series on philliant

ai

Thu, 02 Apr 2026 17:44:14 -0700

this series is where i document how i use ai as a real work system, not as a novelty tool.

i write these posts to make decision quality visible: when ai is helping, when it is creating hidden cost, and which workflow choices keep outcomes stable over time. the goal is to make ai usage more deliberate, measurable, and easier to hand off across sessions.

cursor

Thu, 02 Apr 2026 17:44:14 -0700

this series is my living documentation for using cursor as a daily driver.

i built it because most setup guides stop at installation, while the real leverage comes from repeatable systems: workspace boundaries, reusable rules and skills, model-routing habits, and tight review loops. those are the parts that decide whether ai-assisted editing is useful.

commentary

Thu, 02 Apr 2026 05:11:05 -0700

this series is where i publish the looser essays that do not fit a strict tutorial format.

dbt

Mon, 30 Mar 2026 16:34:36 -0700

this series is my working notebook for dbt architecture and transformation workflows.

i care less about one-off clever models and more about systems that are easy to understand, easy to test, and easy to change six months later. when i publish here, i focus on practical design decisions and why they hold up under change.

sql

Sat, 28 Mar 2026 05:48:02 -0700

this series is where i write about sql as a working craft: clear queries, reliable debugging, and practical performance habits.

if a specific sql pain point keeps repeating in your work, send it to me and i will use it to shape upcoming entries in this series.

snowflake

Sat, 28 Mar 2026 04:49:27 -0700

this series is where i document practical snowflake decisions that affect speed, cost, and reliability in day-to-day data work.

here, i consider the operating model: how to design warehouse layers, tune workloads, and keep teams moving without burning credits.

data vault 2.0

Tue, 24 Mar 2026 07:00:00 -0700

this series is where i break down data vault 2.0 decisions into practical implementation patterns.

the focus here is concrete modeling choices: what to put in hubs, links, and satellites, how to handle change, and how to keep lineage understandable as the system grows.