<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>System Architecture on MacWorks</title><link>https://macworks.dev/tags/system-architecture/</link><description>Recent content in System Architecture on MacWorks</description><generator>Hugo</generator><language>en</language><atom:link href="https://macworks.dev/tags/system-architecture/index.xml" rel="self" type="application/rss+xml"/><item><title>Week 14 Summary</title><link>https://macworks.dev/docs/month/tech-videos/weekly-2026-W14/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/month/tech-videos/weekly-2026-W14/</guid><description>&lt;h1 id="tech-videos--week-of-2026-03-28-to-2026-04-03"&gt;Tech Videos — Week of 2026-03-28 to 2026-04-03&lt;a class="anchor" href="#tech-videos--week-of-2026-03-28-to-2026-04-03"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="watch-first"&gt;Watch First&lt;a class="anchor" href="#watch-first"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;For the most impactful video, the Syntax channel&amp;rsquo;s &lt;a href="#"&gt;37,000 Lines of Slop&lt;/a&gt; is the single best watch this week because it provides a brutal, necessary teardown of AI coding hype. It vividly demonstrates why blindly shipping massive LLM output without rigorous human review results in catastrophic production payloads, cutting through the marketing noise of effortless AI development.&lt;/p&gt;
&lt;h2 id="week-in-review"&gt;Week in Review&lt;a class="anchor" href="#week-in-review"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;The dominant theme this week is the awkward transition from isolated LLM chat interfaces to orchestrated, tool-using agents, exposing massive friction in both security and developer workflows. We are also seeing a definitive industry shift toward inference-bound hardware architectures, as scaling laws collide with concrete power, memory, and cooling bottlenecks.&lt;/p&gt;</description></item><item><title>Tech Company Blogs</title><link>https://macworks.dev/docs/week/tech/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/</guid><description>&lt;h1 id="engineering--scale--week-of-2026-04-03-to-2026-04-10"&gt;Engineering @ Scale — Week of 2026-04-03 to 2026-04-10&lt;a class="anchor" href="#engineering--scale--week-of-2026-04-03-to-2026-04-10"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="week-in-review"&gt;Week in Review&lt;a class="anchor" href="#week-in-review"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;This week, the industry rapidly shifted from conversational AI paradigms to formal &amp;ldquo;Agentic Infrastructure,&amp;rdquo; prioritizing strict deterministic guardrails over massive, unstructured context windows. Top organizations are aggressively fracturing monolithic processes—whether it is breaking down massive LLM prompts into specialized sub-agents, federating sprawling databases, or shifting compute-heavy security mitigation entirely to the network edge—to manage the unbounded scaling demands of machine actors.&lt;/p&gt;</description></item><item><title>2026-04-07</title><link>https://macworks.dev/docs/week/tech/tech-2026-04-07/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/week/tech/tech-2026-04-07/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-07"&gt;Engineering @ Scale — 2026-04-07&lt;a class="anchor" href="#engineering--scale--2026-04-07"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;By implementing an LLM-based risk classifier as an executable guardrail, Vercel successfully automated 58% of monorepo pull request merges without increasing revert rates. This demonstrates that mature codebases often suffer from review capacity misallocation rather than a lack of verification capability, making automated risk routing a highly effective scaling lever.&lt;/p&gt;</description></item><item><title>2026-04-03</title><link>https://macworks.dev/docs/archives/tech-videos/tech-videos-2026-04-03/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/archives/tech-videos/tech-videos-2026-04-03/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UULKPca3kwwd-B59HNr-_lvA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;AI Engineer&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUESLZhusAkFfsNsApnjF_Cg&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;All-In Podcast&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUXUPKJO5MZQN11PqgIvyuvQ&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Andrej Karpathy&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUrDwWp7EBBv4NwvScIpBDOA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Anthropic&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUE_M8A5yxnLfW0KghEeajjw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Apple&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUwrVwiJllwhJUKXKmjLcckQ&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Apple Developer&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUdoadna9HFHsxXWhafhNvKw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;AWS Events&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUZgt6AzoyjslHTC9dz0UoTw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UU9-y-6csu5WGm29I7JiwpnA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Computerphile&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UU6YYHJzM6PhZ2Yey9BQiUaw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Cursor&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUXl4i9dYBrFOabk0xGmbkRA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Dwarkesh Patel&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUlWTCPVi-AU9TeCN6FkGARg&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;EO&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUsBjURrPoezykLs9EqgamOA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Fireship&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UU7c3Kb6jYCRj4JOHHZTxKsQ&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;GitHub&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUJS9pqu9BzkAMNTmzNMNhvg&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Google Cloud Tech&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUP7jMXSY2xbc3KCAE0MHQ-A&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UU_x5XG1OV2P6uZZ5FSM9Ttw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Google for Developers&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UU2ggjtuuWvxrHHHiaDH1dlQ&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Hung-yi Lee&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UU6t1O76G0jYXOAoYCm153dA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Lenny&amp;#39;s Podcast&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUJIfeSCssxSC_Dhc5s7woww&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Lex