<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Meta on</title><link>/tags/meta/</link><description>Recent content in Meta on</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 29 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="/tags/meta/index.xml" rel="self" type="application/rss+xml"/><item><title>Research Engineer Trajectory</title><link>/projects/research-engineer-trajectory/</link><pubDate>Mon, 29 Jun 2026 00:00:00 +0000</pubDate><guid>/projects/research-engineer-trajectory/</guid><description>&lt;p>A 6-month personal study direction. I am becoming someone who understands modern LLMs across abstraction levels — from math to metal — with a focus on transformers, inference systems, and efficient kernels.&lt;/p>
&lt;p>&lt;a href="/research-engineer-trajectory-2026-06/">Read the full living note&lt;/a>&lt;/p></description></item><item><title>Research Engineer Trajectory</title><link>/research-engineer-trajectory-2026-06/</link><pubDate>Mon, 29 Jun 2026 00:00:00 +0000</pubDate><guid>/research-engineer-trajectory-2026-06/</guid><description>&lt;blockquote>
&lt;p>Status: direction, not a plan&lt;br>
Horizon: ~6 months, with weekly check-ins against this note&lt;/p>&lt;/blockquote>
&lt;hr>
&lt;h2 class="heading" id="what-this-is">
 What this is
 &lt;a href="#what-this-is">#&lt;/a>
&lt;/h2>
&lt;p>A reference document capturing a long conversation about how to spend the next ~6 months of personal study time. It is a living note, not a fixed plan. It will be revised as the work reveals what actually matters.&lt;/p>
&lt;hr>
&lt;h2 class="heading" id="starting-identity">
 Starting identity
 &lt;a href="#starting-identity">#&lt;/a>
&lt;/h2>
&lt;p>I am becoming someone who understands modern LLMs and transformers across abstraction levels — from the math to the metal. The working title is &lt;strong>research engineer with inference engineer capabilities&lt;/strong>, but the exact craft will emerge from the work. The trunk is transformers and inference. Branches may form later.&lt;/p></description></item><item><title>Week 26, 2026</title><link>/weekly/2026-w26/</link><pubDate>Mon, 29 Jun 2026 00:00:00 +0000</pubDate><guid>/weekly/2026-w26/</guid><description>&lt;p>June 29 — July 5, 2026&lt;/p>
&lt;h2 class="heading" id="this-week">
 This week
 &lt;a href="#this-week">#&lt;/a>
&lt;/h2>
&lt;ul>
&lt;li>Revived this site as a public record of a 6-month research engineering trajectory.&lt;/li>
&lt;li>Settled on a structure: transformers + LLM inference + efficient kernels as the core trunk; agents, SOTA papers, and TypeScript literacy as satellites.&lt;/li>
&lt;li>Blocked study time on the calendar for the next 8 weeks.&lt;/li>
&lt;li>Started a living note to track direction: &lt;a href="/projects/research-engineer-trajectory/">Research Engineer Trajectory&lt;/a>.&lt;/li>
&lt;/ul>
&lt;h2 class="heading" id="up-next">
 Up next
 &lt;a href="#up-next">#&lt;/a>
&lt;/h2>
&lt;ul>
&lt;li>Read the Word2Vec paper and understand CBOW / skip-gram / negative sampling.&lt;/li>
&lt;li>Implement Word2Vec from scratch in NumPy or raw PyTorch.&lt;/li>
&lt;li>Explore &lt;a href="https://github.com/huggingface/tau">Tau&lt;/a> as a Python agent harness for MVF work.&lt;/li>
&lt;/ul>
&lt;h2 class="heading" id="open-questions">
 Open questions
 &lt;a href="#open-questions">#&lt;/a>
&lt;/h2>
&lt;ul>
&lt;li>What part of the transformer/inference stack lights me up most as I go deeper?&lt;/li>
&lt;li>How much focused work can I realistically get from the 3–7pm weekday blocks?&lt;/li>
&lt;/ul></description></item><item><title>Hello again</title><link>/posts/my-first-post/</link><pubDate>Sun, 02 Feb 2025 00:00:00 +0000</pubDate><guid>/posts/my-first-post/</guid><description>&lt;p>This site is being revived as a public record of my work and learning.&lt;/p>
&lt;p>Expect:&lt;/p>
&lt;ul>
&lt;li>&lt;strong>Weekly notes&lt;/strong> — what I studied, built, and got wrong.&lt;/li>
&lt;li>&lt;strong>Posts&lt;/strong> — deeper writeups on transformers, inference, and systems.&lt;/li>
&lt;li>&lt;strong>Projects&lt;/strong> — code, experiments, and reproductions.&lt;/li>
&lt;/ul>
&lt;p>Current focus: understanding large language models from the math to the metal.&lt;/p></description></item></channel></rss>