time. You need LLMOps Monitoring: evals to measure quality, tracing to debug runs, and...

organization

Designing the "Blank Slate" of an organization

The first time you open an application you just installed, you might see several frames and components that look empty. These will fill up with your data as you start using the application. Designers call this initial state a "Blank Slate." It's now ...

spark

Pandas vs. PySpark: When Bigger Isn’t Always Better

Introduction In the data engineering world, bigger usually means better. More power, more scalability, and more buzzwords! PySpark, for instance, is typically our trusty steed when tackling massive da

data management

Data Set or Data Product, That is the Question

From nomenclature to business transformation, a handy guide to the fundamentals of Data as a Product

RAG

Improving Information Retrieval with Knowledge Graphs: Comparing VectorDB RAG vs Graph-Powered RAG on AWS

How Integrating Knowledge Graphs Can Improve Retrieval Augmented Generation Systems

team

Your Teams are not Call Centers

How Team APIs can address a basic need for clarity in the organization