Clips&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUSHZKyawb77ixDdsGog4iWA&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Lex Fridman&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUWIzrKzN4KY6BPU8hsk880Q&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Life at Google&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUBJycsmduvYEL83R_U4JriQ&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Marques Brownlee&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUFtEEv80fQVKkD4h1PF-Xqw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Microsoft&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUSI7h9hydQ40K5MJHnCrQvw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;No Priors: AI, Machine Learning, Tech, &amp;amp; Startups&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUoxcjq-8xIDTYp3uz647V5A&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Numberphile&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUHuiy8bXnmK5nisYHUd1J5g&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;NVIDIA&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUXZCJLdBC09xxGZ6gcdrc6A&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;OpenAI&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUYqxnCFtaC4-iC_bwt2bRLg&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Perplexity&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUTpmmkp1E4nmZqWPS-dl5bg&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Quanta Magazine&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUY3YECgeBcLCzIrFLP4gblw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Slack&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUPbwhExawYrn9xxI21TFfyw&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;The Pragmatic Engineer&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.youtube.com/playlist?list=UUs5Y5_7XK8HLDX0SLNwkd3w&amp;amp;bq_guid_format=yt%3Avideo%3AVIDEO_ID"&gt;Visual Studio Code&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="tech-videos--2026-04-03"&gt;Tech Videos — 2026-04-03&lt;a class="anchor" href="#tech-videos--2026-04-03"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="watch-first"&gt;Watch First&lt;a class="anchor" href="#watch-first"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;&lt;a href="https://www.youtube.com/watch?v=1r9n-HsBQsE"&gt;37,000 Lines of Slop&lt;/a&gt;
A vital, pragmatic teardown of AI-generated code hype that demonstrates why blindly shipping 37,000 lines of LLM output a day results in catastrophic, unreviewed production payloads.&lt;/p&gt;</description></item><item><title>2026-04-04</title><link>https://macworks.dev/docs/archives/tech/tech-2026-04-04/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/archives/tech/tech-2026-04-04/</guid><description>&lt;details&gt;
&lt;summary&gt;Sources&lt;/summary&gt;
&lt;div class="markdown-inner"&gt;
&lt;ul&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/airbnb-engineering"&gt;Airbnb Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/machine-learning/feed/"&gt;Amazon AWS AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/cn/blogs/architecture/feed/"&gt;AWS Architecture Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://aws.amazon.com/blogs/opensource/feed/"&gt;AWS Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://brett.trpstra.net/brettterpstra"&gt;BrettTerpstra.com&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.bytebytego.com/feed"&gt;ByteByteGo&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.cloudflare.com/rss/"&gt;CloudFlare&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://dropbox.tech/feed"&gt;Dropbox Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.fb.com/feed/"&gt;Facebook Code&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/engineering.atom"&gt;GitHub Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.google/innovation-and-ai/technology/ai/rss/"&gt;Google AI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://deepmind.google/blog/rss.xml"&gt;Google DeepMind&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/GoogleOpenSourceBlog"&gt;Google Open Source Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.hashicorp.com/blog/feed.xml"&gt;HashiCorp Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://feed.infoq.com/?token=XQ47eEiAJqUtN8043NhEqJ6kZB8XallO"&gt;InfoQ&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineering.atspotify.com/feed/"&gt;Spotify Engineering&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://www.microsoft.com/en-us/research/feed/"&gt;Microsoft Research&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://hacks.mozilla.org/feed/"&gt;Mozilla Hacks&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://netflixtechblog.com/feed"&gt;Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/nvidiablog"&gt;NVIDIA Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="http://feeds.feedburner.com/oreilly/radar/atom"&gt;O&amp;#39;Reilly Radar&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://openai.com/news/rss.xml"&gt;OpenAI Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://developers.soundcloud.com/blog/blog.rss"&gt;SoundCloud Backstage Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://stripe.com/blog/feed.rss"&gt;Stripe Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://rsshub.bestblogs.dev/deeplearning/the-batch"&gt;The Batch | DeepLearning.AI | AI News &amp;amp; Insights&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blog.dropbox.com/feed"&gt;The Dropbox Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://github.blog/feed/"&gt;The GitHub Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://medium.com/feed/netflix-techblog"&gt;The Netflix Tech Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://blogs.microsoft.com/feed/"&gt;The Official Microsoft Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://vercel.com/atom"&gt;Vercel Blog&lt;/a&gt;&lt;/li&gt;

&lt;li&gt;&lt;a href="https://engineeringblog.yelp.com/feed.xml"&gt;Yelp Engineering and Product Blog&lt;/a&gt;&lt;/li&gt;

&lt;/ul&gt;
&lt;/div&gt;
&lt;/details&gt;


&lt;h1 id="engineering--scale--2026-04-04"&gt;Engineering @ Scale — 2026-04-04&lt;a class="anchor" href="#engineering--scale--2026-04-04"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="signal-of-the-day"&gt;Signal of the Day&lt;a class="anchor" href="#signal-of-the-day"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;When fusing high-dimensional, wildly heterogeneous data at scale, decouple your high-speed ingestion from your computational intersections. Netflix demonstrated that by discretizing continuous multimodal AI outputs into fixed one-second temporal buckets offline, they could bypass massive computational hurdles and achieve sub-second query latency without bottlenecking real-time data intake.&lt;/p&gt;</description></item></channel></rss>