<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>article on philliant</title><link>https://philliant.com/categories/article/</link><description>Recent content in article on philliant</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 philip mathew hern</copyright><lastBuildDate>Thu, 02 Apr 2026 17:44:14 -0700</lastBuildDate><atom:link href="https://philliant.com/categories/article/index.xml" rel="self" type="application/rss+xml"/><item><title>how i use cursor and ai agents to write dbt tests and documentation</title><link>https://philliant.com/posts/20260402-how-i-use-cursor-and-ai-agents-to-write-dbt-tests-and-documentation/</link><pubDate>Thu, 02 Apr 2026 17:44:14 -0700</pubDate><guid>https://philliant.com/posts/20260402-how-i-use-cursor-and-ai-agents-to-write-dbt-tests-and-documentation/</guid><description>writing dbt tests and documentation is often the most neglected part of data engineering. i will show you how i use cursor and ai agents to automate this process, ensuring high-quality data pipelines without the manual overhead.</description></item><item><title>the future of data engineering workflows with ai</title><link>https://philliant.com/posts/20260402-the-future-of-data-engineering-workflows-with-ai/</link><pubDate>Thu, 02 Apr 2026 17:44:14 -0700</pubDate><guid>https://philliant.com/posts/20260402-the-future-of-data-engineering-workflows-with-ai/</guid><description>data engineering is evolving rapidly with the integration of artificial intelligence. i will explore how ai agents, large language models, and automated workflows are transforming the way we build, maintain, and scale data platforms.</description></item><item><title>sharing is caring</title><link>https://philliant.com/posts/20260402-sharing-is-caring/</link><pubDate>Thu, 02 Apr 2026 05:11:05 -0700</pubDate><guid>https://philliant.com/posts/20260402-sharing-is-caring/</guid><description>mastering emerging tools like cursor and ai is only the first step. true value comes from becoming a point person for your team, sharing your voice, and mentoring others through the nuances of adoption.</description></item><item><title>what is art?</title><link>https://philliant.com/posts/20260330-what-is-art/</link><pubDate>Mon, 30 Mar 2026 16:38:30 -0700</pubDate><guid>https://philliant.com/posts/20260330-what-is-art/</guid><description>i do not have a clean answer. i am trying to understand why ai-assisted code can feel normal while ai-assisted painting or music can trigger backlash, and what that says about authorship, labor, and value.</description></item><item><title>dbt tests</title><link>https://philliant.com/posts/20260330-dbt-tests/</link><pubDate>Mon, 30 Mar 2026 16:34:36 -0700</pubDate><guid>https://philliant.com/posts/20260330-dbt-tests/</guid><description>dbt tests are one of the highest-leverage habits in analytics engineering, but they are often underfunded in real projects. this post explains how i use generic and singular tests, what to prioritize first, and a few practical examples you can copy today.</description></item><item><title>dbt docs</title><link>https://philliant.com/posts/20260330-dbt-docs/</link><pubDate>Mon, 30 Mar 2026 04:39:08 -0700</pubDate><guid>https://philliant.com/posts/20260330-dbt-docs/</guid><description>dbt docs are one of the most overlooked features in a dbt project, but they are one of the most valuable for teammates who consume data without building it. i walk through how they work, what options matter, and how to host them for free on github pages.</description></item><item><title>what is sql, and why it still works</title><link>https://philliant.com/posts/20260328-what-is-sql-and-why-it-still-works/</link><pubDate>Sat, 28 Mar 2026 05:48:02 -0700</pubDate><guid>https://philliant.com/posts/20260328-what-is-sql-and-why-it-still-works/</guid><description>i break down sql in plain language: what it is, how it evolved over five decades, which problems it solves best, and the core features that keep it relevant</description></item><item><title>the difference between snowflake and the "other" databases</title><link>https://philliant.com/posts/20260328-the-difference-between-snowflake-and-the-other-databases/</link><pubDate>Sat, 28 Mar 2026 04:49:27 -0700</pubDate><guid>https://philliant.com/posts/20260328-the-difference-between-snowflake-and-the-other-databases/</guid><description>when you first step into data engineering, the sheer number of database options can be overwhelming. i break down how snowflake compares to traditional relational databases like rds and nosql options like dynamodb, focusing on when to use each and how they scale.</description></item><item><title>adaptability</title><link>https://philliant.com/posts/20260327-adaptability/</link><pubDate>Fri, 27 Mar 2026 09:45:05 -0700</pubDate><guid>https://philliant.com/posts/20260327-adaptability/</guid><description>ai and agents are accelerating how quickly work changes, and that pressure is showing up far beyond tech. i am seeing it directly while working with almost no cell signal and shared low-bandwidth internet, and it keeps reminding me that adaptability is a compounding skill.</description></item><item><title>the danger of trusting the ai agent</title><link>https://philliant.com/posts/20260326-the-danger-of-trusting-the-ai-agent/</link><pubDate>Thu, 26 Mar 2026 06:31:57 -0700</pubDate><guid>https://philliant.com/posts/20260326-the-danger-of-trusting-the-ai-agent/</guid><description>i share a real failure mode where an ai agent created and then deleted files while debugging, leaving a clean git tree but low confidence. the lesson for me is simple: ai should accelerate the work i own and understand, while domain-specific decisions stay with the people accountable for that domain.