One question per article: what should get built, and how I would know it worked.
Articles
26
Topics
5
Latest
Oct 19
Archive
Filter by topic or search titles and tags. Each post answers one question.
Agentic coding removed the cost that used to kill a weak idea before anyone built it. I keep a refusal that can win, and an assistant does not move a finished draft onto the list of things I will stand behind.
I build reports with the Power BI MCP and reporting skills, so an assistant can produce the model and the pages. The contract has to state how the analytics are allowed to behave before that build, because the unit is the report, not one measure.
Barcelona's Copilot and Power BI updates let a report's definitions leave the report and change stored data. I would name the speaking model, the allowed writes, and who can stop a bad action before I turn that on.
As report construction gets cheaper, I need a testable brief and a separate check for decision quality before a polished page earns trust.
AI can remove the repetitive work of configuring data access, but I still need a desired-state policy, a readable diff, and a named owner before permissions change.
I treat semantic-model modification times as incident triage: useful for narrowing suspects, never enough to prove causality.
When an analytics platform moves, I adopt the change only if it removes a named recurring job without removing the control that kept that job safe.
Shipping many side projects teaches almost nothing if each one starts from a blank slate. Here is the shared spine I reuse: write things down, share knowledge, remember across work, and keep a human in the approval loop.
My training plan already had honest numbers. They still felt like a parking ticket. Gate ranks wrap the same sensor data in a story so I actually look at readiness before I look at Tuesday squats.
Chat history is a transcript, not a filing system. After retiring a heavy local orchestrator, I built a quieter portfolio memory so each new session starts with what I already decided.
A native Power BI feature can remove a workaround, but the durable improvement is deciding which responsibility moved and what the report can still rely on.
Sadalage and Chandrasekaran argue agentic AI fails on sand foundations. As a delivery lead I would fix contracts and quarantine before another orchestration demo.
Mohammad Ali's usable split: a semantic model answers a mathematical question; an ontology is for the process that acts. I would not skip the middle doll because Desktop grew a prompt.
A personal coach that turns Intervals form, Slack RPE, and block research into a Sunday week plan, so I spend energy training instead of re-deciding the week.
A React frontend can change the reporting experience quickly, but durable analytics still depends on a stable semantic contract and two deliberate release lanes.
MCP and CLI can move Fabric work from clicks to agent actions, but the durable gain comes from scoped permissions, inspectable plans, and deliberate approval.
Fabric Apps move analytics beyond the report canvas, but a custom frontend only pays off when the experience needs more than a report and the team accepts software ownership.
A Vite board for Nordic large-caps: market-cap size, day-change color, logos, and sector zoom — fed from the same gold the Power BI report uses.
What shifts when you move from PD models and ECL to leading Azure application operations, and which quantitative habits still decide the call.
Individual copilots make people faster; without shared judgment and a real priority gate, that speed mostly manufactures misalignment.
A small Python research loop that compares a few stock strategies on shared data, changes the working rule only when the edge is clear, then lists concrete buys and sells with reasons.
A shared report grammar for analytics work: gold tables, a semantic model, Landing → Pulse → Drivers → Queue, then screenshots synced into Orbit so the site matches the repo.
Chris Webb proved Fabric can alert on a broken DAX visual. The harder work is writing semantic instructions, validating KQL, and deciding what the owner does when Teams rings.
Chris Webb's Direct Lake case is really about where cost and cycle time live. For portfolio reports that still ship as Import models, measure the gold layer before you chase framing.
If agents become a unit of work, stop counting runs and start defining useful outcomes — the same discipline that makes a Monday dashboard trustworthy.
A Next.js headquarters for Blog, portfolio proof, a curated RSS feed, and Studio — designed so future-me can ship without renting another platform.