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...

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...

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...

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 ...

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...

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...

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...