<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>schristoph.online</title><link>https://schristoph.online/tags/contentpipeline/</link><description>Personal homepage and blog of Stefan Christoph</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>Stefan Christoph. All rights reserved.</copyright><lastBuildDate>Sun, 14 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://schristoph.online/tags/contentpipeline/index.xml" rel="self" type="application/rss+xml"/><item><title>Weekly Review — June 8-14, 2026</title><link>https://schristoph.online/weekly/weekly-review-2026-w24/?utm=rss-feed</link><pubDate>Sun, 14 Jun 2026 00:00:00 +0000</pubDate><guid>https://schristoph.online/weekly/weekly-review-2026-w24/</guid><description>&lt;div class="tldr" data-pagefind-weight="5" data-pagefind-meta="tldr" style="display:block;font-size:.875em;margin:2rem 0;border-left:4px solid #ccc;padding-left:1rem;line-height:1.5;">&lt;strong>TL;DR:&lt;/strong> Six posts this week, all circling one idea: with AI systems, raw model power is rarely the differentiator — the structure, governance, and craft &lt;em>around&lt;/em> the model are. A paper (and a Bedrock reproduction) shows your cheapest model writes agent harness updates as well as a frontier one; two pipeline deep-dives show quality comes from systematic editing passes and disciplined voice-matching; a day-one Claude Fable 5 run shows the real decision is the data-retention switch, not the latency; and AWS quietly closed the CLI&amp;rsquo;s multi-account advantage with a stricter MCP design. Plus a build-log on cloning my own voice on SageMaker.&lt;/div>
&lt;p>This is the Weekly Review, a Sunday digest of everything that went up on the blog this week, plus a short list of things I read but didn&amp;rsquo;t write about. If you only have ten minutes on a Sunday, this is the one to read.&lt;/p></description></item><item><title>Weekly Review — June 1-7, 2026</title><link>https://schristoph.online/weekly/weekly-review-2026-w23/?utm=rss-feed</link><pubDate>Sun, 07 Jun 2026 00:00:00 +0000</pubDate><guid>https://schristoph.online/weekly/weekly-review-2026-w23/</guid><description>&lt;div class="tldr" data-pagefind-weight="5" data-pagefind-meta="tldr" style="display:block;font-size:.875em;margin:2rem 0;border-left:4px solid #ccc;padding-left:1rem;line-height:1.5;">&lt;strong>TL;DR:&lt;/strong> Six posts went out this week, and three of them kept circling the same idea: reliability in AI agents does not come from better prompts, it comes from structure. Boundaries, constraints, and code. Add two deep-dive pipeline posts, a working agent that pays real money, and two frontier models meeting on Bedrock, and you get a week that was equal parts theory and &amp;ldquo;I actually built this.&amp;rdquo; Below is the recap, the thread tying it together, and five public reads worth your time.&lt;/div>
&lt;p>This is the first Weekly Review, a Sunday digest of everything that went up on the blog this week, plus a short list of things I read but didn&amp;rsquo;t write about. The goal is simple: if you only have ten minutes on a Sunday, this is the one to read.&lt;/p></description></item></channel></rss>