</description></item><item><title>plane wifi: when the cabin forced disconnect</title><link>https://philliant.com/posts/20260324-wifi-on-planes/</link><pubDate>Tue, 24 Mar 2026 09:23:21 -0700</pubDate><guid>https://philliant.com/posts/20260324-wifi-on-planes/</guid><description>i used to want to protect disconnected travel time. now i am torn between relief from the message stream and the feeling that a long flight is wasted if i cannot sleep and i am not online. cabin class changes how real that tradeoff is, and i still do not have a clean verdict.</description></item><item><title>left join an effective satellite without duplicating rows (use a cte)</title><link>https://philliant.com/posts/20260324-left-join-effective-satellite-cte/</link><pubDate>Tue, 24 Mar 2026 07:00:00 -0700</pubDate><guid>https://philliant.com/posts/20260324-left-join-effective-satellite-cte/</guid><description>when an entity link to another hub is optional, a naive left join that pulls in an effective satellite in the same from list can explode or blur grain. i isolate the current effective row in a cte and left join that instead.</description></item><item><title>brain defrag: time away from screens (and from "one more" with ai)</title><link>https://philliant.com/posts/20260320-brain-defrag-time-away-from-screens/</link><pubDate>Fri, 20 Mar 2026 14:30:00 -0700</pubDate><guid>https://philliant.com/posts/20260320-brain-defrag-time-away-from-screens/</guid><description>i argue that constant production and always-on tools work against clarity. yard work, runs, and boredom give my thoughts room to float, and that is when problems unlock after long struggle.</description></item><item><title>deep dive: the ai models i use</title><link>https://philliant.com/posts/20260320-deep-dive-ai-models-i-use/</link><pubDate>Fri, 20 Mar 2026 10:45:00 -0700</pubDate><guid>https://philliant.com/posts/20260320-deep-dive-ai-models-i-use/</guid><description>i walk through composer-2, gpt-5.3-codex-xhigh, claude 4.6 opus, gemini 3.1 pro, grok-4-20, and kimi-k2.5 with a comparison table plus longer notes on how i actually use each one.</description></item><item><title>a practical ai workflow: jira, github, and mcp</title><link>https://philliant.com/posts/20260319-practical-ai-workflow-jira-github-mcp/</link><pubDate>Thu, 19 Mar 2026 11:30:00 -0700</pubDate><guid>https://philliant.com/posts/20260319-practical-ai-workflow-jira-github-mcp/</guid><description>i connect my editor to jira and github through mcp, create well-structured issues from templates before coding, and reuse that text in pull requests so every agent in the chain has the same ground truth.</description></item><item><title>from prototype to production: my early adopter view of ai</title><link>https://philliant.com/posts/20260318-from-prototype-to-production-ai/</link><pubDate>Wed, 18 Mar 2026 07:09:57 -0700</pubDate><guid>https://philliant.com/posts/20260318-from-prototype-to-production-ai/</guid><description>i have watched ai move from a prototype side assistant to an operational core system. this post shares that journey with time-stamped benchmark evidence and a practical view on where model usage is headed next.</description></item><item><title>starter templates for ai rules, skills, and commands</title><link>https://philliant.com/posts/20260315-starter-templates-for-ai-rules-skills-and-commands/</link><pubDate>Sun, 15 Mar 2026 04:00:00 -0700</pubDate><guid>https://philliant.com/posts/20260315-starter-templates-for-ai-rules-skills-and-commands/</guid><description>this follow-up post gives practical, generic templates you can adapt for rules, skills, and commands, plus side-by-side examples that show why tighter structure improves ai execution quality.</description></item><item><title>how to use ai to create ai rules, skills, and commands</title><link>https://philliant.com/posts/20260314-how-to-use-ai-to-create-ai-rules-skills-and-commands/</link><pubDate>Sat, 14 Mar 2026 11:15:00 -0700</pubDate><guid>https://philliant.com/posts/20260314-how-to-use-ai-to-create-ai-rules-skills-and-commands/</guid><description>this kickoff post explains why ai-authored rule, skill, and command scaffolds are often clearer for ai execution, and how to keep humans in control with constraints, reviews, and acceptance checks.</description></item><item><title>ai br-ai-n fr-ai</title><link>https://philliant.com/posts/20260314-ai-br-ai-n-fr-ai/</link><pubDate>Sat, 14 Mar 2026 10:30:00 -0700</pubDate><guid>https://philliant.com/posts/20260314-ai-br-ai-n-fr-ai/</guid><description>this post frames ai brain fry as a workflow design problem and gives a practical framework to reduce cognitive overload while keeping ai leverage high.</description></item><item><title>my cursor setup</title><link>https://philliant.com/posts/20260313-my-cursor-setup/</link><pubDate>Fri, 13 Mar 2026 10:30:00 -0700</pubDate><guid>https://philliant.com/posts/20260313-my-cursor-setup/</guid><description>this is my real cursor setup as of march 13, 2026, rewritten as a practical tutorial with settings explanations, mcp server breakdowns, and a replication checklist.</description></item></channel></rss>